From 90500da351a1f1858e3fa570d54cb956bda993ac Mon Sep 17 00:00:00 2001 From: Johnny Greco Date: Wed, 24 Jun 2026 17:32:46 +0000 Subject: [PATCH 01/45] Add Reachy Mini OpenShell research scaffold --- projects/README.md | 8 + projects/reachy-mini-openshell/.dockerignore | 10 + projects/reachy-mini-openshell/.gitignore | 8 + projects/reachy-mini-openshell/Dockerfile | 40 ++++ projects/reachy-mini-openshell/Makefile | 22 ++ projects/reachy-mini-openshell/README.md | 95 +++++++++ .../docs/research-plan.md | 31 +++ .../openshell/policy.local-sim.yaml | 36 ++++ projects/reachy-mini-openshell/pyproject.toml | 33 +++ .../src/reachy_openshell/__init__.py | 2 + .../src/reachy_openshell/backend.py | 190 ++++++++++++++++++ .../src/reachy_openshell/smoke.py | 108 ++++++++++ 12 files changed, 583 insertions(+) create mode 100644 projects/README.md create mode 100644 projects/reachy-mini-openshell/.dockerignore create mode 100644 projects/reachy-mini-openshell/.gitignore create mode 100644 projects/reachy-mini-openshell/Dockerfile create mode 100644 projects/reachy-mini-openshell/Makefile create mode 100644 projects/reachy-mini-openshell/README.md create mode 100644 projects/reachy-mini-openshell/docs/research-plan.md create mode 100644 projects/reachy-mini-openshell/openshell/policy.local-sim.yaml create mode 100644 projects/reachy-mini-openshell/pyproject.toml create mode 100644 projects/reachy-mini-openshell/src/reachy_openshell/__init__.py create mode 100644 projects/reachy-mini-openshell/src/reachy_openshell/backend.py create mode 100644 projects/reachy-mini-openshell/src/reachy_openshell/smoke.py diff --git a/projects/README.md b/projects/README.md new file mode 100644 index 00000000..08fc37c2 --- /dev/null +++ b/projects/README.md @@ -0,0 +1,8 @@ +# Projects + +This directory contains self-contained research projects. Each project should live in its own subfolder with its own dependencies, runtime notes, and source layout. + +Current projects: + +- `reachy-mini-openshell`: Reachy Mini simulator/backend research for running the backend inside an OpenShell runtime. + diff --git a/projects/reachy-mini-openshell/.dockerignore b/projects/reachy-mini-openshell/.dockerignore new file mode 100644 index 00000000..75e643c1 --- /dev/null +++ b/projects/reachy-mini-openshell/.dockerignore @@ -0,0 +1,10 @@ +.git +.venv +__pycache__ +*.pyc +*.pyo +.pytest_cache +.ruff_cache +dist +*.egg-info + diff --git a/projects/reachy-mini-openshell/.gitignore b/projects/reachy-mini-openshell/.gitignore new file mode 100644 index 00000000..9c30bb62 --- /dev/null +++ b/projects/reachy-mini-openshell/.gitignore @@ -0,0 +1,8 @@ +.venv/ +__pycache__/ +*.py[cod] +.pytest_cache/ +.ruff_cache/ +dist/ +*.egg-info/ + diff --git a/projects/reachy-mini-openshell/Dockerfile b/projects/reachy-mini-openshell/Dockerfile new file mode 100644 index 00000000..1a83bbcb --- /dev/null +++ b/projects/reachy-mini-openshell/Dockerfile @@ -0,0 +1,40 @@ +FROM ghcr.io/nvidia/openshell-community/sandboxes/base:latest + +USER root +WORKDIR /sandbox/reachy-mini-openshell + +RUN apt-get update \ + && apt-get install -y --no-install-recommends \ + build-essential \ + pkg-config \ + python3-dev \ + libcairo2-dev \ + libgirepository1.0-dev \ + libglib2.0-dev \ + libgstreamer-plugins-bad1.0-dev \ + libgstreamer-plugins-base1.0-dev \ + libgstreamer1.0-dev \ + libnice10 \ + libportaudio2 \ + libssl-dev \ + gstreamer1.0-alsa \ + gstreamer1.0-nice \ + gstreamer1.0-plugins-bad \ + gstreamer1.0-plugins-good \ + python3-gi \ + python3-gi-cairo \ + && rm -rf /var/lib/apt/lists/* + +COPY pyproject.toml README.md ./ +COPY src ./src + +RUN python3 -m venv /opt/reachy-mini-openshell +ENV PATH="/opt/reachy-mini-openshell/bin:${PATH}" +ENV PYTHONDONTWRITEBYTECODE=1 + +RUN pip install --no-cache-dir ".[backend,sdk]" +RUN chown -R sandbox:sandbox /sandbox/reachy-mini-openshell /opt/reachy-mini-openshell + +USER sandbox + +CMD ["python3", "-m", "reachy_openshell.backend", "--host", "0.0.0.0", "--port", "8080"] diff --git a/projects/reachy-mini-openshell/Makefile b/projects/reachy-mini-openshell/Makefile new file mode 100644 index 00000000..ce34839a --- /dev/null +++ b/projects/reachy-mini-openshell/Makefile @@ -0,0 +1,22 @@ +UV ?= uv +PYTHON ?= python3 + +.PHONY: install install-backend install-sim sim smoke backend + +install: + $(UV) pip install -e ".[backend,sdk]" + +install-backend: + $(UV) pip install -e ".[backend]" + +install-sim: + $(UV) pip install -e ".[backend,sim]" + +sim: + reachy-mini-daemon --sim --scene $${REACHY_SCENE:-minimal} + +smoke: + $(PYTHON) -m reachy_openshell.smoke + +backend: + $(PYTHON) -m reachy_openshell.backend diff --git a/projects/reachy-mini-openshell/README.md b/projects/reachy-mini-openshell/README.md new file mode 100644 index 00000000..9ae54b84 --- /dev/null +++ b/projects/reachy-mini-openshell/README.md @@ -0,0 +1,95 @@ +# Reachy Mini OpenShell Research + +Minimal research scaffold for running a Reachy Mini backend inside an OpenShell sandbox while starting against the Reachy Mini MuJoCo simulator. + +## Current Shape + +- Host process: runs `reachy-mini-daemon --sim`, which starts the simulator and exposes the daemon API on port `8000`. +- OpenShell process: runs this backend in a sandbox and connects to the host daemon through `host.openshell.internal:8000`. +- First backend surface: `GET /health` for daemon reachability and `POST /moves/smoke` for a small head/antenna motion. + +## Local Simulator Quickstart + +On Linux, install the Reachy Mini GStreamer prerequisites before installing the SDK. The upstream guide lists the full package set and notes that Ubuntu 22.04 needs newer GStreamer packages. + +```bash +cd projects/reachy-mini-openshell +uv venv --python 3.12 +source .venv/bin/activate +uv pip install -e ".[backend,sim]" +``` + +Start the simulator: + +```bash +reachy-mini-daemon --sim --scene minimal +``` + +In another terminal: + +```bash +source .venv/bin/activate +python -m reachy_openshell.smoke +python -m reachy_openshell.backend +``` + +Then probe the backend: + +```bash +curl http://127.0.0.1:8080/health +curl -X POST http://127.0.0.1:8080/moves/smoke +``` + +On macOS, the Reachy docs recommend launching the simulator with `mjpython` instead: + +```bash +mjpython -m reachy_mini.daemon.app.main --sim +``` + +## OpenShell Sandbox Path + +For the sandboxed backend to reach a host-level simulator, bind the Reachy daemon to an interface visible from containers: + +```bash +reachy-mini-daemon --sim --scene minimal --fastapi-host 0.0.0.0 --fastapi-port 8000 +``` + +If your installed daemon exposes different flag names, check `reachy-mini-daemon --help`; the important part is that the daemon is reachable from the sandbox at `host.openshell.internal:8000`. + +Build and run the backend in OpenShell: + +```bash +openshell status +openshell sandbox create \ + --name reachy-mini-backend \ + --from . \ + --policy openshell/policy.local-sim.yaml \ + --env REACHY_HOST=host.openshell.internal \ + --env REACHY_PORT=8000 \ + --env REACHY_CONNECTION_MODE=network \ + -- python3 -m reachy_openshell.backend --host 0.0.0.0 --port 8080 +``` + +Expose the backend service: + +```bash +openshell service expose reachy-mini-backend 8080 +``` + +The sandbox image installs the Linux system packages needed by the Reachy SDK before installing the Python package. + +## Layout + +- `src/reachy_openshell/smoke.py`: SDK smoke motion for the simulator or a real robot daemon. +- `src/reachy_openshell/backend.py`: small FastAPI backend for health checks and the smoke motion. +- `openshell/policy.local-sim.yaml`: starter OpenShell policy allowing Python to reach the host simulator daemon. +- `Dockerfile`: OpenShell sandbox image for the backend, based on the OpenShell community base sandbox. + +## References + +- Reachy Mini simulator setup: https://huggingface.co/docs/reachy_mini/en/platforms/simulation/get_started +- Reachy Mini Linux GStreamer prerequisites: https://huggingface.co/docs/reachy_mini/en/SDK/gstreamer-installation +- Reachy Mini SDK API: https://huggingface.co/docs/reachy_mini/en/API/reachymini +- OpenShell overview: https://docs.nvidia.com/openshell/about/overview +- OpenShell sandbox management: https://docs.nvidia.com/openshell/sandboxes/manage-sandboxes +- OpenShell policy reference: https://docs.nvidia.com/openshell/reference/policy-schema diff --git a/projects/reachy-mini-openshell/docs/research-plan.md b/projects/reachy-mini-openshell/docs/research-plan.md new file mode 100644 index 00000000..adce629f --- /dev/null +++ b/projects/reachy-mini-openshell/docs/research-plan.md @@ -0,0 +1,31 @@ +# Research Plan + +## Working Hypothesis + +Keep the simulator on the host for the first spike so MuJoCo can open its viewer normally. Run only the backend in OpenShell. The sandbox reaches the host daemon through `host.openshell.internal:8000`, using a narrow OpenShell network policy. + +## Phase 0: Simulator Bootstrap + +- Install `reachy-mini[mujoco]` locally. +- Start `reachy-mini-daemon --sim --scene minimal`. +- Verify the Python SDK can connect and run the smoke motion. + +## Phase 1: Sandboxed Backend + +- Build the local OpenShell sandbox image from `Dockerfile`. +- Run `python3 -m reachy_openshell.backend` inside the sandbox. +- Confirm `GET /health` reaches the simulator daemon. +- Confirm `POST /moves/smoke` moves the simulated robot. + +## Phase 2: Policy Tightening + +- Capture the exact daemon traffic used by the SDK. +- Replace the current L4 passthrough policy with REST and WebSocket rules if the daemon API remains stable enough. +- Decide whether PyPI access is needed at runtime or only at image build time. + +## Open Questions + +- Should the simulator stay host-side for development, or should a headless simulator move into its own OpenShell sandbox later? +- Which daemon bind flags are stable across Reachy Mini SDK versions and operating systems? +- Do audio and camera paths need to be disabled or mocked for OpenShell-based backend tests? + diff --git a/projects/reachy-mini-openshell/openshell/policy.local-sim.yaml b/projects/reachy-mini-openshell/openshell/policy.local-sim.yaml new file mode 100644 index 00000000..ebff2820 --- /dev/null +++ b/projects/reachy-mini-openshell/openshell/policy.local-sim.yaml @@ -0,0 +1,36 @@ +version: 1 + +filesystem_policy: + include_workdir: true + read_only: + - /usr + - /lib + - /lib64 + - /etc + - /bin + - /sbin + - /opt + read_write: + - /sandbox + - /workspace + - /tmp + +landlock: + compatibility: best_effort + +process: + run_as_user: sandbox + run_as_group: sandbox + +network_policies: + reachy_daemon: + name: reachy-daemon-local-simulator + endpoints: + - host: host.openshell.internal + port: 8000 + binaries: + - path: /usr/bin/python* + - path: /usr/local/bin/python* + - path: /opt/reachy-mini-openshell/bin/python* + - path: /sandbox/**/python* + diff --git a/projects/reachy-mini-openshell/pyproject.toml b/projects/reachy-mini-openshell/pyproject.toml new file mode 100644 index 00000000..07029d0c --- /dev/null +++ b/projects/reachy-mini-openshell/pyproject.toml @@ -0,0 +1,33 @@ +[build-system] +requires = ["hatchling>=1.25"] +build-backend = "hatchling.build" + +[project] +name = "reachy-mini-openshell" +version = "0.1.0" +description = "Research scaffold for running a Reachy Mini backend in OpenShell against a Reachy Mini simulator." +readme = "README.md" +requires-python = ">=3.10" +dependencies = [] + +[project.optional-dependencies] +backend = [ + "fastapi>=0.115,<1", + "uvicorn[standard]>=0.30,<1", +] +sdk = [ + "reachy-mini>=1.8.3,<2", +] +sim = [ + "reachy-mini[mujoco]>=1.8.3,<2", +] +dev = [ + "ruff>=0.8,<1", +] + +[project.scripts] +reachy-backend = "reachy_openshell.backend:main" +reachy-smoke = "reachy_openshell.smoke:main" + +[tool.hatch.build.targets.wheel] +packages = ["src/reachy_openshell"] diff --git a/projects/reachy-mini-openshell/src/reachy_openshell/__init__.py b/projects/reachy-mini-openshell/src/reachy_openshell/__init__.py new file mode 100644 index 00000000..f38884b6 --- /dev/null +++ b/projects/reachy-mini-openshell/src/reachy_openshell/__init__.py @@ -0,0 +1,2 @@ +__version__ = "0.1.0" + diff --git a/projects/reachy-mini-openshell/src/reachy_openshell/backend.py b/projects/reachy-mini-openshell/src/reachy_openshell/backend.py new file mode 100644 index 00000000..39f8c5fc --- /dev/null +++ b/projects/reachy-mini-openshell/src/reachy_openshell/backend.py @@ -0,0 +1,190 @@ +from __future__ import annotations + +import argparse +import asyncio +import os +import sys +import urllib.error +import urllib.request +from dataclasses import asdict, dataclass +from typing import Any + +from . import __version__ + +LOCAL_HOSTS = {"localhost", "127.0.0.1", "::1"} + +try: + from fastapi import FastAPI, HTTPException +except ImportError: # pragma: no cover - exercised only when optional deps are absent. + FastAPI = None # type: ignore[assignment] + HTTPException = None # type: ignore[assignment] + + +@dataclass(frozen=True) +class Settings: + reachy_host: str + reachy_port: int + connection_mode: str + timeout: float + + @classmethod + def from_env(cls) -> "Settings": + host = os.getenv("REACHY_HOST", "localhost") + return cls( + reachy_host=host, + reachy_port=_env_int("REACHY_PORT", 8000), + connection_mode=os.getenv("REACHY_CONNECTION_MODE", _default_connection_mode(host)), + timeout=_env_float("REACHY_TIMEOUT", 5.0), + ) + + @property + def daemon_base_url(self) -> str: + return f"http://{self.reachy_host}:{self.reachy_port}" + + +def _env_int(name: str, default: int) -> int: + raw = os.getenv(name) + if raw is None: + return default + try: + return int(raw) + except ValueError as exc: + raise ValueError(f"{name} must be an integer, got {raw!r}") from exc + + +def _env_float(name: str, default: float) -> float: + raw = os.getenv(name) + if raw is None: + return default + try: + return float(raw) + except ValueError as exc: + raise ValueError(f"{name} must be a number, got {raw!r}") from exc + + +def _default_connection_mode(host: str) -> str: + return "localhost_only" if host in LOCAL_HOSTS else "network" + + +def daemon_status(settings: Settings) -> dict[str, Any]: + url = f"{settings.daemon_base_url}/api/daemon/status" + try: + with urllib.request.urlopen(url, timeout=settings.timeout) as response: + body = response.read(4096).decode("utf-8", errors="replace") + return { + "ok": 200 <= response.status < 500, + "status_code": response.status, + "url": url, + "body": body, + } + except (urllib.error.URLError, TimeoutError, OSError) as exc: + return { + "ok": False, + "url": url, + "error": str(exc), + } + + +def run_smoke_motion(settings: Settings) -> dict[str, Any]: + try: + from reachy_mini import ReachyMini + from reachy_mini.utils import create_head_pose + except ImportError as exc: + raise RuntimeError( + "Reachy Mini SDK is not installed. Install with `uv pip install -e .` " + "or include the `sim` extra for local simulator work." + ) from exc + + with ReachyMini( + host=settings.reachy_host, + port=settings.reachy_port, + connection_mode=settings.connection_mode, + spawn_daemon=False, + timeout=settings.timeout, + ) as mini: + mini.goto_target( + head=create_head_pose(z=20, roll=10, mm=True, degrees=True), + duration=1.0, + ) + mini.goto_target(antennas=[0.6, -0.6], duration=0.3) + mini.goto_target(antennas=[-0.6, 0.6], duration=0.3) + mini.goto_target( + head=create_head_pose(), + antennas=[0.0, 0.0], + duration=1.0, + ) + + return { + "ok": True, + "reachy": asdict(settings), + "motion": "smoke", + } + + +def _create_app() -> Any: + if FastAPI is None: + return None + + api = FastAPI( + title="Reachy Mini OpenShell Backend", + version=__version__, + ) + + @api.get("/health") + def health() -> dict[str, Any]: + settings = Settings.from_env() + status = daemon_status(settings) + return { + "ok": status["ok"], + "reachy": asdict(settings), + "daemon": status, + } + + @api.post("/moves/smoke") + async def smoke_move() -> dict[str, Any]: + settings = Settings.from_env() + try: + return await asyncio.to_thread(run_smoke_motion, settings) + except Exception as exc: # pragma: no cover - depends on live daemon. + raise HTTPException(status_code=502, detail=str(exc)) from exc + + return api + + +app = _create_app() + + +def main(argv: list[str] | None = None) -> int: + if FastAPI is None: + print( + "FastAPI is not installed. Install backend dependencies with " + '`uv pip install -e ".[backend]"`.', + file=sys.stderr, + ) + return 2 + + parser = argparse.ArgumentParser(description="Run the Reachy Mini OpenShell backend.") + parser.add_argument("--host", default=os.getenv("BACKEND_HOST", "0.0.0.0")) + parser.add_argument("--port", type=int, default=_env_int("BACKEND_PORT", 8080)) + parser.add_argument("--reachy-host", default=None) + parser.add_argument("--reachy-port", type=int, default=None) + parser.add_argument("--connection-mode", default=None) + parser.add_argument("--log-level", default=os.getenv("UVICORN_LOG_LEVEL", "info")) + args = parser.parse_args(argv) + + if args.reachy_host is not None: + os.environ["REACHY_HOST"] = args.reachy_host + if args.reachy_port is not None: + os.environ["REACHY_PORT"] = str(args.reachy_port) + if args.connection_mode is not None: + os.environ["REACHY_CONNECTION_MODE"] = args.connection_mode + + import uvicorn + + uvicorn.run(app, host=args.host, port=args.port, log_level=args.log_level) + return 0 + + +if __name__ == "__main__": + raise SystemExit(main()) + diff --git a/projects/reachy-mini-openshell/src/reachy_openshell/smoke.py b/projects/reachy-mini-openshell/src/reachy_openshell/smoke.py new file mode 100644 index 00000000..f86a7ac2 --- /dev/null +++ b/projects/reachy-mini-openshell/src/reachy_openshell/smoke.py @@ -0,0 +1,108 @@ +from __future__ import annotations + +import argparse +import os +import sys +from dataclasses import dataclass + +LOCAL_HOSTS = {"localhost", "127.0.0.1", "::1"} + + +@dataclass(frozen=True) +class ReachyTarget: + host: str + port: int + connection_mode: str + timeout: float + + +def _env_int(name: str, default: int) -> int: + raw = os.getenv(name) + if raw is None: + return default + try: + return int(raw) + except ValueError as exc: + raise ValueError(f"{name} must be an integer, got {raw!r}") from exc + + +def _env_float(name: str, default: float) -> float: + raw = os.getenv(name) + if raw is None: + return default + try: + return float(raw) + except ValueError as exc: + raise ValueError(f"{name} must be a number, got {raw!r}") from exc + + +def _default_connection_mode(host: str) -> str: + return "localhost_only" if host in LOCAL_HOSTS else "network" + + +def build_parser() -> argparse.ArgumentParser: + default_host = os.getenv("REACHY_HOST", "localhost") + parser = argparse.ArgumentParser(description="Run a small Reachy Mini SDK smoke motion.") + parser.add_argument("--host", default=default_host) + parser.add_argument("--port", type=int, default=_env_int("REACHY_PORT", 8000)) + parser.add_argument( + "--connection-mode", + choices=["auto", "localhost_only", "network"], + default=os.getenv("REACHY_CONNECTION_MODE", _default_connection_mode(default_host)), + ) + parser.add_argument("--timeout", type=float, default=_env_float("REACHY_TIMEOUT", 5.0)) + return parser + + +def run_motion(target: ReachyTarget) -> None: + try: + from reachy_mini import ReachyMini + from reachy_mini.utils import create_head_pose + except ImportError as exc: + raise RuntimeError( + "Reachy Mini SDK is not installed. Install with `uv pip install -e .` " + "or `uv pip install -e '.[sim]'` for simulator work." + ) from exc + + with ReachyMini( + host=target.host, + port=target.port, + connection_mode=target.connection_mode, + spawn_daemon=False, + timeout=target.timeout, + ) as mini: + print(f"Connected to Reachy Mini daemon at {target.host}:{target.port}") + print("Moving head and antennas...") + mini.goto_target( + head=create_head_pose(z=20, roll=10, mm=True, degrees=True), + duration=1.0, + ) + mini.goto_target(antennas=[0.6, -0.6], duration=0.3) + mini.goto_target(antennas=[-0.6, 0.6], duration=0.3) + mini.goto_target( + head=create_head_pose(), + antennas=[0.0, 0.0], + duration=1.0, + ) + print("Smoke motion complete.") + + +def main(argv: list[str] | None = None) -> int: + args = build_parser().parse_args(argv) + target = ReachyTarget( + host=args.host, + port=args.port, + connection_mode=args.connection_mode, + timeout=args.timeout, + ) + try: + run_motion(target) + except Exception as exc: + print(f"Reachy smoke motion failed: {exc}", file=sys.stderr) + return 1 + return 0 + + +if __name__ == "__main__": + raise SystemExit(main()) + From a7ba27e21d08c666e62d50a79889299681790177 Mon Sep 17 00:00:00 2001 From: Johnny Greco Date: Wed, 24 Jun 2026 17:41:20 +0000 Subject: [PATCH 02/45] Address Reachy scaffold review findings --- README.md | 2 + projects/reachy-mini-openshell/README.md | 8 +- .../openshell/policy.local-sim.yaml | 3 - .../src/reachy_openshell/backend.py | 9 +- .../src/reachy_openshell/smoke.py | 7 +- .../tests/test_reachy_constructors.py | 85 +++++++++++++++++++ 6 files changed, 106 insertions(+), 8 deletions(-) create mode 100644 projects/reachy-mini-openshell/tests/test_reachy_constructors.py diff --git a/README.md b/README.md index 1ef43ce5..f54acf22 100644 --- a/README.md +++ b/README.md @@ -12,6 +12,8 @@ OpenShell as the runtime. - `docs/dev-notes/` contains research engineering updates, release notes, and build logs worth sharing. - `docs/dev-notes/authors.json` contains reusable Dev Notes author metadata. +- `projects/` contains self-contained research project folders, including the + Reachy Mini OpenShell simulator/backend scaffold. - `scripts/render-dev-notes.py` renders Dev Notes cards, post bylines, and navigation entries from post front matter. - `zensical.toml` configures the documentation site. diff --git a/projects/reachy-mini-openshell/README.md b/projects/reachy-mini-openshell/README.md index 9ae54b84..d29ca663 100644 --- a/projects/reachy-mini-openshell/README.md +++ b/projects/reachy-mini-openshell/README.md @@ -7,10 +7,15 @@ Minimal research scaffold for running a Reachy Mini backend inside an OpenShell - Host process: runs `reachy-mini-daemon --sim`, which starts the simulator and exposes the daemon API on port `8000`. - OpenShell process: runs this backend in a sandbox and connects to the host daemon through `host.openshell.internal:8000`. - First backend surface: `GET /health` for daemon reachability and `POST /moves/smoke` for a small head/antenna motion. +- Default SDK media mode: `no_media`, so the motion-only smoke path does not require camera, audio, or WebRTC access. ## Local Simulator Quickstart -On Linux, install the Reachy Mini GStreamer prerequisites before installing the SDK. The upstream guide lists the full package set and notes that Ubuntu 22.04 needs newer GStreamer packages. +Prerequisites: + +- `uv` +- Python 3.10-3.12. Python 3.12 is recommended by the Reachy Mini docs and used below. +- On Linux, install the Reachy Mini GStreamer prerequisites before installing the SDK. The upstream guide lists the full package set and notes that Ubuntu 22.04 needs newer GStreamer packages. ```bash cd projects/reachy-mini-openshell @@ -67,6 +72,7 @@ openshell sandbox create \ --env REACHY_HOST=host.openshell.internal \ --env REACHY_PORT=8000 \ --env REACHY_CONNECTION_MODE=network \ + --env REACHY_MEDIA_BACKEND=no_media \ -- python3 -m reachy_openshell.backend --host 0.0.0.0 --port 8080 ``` diff --git a/projects/reachy-mini-openshell/openshell/policy.local-sim.yaml b/projects/reachy-mini-openshell/openshell/policy.local-sim.yaml index ebff2820..2eb80b63 100644 --- a/projects/reachy-mini-openshell/openshell/policy.local-sim.yaml +++ b/projects/reachy-mini-openshell/openshell/policy.local-sim.yaml @@ -12,7 +12,6 @@ filesystem_policy: - /opt read_write: - /sandbox - - /workspace - /tmp landlock: @@ -32,5 +31,3 @@ network_policies: - path: /usr/bin/python* - path: /usr/local/bin/python* - path: /opt/reachy-mini-openshell/bin/python* - - path: /sandbox/**/python* - diff --git a/projects/reachy-mini-openshell/src/reachy_openshell/backend.py b/projects/reachy-mini-openshell/src/reachy_openshell/backend.py index 39f8c5fc..47824f82 100644 --- a/projects/reachy-mini-openshell/src/reachy_openshell/backend.py +++ b/projects/reachy-mini-openshell/src/reachy_openshell/backend.py @@ -25,6 +25,7 @@ class Settings: reachy_host: str reachy_port: int connection_mode: str + media_backend: str timeout: float @classmethod @@ -34,6 +35,7 @@ def from_env(cls) -> "Settings": reachy_host=host, reachy_port=_env_int("REACHY_PORT", 8000), connection_mode=os.getenv("REACHY_CONNECTION_MODE", _default_connection_mode(host)), + media_backend=os.getenv("REACHY_MEDIA_BACKEND", "no_media"), timeout=_env_float("REACHY_TIMEOUT", 5.0), ) @@ -91,7 +93,7 @@ def run_smoke_motion(settings: Settings) -> dict[str, Any]: from reachy_mini.utils import create_head_pose except ImportError as exc: raise RuntimeError( - "Reachy Mini SDK is not installed. Install with `uv pip install -e .` " + "Reachy Mini SDK is not installed. Install with `uv pip install -e '.[sdk]'` " "or include the `sim` extra for local simulator work." ) from exc @@ -100,6 +102,7 @@ def run_smoke_motion(settings: Settings) -> dict[str, Any]: port=settings.reachy_port, connection_mode=settings.connection_mode, spawn_daemon=False, + media_backend=settings.media_backend, timeout=settings.timeout, ) as mini: mini.goto_target( @@ -169,6 +172,7 @@ def main(argv: list[str] | None = None) -> int: parser.add_argument("--reachy-host", default=None) parser.add_argument("--reachy-port", type=int, default=None) parser.add_argument("--connection-mode", default=None) + parser.add_argument("--media-backend", default=None) parser.add_argument("--log-level", default=os.getenv("UVICORN_LOG_LEVEL", "info")) args = parser.parse_args(argv) @@ -178,6 +182,8 @@ def main(argv: list[str] | None = None) -> int: os.environ["REACHY_PORT"] = str(args.reachy_port) if args.connection_mode is not None: os.environ["REACHY_CONNECTION_MODE"] = args.connection_mode + if args.media_backend is not None: + os.environ["REACHY_MEDIA_BACKEND"] = args.media_backend import uvicorn @@ -187,4 +193,3 @@ def main(argv: list[str] | None = None) -> int: if __name__ == "__main__": raise SystemExit(main()) - diff --git a/projects/reachy-mini-openshell/src/reachy_openshell/smoke.py b/projects/reachy-mini-openshell/src/reachy_openshell/smoke.py index f86a7ac2..b49d6e59 100644 --- a/projects/reachy-mini-openshell/src/reachy_openshell/smoke.py +++ b/projects/reachy-mini-openshell/src/reachy_openshell/smoke.py @@ -13,6 +13,7 @@ class ReachyTarget: host: str port: int connection_mode: str + media_backend: str timeout: float @@ -50,6 +51,7 @@ def build_parser() -> argparse.ArgumentParser: choices=["auto", "localhost_only", "network"], default=os.getenv("REACHY_CONNECTION_MODE", _default_connection_mode(default_host)), ) + parser.add_argument("--media-backend", default=os.getenv("REACHY_MEDIA_BACKEND", "no_media")) parser.add_argument("--timeout", type=float, default=_env_float("REACHY_TIMEOUT", 5.0)) return parser @@ -60,7 +62,7 @@ def run_motion(target: ReachyTarget) -> None: from reachy_mini.utils import create_head_pose except ImportError as exc: raise RuntimeError( - "Reachy Mini SDK is not installed. Install with `uv pip install -e .` " + "Reachy Mini SDK is not installed. Install with `uv pip install -e '.[sdk]'` " "or `uv pip install -e '.[sim]'` for simulator work." ) from exc @@ -69,6 +71,7 @@ def run_motion(target: ReachyTarget) -> None: port=target.port, connection_mode=target.connection_mode, spawn_daemon=False, + media_backend=target.media_backend, timeout=target.timeout, ) as mini: print(f"Connected to Reachy Mini daemon at {target.host}:{target.port}") @@ -93,6 +96,7 @@ def main(argv: list[str] | None = None) -> int: host=args.host, port=args.port, connection_mode=args.connection_mode, + media_backend=args.media_backend, timeout=args.timeout, ) try: @@ -105,4 +109,3 @@ def main(argv: list[str] | None = None) -> int: if __name__ == "__main__": raise SystemExit(main()) - diff --git a/projects/reachy-mini-openshell/tests/test_reachy_constructors.py b/projects/reachy-mini-openshell/tests/test_reachy_constructors.py new file mode 100644 index 00000000..8aa5005a --- /dev/null +++ b/projects/reachy-mini-openshell/tests/test_reachy_constructors.py @@ -0,0 +1,85 @@ +from __future__ import annotations + +import sys +import types +import unittest +from contextlib import contextmanager, redirect_stdout +from io import StringIO + +from reachy_openshell import backend, smoke + + +class FakeReachyMini: + calls: list[dict[str, object]] = [] + + def __init__(self, **kwargs: object) -> None: + self.calls.append(kwargs) + + def __enter__(self) -> "FakeReachyMini": + return self + + def __exit__(self, *_args: object) -> None: + return None + + def goto_target(self, **_kwargs: object) -> None: + return None + + +@contextmanager +def fake_reachy_modules(): + original = { + name: sys.modules.get(name) + for name in ("reachy_mini", "reachy_mini.utils") + } + + reachy_module = types.ModuleType("reachy_mini") + reachy_module.ReachyMini = FakeReachyMini + utils_module = types.ModuleType("reachy_mini.utils") + utils_module.create_head_pose = lambda **kwargs: {"head_pose": kwargs} + + sys.modules["reachy_mini"] = reachy_module + sys.modules["reachy_mini.utils"] = utils_module + FakeReachyMini.calls = [] + + try: + yield + finally: + for name, module in original.items(): + if module is None: + sys.modules.pop(name, None) + else: + sys.modules[name] = module + + +class ReachyConstructorTests(unittest.TestCase): + def test_backend_smoke_motion_disables_media_by_default(self) -> None: + settings = backend.Settings( + reachy_host="host.openshell.internal", + reachy_port=8000, + connection_mode="network", + media_backend="no_media", + timeout=5.0, + ) + + with fake_reachy_modules(): + backend.run_smoke_motion(settings) + + self.assertEqual(FakeReachyMini.calls[0]["media_backend"], "no_media") + + def test_smoke_cli_disables_media_by_default(self) -> None: + target = smoke.ReachyTarget( + host="localhost", + port=8000, + connection_mode="localhost_only", + media_backend="no_media", + timeout=5.0, + ) + + with fake_reachy_modules(), redirect_stdout(StringIO()): + smoke.run_motion(target) + + self.assertEqual(FakeReachyMini.calls[0]["media_backend"], "no_media") + + +if __name__ == "__main__": + unittest.main() From 8f6c1b8932b4bf1cf4ef8851df344eafe0b8a18c Mon Sep 17 00:00:00 2001 From: Johnny Greco Date: Wed, 24 Jun 2026 17:50:49 +0000 Subject: [PATCH 03/45] Tighten Reachy runtime defaults --- projects/README.md | 1 - projects/reachy-mini-openshell/.dockerignore | 1 - projects/reachy-mini-openshell/.gitignore | 1 - projects/reachy-mini-openshell/Dockerfile | 2 +- projects/reachy-mini-openshell/README.md | 2 +- .../docs/research-plan.md | 1 - .../src/reachy_openshell/__init__.py | 1 - .../src/reachy_openshell/backend.py | 2 +- .../src/reachy_openshell/smoke.py | 20 +++++++------ .../tests/test_reachy_constructors.py | 28 +++++++++---------- 10 files changed, 29 insertions(+), 30 deletions(-) diff --git a/projects/README.md b/projects/README.md index 08fc37c2..998778ed 100644 --- a/projects/README.md +++ b/projects/README.md @@ -5,4 +5,3 @@ This directory contains self-contained research projects. Each project should li Current projects: - `reachy-mini-openshell`: Reachy Mini simulator/backend research for running the backend inside an OpenShell runtime. - diff --git a/projects/reachy-mini-openshell/.dockerignore b/projects/reachy-mini-openshell/.dockerignore index 75e643c1..d6db44c1 100644 --- a/projects/reachy-mini-openshell/.dockerignore +++ b/projects/reachy-mini-openshell/.dockerignore @@ -7,4 +7,3 @@ __pycache__ .ruff_cache dist *.egg-info - diff --git a/projects/reachy-mini-openshell/.gitignore b/projects/reachy-mini-openshell/.gitignore index 9c30bb62..34e42671 100644 --- a/projects/reachy-mini-openshell/.gitignore +++ b/projects/reachy-mini-openshell/.gitignore @@ -5,4 +5,3 @@ __pycache__/ .ruff_cache/ dist/ *.egg-info/ - diff --git a/projects/reachy-mini-openshell/Dockerfile b/projects/reachy-mini-openshell/Dockerfile index 1a83bbcb..b7be69a1 100644 --- a/projects/reachy-mini-openshell/Dockerfile +++ b/projects/reachy-mini-openshell/Dockerfile @@ -37,4 +37,4 @@ RUN chown -R sandbox:sandbox /sandbox/reachy-mini-openshell /opt/reachy-mini-ope USER sandbox -CMD ["python3", "-m", "reachy_openshell.backend", "--host", "0.0.0.0", "--port", "8080"] +CMD ["python3", "-m", "reachy_openshell.backend", "--host", "127.0.0.1", "--port", "8080"] diff --git a/projects/reachy-mini-openshell/README.md b/projects/reachy-mini-openshell/README.md index d29ca663..9dfae05f 100644 --- a/projects/reachy-mini-openshell/README.md +++ b/projects/reachy-mini-openshell/README.md @@ -73,7 +73,7 @@ openshell sandbox create \ --env REACHY_PORT=8000 \ --env REACHY_CONNECTION_MODE=network \ --env REACHY_MEDIA_BACKEND=no_media \ - -- python3 -m reachy_openshell.backend --host 0.0.0.0 --port 8080 + -- python3 -m reachy_openshell.backend --host 127.0.0.1 --port 8080 ``` Expose the backend service: diff --git a/projects/reachy-mini-openshell/docs/research-plan.md b/projects/reachy-mini-openshell/docs/research-plan.md index adce629f..6e06d210 100644 --- a/projects/reachy-mini-openshell/docs/research-plan.md +++ b/projects/reachy-mini-openshell/docs/research-plan.md @@ -28,4 +28,3 @@ Keep the simulator on the host for the first spike so MuJoCo can open its viewer - Should the simulator stay host-side for development, or should a headless simulator move into its own OpenShell sandbox later? - Which daemon bind flags are stable across Reachy Mini SDK versions and operating systems? - Do audio and camera paths need to be disabled or mocked for OpenShell-based backend tests? - diff --git a/projects/reachy-mini-openshell/src/reachy_openshell/__init__.py b/projects/reachy-mini-openshell/src/reachy_openshell/__init__.py index f38884b6..3dc1f76b 100644 --- a/projects/reachy-mini-openshell/src/reachy_openshell/__init__.py +++ b/projects/reachy-mini-openshell/src/reachy_openshell/__init__.py @@ -1,2 +1 @@ __version__ = "0.1.0" - diff --git a/projects/reachy-mini-openshell/src/reachy_openshell/backend.py b/projects/reachy-mini-openshell/src/reachy_openshell/backend.py index 47824f82..c9f97acf 100644 --- a/projects/reachy-mini-openshell/src/reachy_openshell/backend.py +++ b/projects/reachy-mini-openshell/src/reachy_openshell/backend.py @@ -167,7 +167,7 @@ def main(argv: list[str] | None = None) -> int: return 2 parser = argparse.ArgumentParser(description="Run the Reachy Mini OpenShell backend.") - parser.add_argument("--host", default=os.getenv("BACKEND_HOST", "0.0.0.0")) + parser.add_argument("--host", default=os.getenv("BACKEND_HOST", "127.0.0.1")) parser.add_argument("--port", type=int, default=_env_int("BACKEND_PORT", 8080)) parser.add_argument("--reachy-host", default=None) parser.add_argument("--reachy-port", type=int, default=None) diff --git a/projects/reachy-mini-openshell/src/reachy_openshell/smoke.py b/projects/reachy-mini-openshell/src/reachy_openshell/smoke.py index b49d6e59..5933427c 100644 --- a/projects/reachy-mini-openshell/src/reachy_openshell/smoke.py +++ b/projects/reachy-mini-openshell/src/reachy_openshell/smoke.py @@ -49,13 +49,23 @@ def build_parser() -> argparse.ArgumentParser: parser.add_argument( "--connection-mode", choices=["auto", "localhost_only", "network"], - default=os.getenv("REACHY_CONNECTION_MODE", _default_connection_mode(default_host)), + default=os.getenv("REACHY_CONNECTION_MODE"), ) parser.add_argument("--media-backend", default=os.getenv("REACHY_MEDIA_BACKEND", "no_media")) parser.add_argument("--timeout", type=float, default=_env_float("REACHY_TIMEOUT", 5.0)) return parser +def target_from_args(args: argparse.Namespace) -> ReachyTarget: + return ReachyTarget( + host=args.host, + port=args.port, + connection_mode=args.connection_mode or _default_connection_mode(args.host), + media_backend=args.media_backend, + timeout=args.timeout, + ) + + def run_motion(target: ReachyTarget) -> None: try: from reachy_mini import ReachyMini @@ -92,13 +102,7 @@ def run_motion(target: ReachyTarget) -> None: def main(argv: list[str] | None = None) -> int: args = build_parser().parse_args(argv) - target = ReachyTarget( - host=args.host, - port=args.port, - connection_mode=args.connection_mode, - media_backend=args.media_backend, - timeout=args.timeout, - ) + target = target_from_args(args) try: run_motion(target) except Exception as exc: diff --git a/projects/reachy-mini-openshell/tests/test_reachy_constructors.py b/projects/reachy-mini-openshell/tests/test_reachy_constructors.py index 8aa5005a..59547309 100644 --- a/projects/reachy-mini-openshell/tests/test_reachy_constructors.py +++ b/projects/reachy-mini-openshell/tests/test_reachy_constructors.py @@ -1,10 +1,12 @@ from __future__ import annotations +import os import sys import types import unittest from contextlib import contextmanager, redirect_stdout from io import StringIO +from unittest.mock import patch from reachy_openshell import backend, smoke @@ -53,13 +55,8 @@ def fake_reachy_modules(): class ReachyConstructorTests(unittest.TestCase): def test_backend_smoke_motion_disables_media_by_default(self) -> None: - settings = backend.Settings( - reachy_host="host.openshell.internal", - reachy_port=8000, - connection_mode="network", - media_backend="no_media", - timeout=5.0, - ) + with patch.dict(os.environ, {}, clear=True): + settings = backend.Settings.from_env() with fake_reachy_modules(): backend.run_smoke_motion(settings) @@ -67,19 +64,22 @@ def test_backend_smoke_motion_disables_media_by_default(self) -> None: self.assertEqual(FakeReachyMini.calls[0]["media_backend"], "no_media") def test_smoke_cli_disables_media_by_default(self) -> None: - target = smoke.ReachyTarget( - host="localhost", - port=8000, - connection_mode="localhost_only", - media_backend="no_media", - timeout=5.0, - ) + with patch.dict(os.environ, {}, clear=True): + target = smoke.target_from_args(smoke.build_parser().parse_args([])) with fake_reachy_modules(), redirect_stdout(StringIO()): smoke.run_motion(target) self.assertEqual(FakeReachyMini.calls[0]["media_backend"], "no_media") + def test_smoke_cli_uses_network_mode_for_non_local_cli_host(self) -> None: + with patch.dict(os.environ, {}, clear=True): + target = smoke.target_from_args( + smoke.build_parser().parse_args(["--host", "host.openshell.internal"]) + ) + + self.assertEqual(target.connection_mode, "network") + if __name__ == "__main__": unittest.main() From a77be29befb8f5378c95b8e270c4aa80c5dd8055 Mon Sep 17 00:00:00 2001 From: Johnny Greco Date: Wed, 24 Jun 2026 17:14:57 -0400 Subject: [PATCH 04/45] Refactor Reachy OpenShell around conversation app --- projects/reachy-mini-openshell/.dockerignore | 9 - projects/reachy-mini-openshell/.env.example | 8 + projects/reachy-mini-openshell/.gitignore | 57 +- projects/reachy-mini-openshell/Dockerfile | 40 - projects/reachy-mini-openshell/LICENSE | 201 +++++ projects/reachy-mini-openshell/Makefile | 22 - projects/reachy-mini-openshell/README.md | 110 +-- .../docs/research-plan.md | 30 - projects/reachy-mini-openshell/index.html | 42 + .../openshell/policy.local-sim.yaml | 33 - projects/reachy-mini-openshell/pyproject.toml | 84 +- .../reachy_mini_conversation_app/__init__.py | 1 + .../reachy_mini_conversation_app/__main__.py | 5 + .../audio/__init__.py | 1 + .../audio/head_wobbler.py | 181 ++++ .../audio/speech_tapper.py | 268 ++++++ .../camera_worker.py | 241 +++++ .../reachy_mini_conversation_app/config.py | 73 ++ .../reachy_mini_conversation_app/console.py | 419 +++++++++ .../dance_emotion_moves.py | 86 ++ .../goto_queue_move.py | 68 ++ .../images/reachymini_avatar.png | Bin 0 -> 1228716 bytes .../images/user_avatar.png | Bin 0 -> 1111878 bytes .../src/reachy_mini_conversation_app/main.py | 255 ++++++ .../src/reachy_mini_conversation_app/moves.py | 849 ++++++++++++++++++ .../openai_realtime.py | 811 +++++++++++++++++ .../profiles/__init__.py | 1 + .../__init__.py | 1 + .../instructions.txt | 3 + .../sweep_look.py | 115 +++ .../tools.txt | 5 + .../reachy_mini_conversation_app/prompts.py | 47 + .../static/index.html | 54 ++ .../static/main.js | 136 +++ .../static/style.css | 210 +++++ .../tools/__init__.py | 1 + .../tools/background_tool_manager.py | 412 +++++++++ .../tools/camera.py | 68 ++ .../tools/core_tools.py | 213 +++++ .../tools/dance.py | 86 ++ .../tools/do_nothing.py | 30 + .../tools/head_tracking.py | 31 + .../tools/move_head.py | 79 ++ .../tools/play_emotion.py | 84 ++ .../tools/stop_dance.py | 31 + .../tools/stop_emotion.py | 31 + .../tools/task_cancel.py | 74 ++ .../tools/task_status.py | 104 +++ .../tools/tool_constants.py | 17 + .../src/reachy_mini_conversation_app/utils.py | 123 +++ .../vision/__init__.py | 1 + .../vision/processors.py | 331 +++++++ .../vision/yolo_head_tracker.py | 148 +++ .../src/reachy_openshell/__init__.py | 1 - .../src/reachy_openshell/backend.py | 195 ---- .../src/reachy_openshell/smoke.py | 115 --- projects/reachy-mini-openshell/style.css | 113 +++ .../tests/audio/test_head_wobbler.py | 110 +++ .../reachy-mini-openshell/tests/conftest.py | 15 + .../tests/test_openai_realtime.py | 544 +++++++++++ .../tests/test_reachy_constructors.py | 85 -- .../tools/test_background_tool_manager.py | 545 +++++++++++ .../tests/vision/test_processors.py | 498 ++++++++++ 63 files changed, 7916 insertions(+), 635 deletions(-) delete mode 100644 projects/reachy-mini-openshell/.dockerignore create mode 100644 projects/reachy-mini-openshell/.env.example delete mode 100644 projects/reachy-mini-openshell/Dockerfile create mode 100644 projects/reachy-mini-openshell/LICENSE delete mode 100644 projects/reachy-mini-openshell/Makefile delete mode 100644 projects/reachy-mini-openshell/docs/research-plan.md create mode 100644 projects/reachy-mini-openshell/index.html delete mode 100644 projects/reachy-mini-openshell/openshell/policy.local-sim.yaml create mode 100644 projects/reachy-mini-openshell/src/reachy_mini_conversation_app/__init__.py create mode 100644 projects/reachy-mini-openshell/src/reachy_mini_conversation_app/__main__.py create mode 100644 projects/reachy-mini-openshell/src/reachy_mini_conversation_app/audio/__init__.py create mode 100644 projects/reachy-mini-openshell/src/reachy_mini_conversation_app/audio/head_wobbler.py create mode 100644 projects/reachy-mini-openshell/src/reachy_mini_conversation_app/audio/speech_tapper.py create mode 100644 projects/reachy-mini-openshell/src/reachy_mini_conversation_app/camera_worker.py create mode 100644 projects/reachy-mini-openshell/src/reachy_mini_conversation_app/config.py create mode 100644 projects/reachy-mini-openshell/src/reachy_mini_conversation_app/console.py create mode 100644 projects/reachy-mini-openshell/src/reachy_mini_conversation_app/dance_emotion_moves.py create mode 100644 projects/reachy-mini-openshell/src/reachy_mini_conversation_app/goto_queue_move.py create mode 100644 projects/reachy-mini-openshell/src/reachy_mini_conversation_app/images/reachymini_avatar.png create mode 100644 projects/reachy-mini-openshell/src/reachy_mini_conversation_app/images/user_avatar.png create mode 100644 projects/reachy-mini-openshell/src/reachy_mini_conversation_app/main.py create mode 100644 projects/reachy-mini-openshell/src/reachy_mini_conversation_app/moves.py create mode 100644 projects/reachy-mini-openshell/src/reachy_mini_conversation_app/openai_realtime.py create mode 100644 projects/reachy-mini-openshell/src/reachy_mini_conversation_app/profiles/__init__.py create mode 100644 projects/reachy-mini-openshell/src/reachy_mini_conversation_app/profiles/_reachy_mini_conversation_app_locked_profile/__init__.py create mode 100644 projects/reachy-mini-openshell/src/reachy_mini_conversation_app/profiles/_reachy_mini_conversation_app_locked_profile/instructions.txt create mode 100644 projects/reachy-mini-openshell/src/reachy_mini_conversation_app/profiles/_reachy_mini_conversation_app_locked_profile/sweep_look.py create mode 100644 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projects/reachy-mini-openshell/src/reachy_mini_conversation_app/tools/dance.py create mode 100644 projects/reachy-mini-openshell/src/reachy_mini_conversation_app/tools/do_nothing.py create mode 100644 projects/reachy-mini-openshell/src/reachy_mini_conversation_app/tools/head_tracking.py create mode 100644 projects/reachy-mini-openshell/src/reachy_mini_conversation_app/tools/move_head.py create mode 100644 projects/reachy-mini-openshell/src/reachy_mini_conversation_app/tools/play_emotion.py create mode 100644 projects/reachy-mini-openshell/src/reachy_mini_conversation_app/tools/stop_dance.py create mode 100644 projects/reachy-mini-openshell/src/reachy_mini_conversation_app/tools/stop_emotion.py create mode 100644 projects/reachy-mini-openshell/src/reachy_mini_conversation_app/tools/task_cancel.py create mode 100644 projects/reachy-mini-openshell/src/reachy_mini_conversation_app/tools/task_status.py create mode 100644 projects/reachy-mini-openshell/src/reachy_mini_conversation_app/tools/tool_constants.py create mode 100644 projects/reachy-mini-openshell/src/reachy_mini_conversation_app/utils.py create mode 100644 projects/reachy-mini-openshell/src/reachy_mini_conversation_app/vision/__init__.py create mode 100644 projects/reachy-mini-openshell/src/reachy_mini_conversation_app/vision/processors.py create mode 100644 projects/reachy-mini-openshell/src/reachy_mini_conversation_app/vision/yolo_head_tracker.py delete mode 100644 projects/reachy-mini-openshell/src/reachy_openshell/__init__.py delete mode 100644 projects/reachy-mini-openshell/src/reachy_openshell/backend.py delete mode 100644 projects/reachy-mini-openshell/src/reachy_openshell/smoke.py create mode 100644 projects/reachy-mini-openshell/style.css create mode 100644 projects/reachy-mini-openshell/tests/audio/test_head_wobbler.py create mode 100644 projects/reachy-mini-openshell/tests/conftest.py create mode 100644 projects/reachy-mini-openshell/tests/test_openai_realtime.py delete mode 100644 projects/reachy-mini-openshell/tests/test_reachy_constructors.py create mode 100644 projects/reachy-mini-openshell/tests/tools/test_background_tool_manager.py create mode 100644 projects/reachy-mini-openshell/tests/vision/test_processors.py diff --git a/projects/reachy-mini-openshell/.dockerignore b/projects/reachy-mini-openshell/.dockerignore deleted file mode 100644 index d6db44c1..00000000 --- a/projects/reachy-mini-openshell/.dockerignore +++ /dev/null @@ -1,9 +0,0 @@ -.git -.venv -__pycache__ -*.pyc -*.pyo -.pytest_cache -.ruff_cache -dist -*.egg-info diff --git a/projects/reachy-mini-openshell/.env.example b/projects/reachy-mini-openshell/.env.example new file mode 100644 index 00000000..12cf25b2 --- /dev/null +++ b/projects/reachy-mini-openshell/.env.example @@ -0,0 +1,8 @@ +OPENAI_API_KEY= +MODEL_NAME="gpt-realtime" + +# Used only with --local-vision. +LOCAL_VISION_MODEL=HuggingFaceTB/SmolVLM2-2.2B-Instruct + +HF_HOME=./cache +HF_TOKEN= diff --git a/projects/reachy-mini-openshell/.gitignore b/projects/reachy-mini-openshell/.gitignore index 34e42671..2451acc1 100644 --- a/projects/reachy-mini-openshell/.gitignore +++ b/projects/reachy-mini-openshell/.gitignore @@ -1,7 +1,58 @@ -.venv/ +# Python __pycache__/ *.py[cod] -.pytest_cache/ -.ruff_cache/ +*$py.class +*.so + +# Virtual environments +.venv/ +venv/ +ENV/ +env/ + +# Environment variables +.env + +# Build and distribution +build/ dist/ *.egg-info/ +.eggs/ + +# Testing +.pytest_cache/ +.coverage +.hypothesis/ +htmlcov/ +coverage.xml +*.cover + +# Linting and formatting +.ruff_cache/ +.mypy_cache/ + +# IDE +.vscode/ +.idea/ +*.swp +*.swo + +# Security +*.key +*.pem +*.crt +*.csr + +# Temporary files +tmp/ +*.log +cache/ + +# macOS +.DS_Store + +# Linux +*~ +.directory +.Trash-* +.nfs* diff --git a/projects/reachy-mini-openshell/Dockerfile b/projects/reachy-mini-openshell/Dockerfile deleted file mode 100644 index b7be69a1..00000000 --- a/projects/reachy-mini-openshell/Dockerfile +++ /dev/null @@ -1,40 +0,0 @@ -FROM ghcr.io/nvidia/openshell-community/sandboxes/base:latest - -USER root -WORKDIR /sandbox/reachy-mini-openshell - -RUN apt-get update \ - && apt-get install -y --no-install-recommends \ - build-essential \ - pkg-config \ - python3-dev \ - libcairo2-dev \ - libgirepository1.0-dev \ - libglib2.0-dev \ - libgstreamer-plugins-bad1.0-dev \ - libgstreamer-plugins-base1.0-dev \ - libgstreamer1.0-dev \ - libnice10 \ - libportaudio2 \ - libssl-dev \ - gstreamer1.0-alsa \ - gstreamer1.0-nice \ - gstreamer1.0-plugins-bad \ - gstreamer1.0-plugins-good \ - python3-gi \ - python3-gi-cairo \ - && rm -rf /var/lib/apt/lists/* - -COPY pyproject.toml README.md ./ -COPY src ./src - -RUN python3 -m venv /opt/reachy-mini-openshell -ENV PATH="/opt/reachy-mini-openshell/bin:${PATH}" -ENV PYTHONDONTWRITEBYTECODE=1 - -RUN pip install --no-cache-dir ".[backend,sdk]" -RUN chown -R sandbox:sandbox /sandbox/reachy-mini-openshell /opt/reachy-mini-openshell - -USER sandbox - -CMD ["python3", "-m", "reachy_openshell.backend", "--host", "127.0.0.1", "--port", "8080"] diff --git a/projects/reachy-mini-openshell/LICENSE b/projects/reachy-mini-openshell/LICENSE new file mode 100644 index 00000000..261eeb9e --- /dev/null +++ b/projects/reachy-mini-openshell/LICENSE @@ -0,0 +1,201 @@ + Apache License + Version 2.0, January 2004 + http://www.apache.org/licenses/ + + TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION + + 1. 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We also recommend that a + file or class name and description of purpose be included on the + same "printed page" as the copyright notice for easier + identification within third-party archives. + + Copyright [yyyy] [name of copyright owner] + + Licensed under the Apache License, Version 2.0 (the "License"); + you may not use this file except in compliance with the License. + You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + + Unless required by applicable law or agreed to in writing, software + distributed under the License is distributed on an "AS IS" BASIS, + WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + See the License for the specific language governing permissions and + limitations under the License. diff --git a/projects/reachy-mini-openshell/Makefile b/projects/reachy-mini-openshell/Makefile deleted file mode 100644 index ce34839a..00000000 --- a/projects/reachy-mini-openshell/Makefile +++ /dev/null @@ -1,22 +0,0 @@ -UV ?= uv -PYTHON ?= python3 - -.PHONY: install install-backend install-sim sim smoke backend - -install: - $(UV) pip install -e ".[backend,sdk]" - -install-backend: - $(UV) pip install -e ".[backend]" - -install-sim: - $(UV) pip install -e ".[backend,sim]" - -sim: - reachy-mini-daemon --sim --scene $${REACHY_SCENE:-minimal} - -smoke: - $(PYTHON) -m reachy_openshell.smoke - -backend: - $(PYTHON) -m reachy_openshell.backend diff --git a/projects/reachy-mini-openshell/README.md b/projects/reachy-mini-openshell/README.md index 9dfae05f..de3e35db 100644 --- a/projects/reachy-mini-openshell/README.md +++ b/projects/reachy-mini-openshell/README.md @@ -1,101 +1,53 @@ -# Reachy Mini OpenShell Research +--- +title: Reachy OpenShell +emoji: 🤖 +colorFrom: purple +colorTo: gray +sdk: static +pinned: false +tags: + - reachy_mini + - reachy_mini_python_app +--- -Minimal research scaffold for running a Reachy Mini backend inside an OpenShell sandbox while starting against the Reachy Mini MuJoCo simulator. +# Reachy OpenShell -## Current Shape +Reachy OpenShell is a locked-profile fork of the Reachy Mini conversation app +for OpenShell research. -- Host process: runs `reachy-mini-daemon --sim`, which starts the simulator and exposes the daemon API on port `8000`. -- OpenShell process: runs this backend in a sandbox and connects to the host daemon through `host.openshell.internal:8000`. -- First backend surface: `GET /health` for daemon reachability and `POST /moves/smoke` for a small head/antenna motion. -- Default SDK media mode: `no_media`, so the motion-only smoke path does not require camera, audio, or WebRTC access. +## Customize -## Local Simulator Quickstart +The app is locked to: -Prerequisites: - -- `uv` -- Python 3.10-3.12. Python 3.12 is recommended by the Reachy Mini docs and used below. -- On Linux, install the Reachy Mini GStreamer prerequisites before installing the SDK. The upstream guide lists the full package set and notes that Ubuntu 22.04 needs newer GStreamer packages. - -```bash -cd projects/reachy-mini-openshell -uv venv --python 3.12 -source .venv/bin/activate -uv pip install -e ".[backend,sim]" -``` - -Start the simulator: - -```bash -reachy-mini-daemon --sim --scene minimal -``` - -In another terminal: - -```bash -source .venv/bin/activate -python -m reachy_openshell.smoke -python -m reachy_openshell.backend +```text +src/reachy_mini_conversation_app/profiles/_reachy_mini_conversation_app_locked_profile ``` -Then probe the backend: +That folder is the customization surface: -```bash -curl http://127.0.0.1:8080/health -curl -X POST http://127.0.0.1:8080/moves/smoke -``` - -On macOS, the Reachy docs recommend launching the simulator with `mjpython` instead: - -```bash -mjpython -m reachy_mini.daemon.app.main --sim -``` +- `instructions.txt`: system prompt for the assistant +- `tools.txt`: explicit tool allow-list +- Python files in that folder: profile-local tools -## OpenShell Sandbox Path +## Run Locally -For the sandboxed backend to reach a host-level simulator, bind the Reachy daemon to an interface visible from containers: +Start the Reachy Mini daemon first. For the simulator baseline: ```bash -reachy-mini-daemon --sim --scene minimal --fastapi-host 0.0.0.0 --fastapi-port 8000 +reachy-mini-daemon --sim --scene minimal --headless --no-media --fastapi-host 127.0.0.1 --fastapi-port 8000 --dataset-update-interval 0 ``` -If your installed daemon exposes different flag names, check `reachy-mini-daemon --help`; the important part is that the daemon is reachable from the sandbox at `host.openshell.internal:8000`. - -Build and run the backend in OpenShell: +Then run the conversation app: ```bash -openshell status -openshell sandbox create \ - --name reachy-mini-backend \ - --from . \ - --policy openshell/policy.local-sim.yaml \ - --env REACHY_HOST=host.openshell.internal \ - --env REACHY_PORT=8000 \ - --env REACHY_CONNECTION_MODE=network \ - --env REACHY_MEDIA_BACKEND=no_media \ - -- python3 -m reachy_openshell.backend --host 127.0.0.1 --port 8080 +python -m reachy_mini_conversation_app --gradio --no-camera ``` -Expose the backend service: +The app also installs a console script: ```bash -openshell service expose reachy-mini-backend 8080 +reachy-mini-conversation-app --gradio --no-camera ``` -The sandbox image installs the Linux system packages needed by the Reachy SDK before installing the Python package. - -## Layout - -- `src/reachy_openshell/smoke.py`: SDK smoke motion for the simulator or a real robot daemon. -- `src/reachy_openshell/backend.py`: small FastAPI backend for health checks and the smoke motion. -- `openshell/policy.local-sim.yaml`: starter OpenShell policy allowing Python to reach the host simulator daemon. -- `Dockerfile`: OpenShell sandbox image for the backend, based on the OpenShell community base sandbox. - -## References - -- Reachy Mini simulator setup: https://huggingface.co/docs/reachy_mini/en/platforms/simulation/get_started -- Reachy Mini Linux GStreamer prerequisites: https://huggingface.co/docs/reachy_mini/en/SDK/gstreamer-installation -- Reachy Mini SDK API: https://huggingface.co/docs/reachy_mini/en/API/reachymini -- OpenShell overview: https://docs.nvidia.com/openshell/about/overview -- OpenShell sandbox management: https://docs.nvidia.com/openshell/sandboxes/manage-sandboxes -- OpenShell policy reference: https://docs.nvidia.com/openshell/reference/policy-schema +Simulation mode auto-enables Gradio; `--gradio` is included here so the expected +browser interface is explicit. diff --git a/projects/reachy-mini-openshell/docs/research-plan.md b/projects/reachy-mini-openshell/docs/research-plan.md deleted file mode 100644 index 6e06d210..00000000 --- a/projects/reachy-mini-openshell/docs/research-plan.md +++ /dev/null @@ -1,30 +0,0 @@ -# Research Plan - -## Working Hypothesis - -Keep the simulator on the host for the first spike so MuJoCo can open its viewer normally. Run only the backend in OpenShell. The sandbox reaches the host daemon through `host.openshell.internal:8000`, using a narrow OpenShell network policy. - -## Phase 0: Simulator Bootstrap - -- Install `reachy-mini[mujoco]` locally. -- Start `reachy-mini-daemon --sim --scene minimal`. -- Verify the Python SDK can connect and run the smoke motion. - -## Phase 1: Sandboxed Backend - -- Build the local OpenShell sandbox image from `Dockerfile`. -- Run `python3 -m reachy_openshell.backend` inside the sandbox. -- Confirm `GET /health` reaches the simulator daemon. -- Confirm `POST /moves/smoke` moves the simulated robot. - -## Phase 2: Policy Tightening - -- Capture the exact daemon traffic used by the SDK. -- Replace the current L4 passthrough policy with REST and WebSocket rules if the daemon API remains stable enough. -- Decide whether PyPI access is needed at runtime or only at image build time. - -## Open Questions - -- Should the simulator stay host-side for development, or should a headless simulator move into its own OpenShell sandbox later? -- Which daemon bind flags are stable across Reachy Mini SDK versions and operating systems? -- Do audio and camera paths need to be disabled or mocked for OpenShell-based backend tests? diff --git a/projects/reachy-mini-openshell/index.html b/projects/reachy-mini-openshell/index.html new file mode 100644 index 00000000..d241f1fc --- /dev/null +++ b/projects/reachy-mini-openshell/index.html @@ -0,0 +1,42 @@ + + + + + + Reachy OpenShell + + + +
+
+
+
Reachy Mini App
+

Reachy OpenShell

+

A conversation app for Reachy Mini robot.

+
+ +
+
+
+

Getting Started

+

Installation

+
+
+

Install this app on your Reachy Mini using the app store, or run it locally:

+ 
uv sync
+reachy-mini-daemon --sim --scene minimal --headless --no-media
+python -m reachy_mini_conversation_app --gradio --no-camera
+
+ +
+
+
+

Configuration

+

OpenAI API Key

+
+
+

This app requires an OpenAI API key for voice conversations. Set it via the web interface or environment variable.

+
+
+ + diff --git a/projects/reachy-mini-openshell/openshell/policy.local-sim.yaml b/projects/reachy-mini-openshell/openshell/policy.local-sim.yaml deleted file mode 100644 index 2eb80b63..00000000 --- a/projects/reachy-mini-openshell/openshell/policy.local-sim.yaml +++ /dev/null @@ -1,33 +0,0 @@ -version: 1 - -filesystem_policy: - include_workdir: true - read_only: - - /usr - - /lib - - /lib64 - - /etc - - /bin - - /sbin - - /opt - read_write: - - /sandbox - - /tmp - -landlock: - compatibility: best_effort - -process: - run_as_user: sandbox - run_as_group: sandbox - -network_policies: - reachy_daemon: - name: reachy-daemon-local-simulator - endpoints: - - host: host.openshell.internal - port: 8000 - binaries: - - path: /usr/bin/python* - - path: /usr/local/bin/python* - - path: /opt/reachy-mini-openshell/bin/python* diff --git a/projects/reachy-mini-openshell/pyproject.toml b/projects/reachy-mini-openshell/pyproject.toml index 07029d0c..6ddc6313 100644 --- a/projects/reachy-mini-openshell/pyproject.toml +++ b/projects/reachy-mini-openshell/pyproject.toml @@ -1,33 +1,71 @@ [build-system] -requires = ["hatchling>=1.25"] -build-backend = "hatchling.build" +requires = [ "setuptools",] +build-backend = "setuptools.build_meta" [project] -name = "reachy-mini-openshell" -version = "0.1.0" -description = "Research scaffold for running a Reachy Mini backend in OpenShell against a Reachy Mini simulator." +name = "reachy_mini_conversation_app" +version = "0.3.0" +description = "OpenShell-oriented fork of the Reachy Mini conversation app." readme = "README.md" requires-python = ">=3.10" -dependencies = [] +dependencies = [ "aiortc>=1.13.0", "fastrtc>=0.0.34", "gradio==5.50.1.dev1", "huggingface-hub==1.3.0", "opencv-python>=4.12.0.88", "python-dotenv", "openai>=2.1", "reachy_mini_dances_library", "reachy_mini_toolbox", "reachy-mini>=1.5.0", "eclipse-zenoh~=1.7.0", "gradio_client>=1.13.3",] +[[project.authors]] +name = "Pollen Robotics" +email = "contact@pollen-robotics.com" + +[dependency-groups] +dev = [ "pytest", "pytest-asyncio", "ruff==0.12.0", "mypy==1.18.2", "pre-commit", "types-requests", "python-semantic-release>=10.5.3",] [project.optional-dependencies] -backend = [ - "fastapi>=0.115,<1", - "uvicorn[standard]>=0.30,<1", -] -sdk = [ - "reachy-mini>=1.8.3,<2", -] -sim = [ - "reachy-mini[mujoco]>=1.8.3,<2", -] -dev = [ - "ruff>=0.8,<1", -] +local_vision = [ "torch>=2.1", "transformers==5.0.0rc2", "num2words",] +yolo_vision = [ "ultralytics", "supervision",] +mediapipe_vision = [ "mediapipe==0.10.14",] +all_vision = [ "torch>=2.1", "transformers==5.0.0rc2", "num2words", "ultralytics", "supervision", "mediapipe==0.10.14",] [project.scripts] -reachy-backend = "reachy_openshell.backend:main" -reachy-smoke = "reachy_openshell.smoke:main" +reachy-mini-conversation-app = "reachy_mini_conversation_app.main:main" + +[tool.setuptools] +include-package-data = true + +[tool.ruff] +line-length = 119 +exclude = [ ".venv", "dist", "build", "**/__pycache__", "*.egg-info", ".mypy_cache", ".pytest_cache",] + +[tool.mypy] +python_version = "3.12" +files = [ "src/",] +ignore_missing_imports = true +strict = true +show_error_codes = true +warn_unused_ignores = true + +[project.entry-points.reachy_mini_apps] +reachy_mini_conversation_app = "reachy_mini_conversation_app.main:ReachyMiniConversationApp" + +[tool.setuptools.package-dir] +"" = "src" + +[tool.setuptools.package-data] +reachy_mini_conversation_app = [ "images/*", "static/*", "profiles/**/*.py", "profiles/**/*.txt",] + +[tool.ruff.lint] +select = [ "E", "F", "W", "I", "C4", "D",] +ignore = [ "E501", "D100", "D203", "D213",] + +[tool.ruff.format] +quote-style = "double" +indent-style = "space" +skip-magic-trailing-comma = false +line-ending = "auto" + +[tool.setuptools.packages.find] +where = [ "src",] -[tool.hatch.build.targets.wheel] -packages = ["src/reachy_openshell"] +[tool.ruff.lint.isort] +length-sort = true +lines-after-imports = 2 +no-lines-before = [ "standard-library", "local-folder",] +known-local-folder = [ "reachy_mini_conversation_app",] +known-first-party = [ "reachy_mini", "reachy_mini_dances_library", "reachy_mini_toolbox",] +split-on-trailing-comma = true diff --git a/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/__init__.py b/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/__init__.py new file mode 100644 index 00000000..60dc15c4 --- /dev/null +++ b/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/__init__.py @@ -0,0 +1 @@ +"""Nothing (for ruff).""" diff --git a/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/__main__.py b/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/__main__.py new file mode 100644 index 00000000..e5091e7b --- /dev/null +++ b/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/__main__.py @@ -0,0 +1,5 @@ +from reachy_mini_conversation_app.main import main + + +if __name__ == "__main__": + main() diff --git a/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/audio/__init__.py b/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/audio/__init__.py new file mode 100644 index 00000000..60dc15c4 --- /dev/null +++ b/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/audio/__init__.py @@ -0,0 +1 @@ +"""Nothing (for ruff).""" diff --git a/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/audio/head_wobbler.py b/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/audio/head_wobbler.py new file mode 100644 index 00000000..805d1cdb --- /dev/null +++ b/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/audio/head_wobbler.py @@ -0,0 +1,181 @@ +"""Moves head given audio samples.""" + +import time +import queue +import base64 +import logging +import threading +from typing import Tuple +from collections.abc import Callable + +import numpy as np +from numpy.typing import NDArray + +from reachy_mini_conversation_app.audio.speech_tapper import HOP_MS, SwayRollRT + + +SAMPLE_RATE = 24000 +MOVEMENT_LATENCY_S = 0.2 # seconds between audio and robot movement +logger = logging.getLogger(__name__) + + +class HeadWobbler: + """Converts audio deltas (base64) into head movement offsets.""" + + def __init__(self, set_speech_offsets: Callable[[Tuple[float, float, float, float, float, float]], None]) -> None: + """Initialize the head wobbler.""" + self._apply_offsets = set_speech_offsets + self._base_ts: float | None = None + self._hops_done: int = 0 + + self.audio_queue: "queue.Queue[Tuple[int, int, NDArray[np.int16]]]" = queue.Queue() + self.sway = SwayRollRT() + + # Synchronization primitives + self._state_lock = threading.Lock() + self._sway_lock = threading.Lock() + self._generation = 0 + + self._stop_event = threading.Event() + self._thread: threading.Thread | None = None + + def feed(self, delta_b64: str) -> None: + """Thread-safe: push audio into the consumer queue.""" + buf = np.frombuffer(base64.b64decode(delta_b64), dtype=np.int16).reshape(1, -1) + with self._state_lock: + generation = self._generation + self.audio_queue.put((generation, SAMPLE_RATE, buf)) + + def start(self) -> None: + """Start the head wobbler loop in a thread.""" + self._stop_event.clear() + self._thread = threading.Thread(target=self.working_loop, daemon=True) + self._thread.start() + logger.debug("Head wobbler started") + + def stop(self) -> None: + """Stop the head wobbler loop.""" + self._stop_event.set() + if self._thread is not None: + self._thread.join() + logger.debug("Head wobbler stopped") + + def working_loop(self) -> None: + """Convert audio deltas into head movement offsets.""" + hop_dt = HOP_MS / 1000.0 + + logger.debug("Head wobbler thread started") + while not self._stop_event.is_set(): + queue_ref = self.audio_queue + try: + chunk_generation, sr, chunk = queue_ref.get_nowait() # (gen, sr, data) + except queue.Empty: + # avoid while to never exit + time.sleep(MOVEMENT_LATENCY_S) + continue + + try: + with self._state_lock: + current_generation = self._generation + if chunk_generation != current_generation: + continue + + if self._base_ts is None: + with self._state_lock: + if self._base_ts is None: + self._base_ts = time.monotonic() + + pcm = np.asarray(chunk).squeeze(0) + with self._sway_lock: + results = self.sway.feed(pcm, sr) + + i = 0 + while i < len(results): + with self._state_lock: + if self._generation != current_generation: + break + base_ts = self._base_ts + hops_done = self._hops_done + + if base_ts is None: + base_ts = time.monotonic() + with self._state_lock: + if self._base_ts is None: + self._base_ts = base_ts + hops_done = self._hops_done + + target = base_ts + MOVEMENT_LATENCY_S + hops_done * hop_dt + now = time.monotonic() + + if now - target >= hop_dt: + lag_hops = int((now - target) / hop_dt) + drop = min(lag_hops, len(results) - i - 1) + if drop > 0: + with self._state_lock: + self._hops_done += drop + hops_done = self._hops_done + i += drop + continue + + if target > now: + time.sleep(target - now) + with self._state_lock: + if self._generation != current_generation: + break + + r = results[i] + offsets = ( + r["x_mm"] / 1000.0, + r["y_mm"] / 1000.0, + r["z_mm"] / 1000.0, + r["roll_rad"], + r["pitch_rad"], + r["yaw_rad"], + ) + + with self._state_lock: + if self._generation != current_generation: + break + + self._apply_offsets(offsets) + + with self._state_lock: + self._hops_done += 1 + i += 1 + finally: + queue_ref.task_done() + logger.debug("Head wobbler thread exited") + + ''' + def drain_audio_queue(self) -> None: + """Empty the audio queue.""" + try: + while True: + self.audio_queue.get_nowait() + except QueueEmpty: + pass + ''' + + def reset(self) -> None: + """Reset the internal state.""" + with self._state_lock: + self._generation += 1 + self._base_ts = None + self._hops_done = 0 + + # Drain any queued audio chunks from previous generations + drained_any = False + while True: + try: + _, _, _ = self.audio_queue.get_nowait() + except queue.Empty: + break + else: + drained_any = True + self.audio_queue.task_done() + + with self._sway_lock: + self.sway.reset() + + if drained_any: + logger.debug("Head wobbler queue drained during reset") diff --git a/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/audio/speech_tapper.py b/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/audio/speech_tapper.py new file mode 100644 index 00000000..3f4a2f16 --- /dev/null +++ b/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/audio/speech_tapper.py @@ -0,0 +1,268 @@ +from __future__ import annotations +import math +from typing import Any, Dict, List +from itertools import islice +from collections import deque + +import numpy as np +from numpy.typing import NDArray + + +# Tunables +SR = 16_000 +FRAME_MS = 20 +HOP_MS = 50 + +SWAY_MASTER = 1.5 +SENS_DB_OFFSET = +4.0 +VAD_DB_ON = -35.0 +VAD_DB_OFF = -45.0 +VAD_ATTACK_MS = 40 +VAD_RELEASE_MS = 250 +ENV_FOLLOW_GAIN = 0.65 + +SWAY_F_PITCH = 2.2 +SWAY_A_PITCH_DEG = 4.5 +SWAY_F_YAW = 0.6 +SWAY_A_YAW_DEG = 7.5 +SWAY_F_ROLL = 1.3 +SWAY_A_ROLL_DEG = 2.25 +SWAY_F_X = 0.35 +SWAY_A_X_MM = 4.5 +SWAY_F_Y = 0.45 +SWAY_A_Y_MM = 3.75 +SWAY_F_Z = 0.25 +SWAY_A_Z_MM = 2.25 + +SWAY_DB_LOW = -46.0 +SWAY_DB_HIGH = -18.0 +LOUDNESS_GAMMA = 0.9 +SWAY_ATTACK_MS = 50 +SWAY_RELEASE_MS = 250 + +# Derived +FRAME = int(SR * FRAME_MS / 1000) +HOP = int(SR * HOP_MS / 1000) +ATTACK_FR = max(1, int(VAD_ATTACK_MS / HOP_MS)) +RELEASE_FR = max(1, int(VAD_RELEASE_MS / HOP_MS)) +SWAY_ATTACK_FR = max(1, int(SWAY_ATTACK_MS / HOP_MS)) +SWAY_RELEASE_FR = max(1, int(SWAY_RELEASE_MS / HOP_MS)) + + +def _rms_dbfs(x: NDArray[np.float32]) -> float: + """Root-mean-square in dBFS for float32 mono array in [-1,1].""" + # numerically stable rms (avoid overflow) + x = x.astype(np.float32, copy=False) + rms = np.sqrt(np.mean(x * x, dtype=np.float32) + 1e-12, dtype=np.float32) + return float(20.0 * math.log10(float(rms) + 1e-12)) + + +def _loudness_gain(db: float, offset: float = SENS_DB_OFFSET) -> float: + """Normalize dB into [0,1] with gamma; clipped to [0,1].""" + t = (db + offset - SWAY_DB_LOW) / (SWAY_DB_HIGH - SWAY_DB_LOW) + if t < 0.0: + t = 0.0 + elif t > 1.0: + t = 1.0 + return t**LOUDNESS_GAMMA if LOUDNESS_GAMMA != 1.0 else t + + +def _to_float32_mono(x: NDArray[Any]) -> NDArray[np.float32]: + """Convert arbitrary PCM array to float32 mono in [-1,1]. + + Accepts shapes: (N,), (1,N), (N,1), (C,N), (N,C). + """ + a = np.asarray(x) + if a.ndim == 0: + return np.zeros(0, dtype=np.float32) + + # If 2D, decide which axis is channels (prefer small first dim) + if a.ndim == 2: + # e.g., (channels, samples) if channels is small (<=8) + if a.shape[0] <= 8 and a.shape[0] <= a.shape[1]: + a = np.mean(a, axis=0) + else: + a = np.mean(a, axis=1) + elif a.ndim > 2: + a = np.mean(a.reshape(a.shape[0], -1), axis=0) + + # Now 1D, cast/scale + if np.issubdtype(a.dtype, np.floating): + return a.astype(np.float32, copy=False) + # integer PCM + info = np.iinfo(a.dtype) + scale = float(max(-info.min, info.max)) + return a.astype(np.float32) / (scale if scale != 0.0 else 1.0) + + +def _resample_linear(x: NDArray[np.float32], sr_in: int, sr_out: int) -> NDArray[np.float32]: + """Lightweight linear resampler for short buffers.""" + if sr_in == sr_out or x.size == 0: + return x + # guard tiny sizes + n_out = int(round(x.size * sr_out / sr_in)) + if n_out <= 1: + return np.zeros(0, dtype=np.float32) + t_in = np.linspace(0.0, 1.0, num=x.size, dtype=np.float32, endpoint=True) + t_out = np.linspace(0.0, 1.0, num=n_out, dtype=np.float32, endpoint=True) + return np.interp(t_out, t_in, x).astype(np.float32, copy=False) + + +class SwayRollRT: + """Feed audio chunks → per-hop sway outputs. + + Usage: + rt = SwayRollRT() + rt.feed(pcm_int16_or_float, sr) -> List[dict] + """ + + def __init__(self, rng_seed: int = 7): + """Initialize state.""" + self._seed = int(rng_seed) + self.samples: deque[float] = deque(maxlen=10 * SR) # sliding window for VAD/env + self.carry: NDArray[np.float32] = np.zeros(0, dtype=np.float32) + + self.vad_on = False + self.vad_above = 0 + self.vad_below = 0 + + self.sway_env = 0.0 + self.sway_up = 0 + self.sway_down = 0 + + rng = np.random.default_rng(self._seed) + self.phase_pitch = float(rng.random() * 2 * math.pi) + self.phase_yaw = float(rng.random() * 2 * math.pi) + self.phase_roll = float(rng.random() * 2 * math.pi) + self.phase_x = float(rng.random() * 2 * math.pi) + self.phase_y = float(rng.random() * 2 * math.pi) + self.phase_z = float(rng.random() * 2 * math.pi) + self.t = 0.0 + + def reset(self) -> None: + """Reset state (VAD/env/buffers/time) but keep initial phases/seed.""" + self.samples.clear() + self.carry = np.zeros(0, dtype=np.float32) + self.vad_on = False + self.vad_above = 0 + self.vad_below = 0 + self.sway_env = 0.0 + self.sway_up = 0 + self.sway_down = 0 + self.t = 0.0 + + def feed(self, pcm: NDArray[Any], sr: int | None) -> List[Dict[str, float]]: + """Stream in PCM chunk. Returns a list of sway dicts, one per hop (HOP_MS). + + Args: + pcm: np.ndarray, shape (N,) or (C,N)/(N,C); int or float. + sr: sample rate of `pcm` (None -> assume SR). + + """ + sr_in = SR if sr is None else int(sr) + x = _to_float32_mono(pcm) + if x.size == 0: + return [] + if sr_in != SR: + x = _resample_linear(x, sr_in, SR) + if x.size == 0: + return [] + + # append to carry and consume fixed HOP chunks + if self.carry.size: + self.carry = np.concatenate([self.carry, x]) + else: + self.carry = x + + out: List[Dict[str, float]] = [] + + while self.carry.size >= HOP: + hop = self.carry[:HOP] + remaining: NDArray[np.float32] = self.carry[HOP:] + self.carry = remaining + + # keep sliding window for VAD/env computation + # (deque accepts any iterable; list() for small HOP is fine) + self.samples.extend(hop.tolist()) + if len(self.samples) < FRAME: + self.t += HOP_MS / 1000.0 + continue + + frame = np.fromiter( + islice(self.samples, len(self.samples) - FRAME, len(self.samples)), + dtype=np.float32, + count=FRAME, + ) + db = _rms_dbfs(frame) + + # VAD with hysteresis + attack/release + if db >= VAD_DB_ON: + self.vad_above += 1 + self.vad_below = 0 + if not self.vad_on and self.vad_above >= ATTACK_FR: + self.vad_on = True + elif db <= VAD_DB_OFF: + self.vad_below += 1 + self.vad_above = 0 + if self.vad_on and self.vad_below >= RELEASE_FR: + self.vad_on = False + + if self.vad_on: + self.sway_up = min(SWAY_ATTACK_FR, self.sway_up + 1) + self.sway_down = 0 + else: + self.sway_down = min(SWAY_RELEASE_FR, self.sway_down + 1) + self.sway_up = 0 + + up = self.sway_up / SWAY_ATTACK_FR + down = 1.0 - (self.sway_down / SWAY_RELEASE_FR) + target = up if self.vad_on else down + self.sway_env += ENV_FOLLOW_GAIN * (target - self.sway_env) + # clamp + if self.sway_env < 0.0: + self.sway_env = 0.0 + elif self.sway_env > 1.0: + self.sway_env = 1.0 + + loud = _loudness_gain(db) * SWAY_MASTER + env = self.sway_env + self.t += HOP_MS / 1000.0 + + # oscillators + pitch = ( + math.radians(SWAY_A_PITCH_DEG) + * loud + * env + * math.sin(2 * math.pi * SWAY_F_PITCH * self.t + self.phase_pitch) + ) + yaw = ( + math.radians(SWAY_A_YAW_DEG) + * loud + * env + * math.sin(2 * math.pi * SWAY_F_YAW * self.t + self.phase_yaw) + ) + roll = ( + math.radians(SWAY_A_ROLL_DEG) + * loud + * env + * math.sin(2 * math.pi * SWAY_F_ROLL * self.t + self.phase_roll) + ) + x_mm = SWAY_A_X_MM * loud * env * math.sin(2 * math.pi * SWAY_F_X * self.t + self.phase_x) + y_mm = SWAY_A_Y_MM * loud * env * math.sin(2 * math.pi * SWAY_F_Y * self.t + self.phase_y) + z_mm = SWAY_A_Z_MM * loud * env * math.sin(2 * math.pi * SWAY_F_Z * self.t + self.phase_z) + + out.append( + { + "pitch_rad": pitch, + "yaw_rad": yaw, + "roll_rad": roll, + "pitch_deg": math.degrees(pitch), + "yaw_deg": math.degrees(yaw), + "roll_deg": math.degrees(roll), + "x_mm": x_mm, + "y_mm": y_mm, + "z_mm": z_mm, + }, + ) + + return out diff --git a/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/camera_worker.py b/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/camera_worker.py new file mode 100644 index 00000000..e625c009 --- /dev/null +++ b/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/camera_worker.py @@ -0,0 +1,241 @@ +"""Camera worker thread with frame buffering and face tracking. + +Ported from main_works.py camera_worker() function to provide: +- 30Hz+ camera polling with thread-safe frame buffering +- Face tracking integration with smooth interpolation +- Latest frame always available for tools +""" + +import time +import logging +import threading +from typing import Any, List, Tuple + +import numpy as np +from numpy.typing import NDArray +from scipy.spatial.transform import Rotation as R + +from reachy_mini import ReachyMini +from reachy_mini.utils.interpolation import linear_pose_interpolation + + +logger = logging.getLogger(__name__) + + +class CameraWorker: + """Thread-safe camera worker with frame buffering and face tracking.""" + + def __init__(self, reachy_mini: ReachyMini, head_tracker: Any = None) -> None: + """Initialize.""" + self.reachy_mini = reachy_mini + self.head_tracker = head_tracker + + # Thread-safe frame storage + self.latest_frame: NDArray[np.uint8] | None = None + self.frame_lock = threading.Lock() + self._stop_event = threading.Event() + self._thread: threading.Thread | None = None + + # Face tracking state + self.is_head_tracking_enabled = True + self.face_tracking_offsets: List[float] = [ + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + ] # x, y, z, roll, pitch, yaw + self.face_tracking_lock = threading.Lock() + + # Face tracking timing variables (same as main_works.py) + self.last_face_detected_time: float | None = None + self.interpolation_start_time: float | None = None + self.interpolation_start_pose: NDArray[np.float32] | None = None + self.face_lost_delay = 2.0 # seconds to wait before starting interpolation + self.interpolation_duration = 1.0 # seconds to interpolate back to neutral + + # Track state changes + self.previous_head_tracking_state = self.is_head_tracking_enabled + + def get_latest_frame(self) -> NDArray[np.uint8] | None: + """Get the latest frame (thread-safe).""" + with self.frame_lock: + if self.latest_frame is None: + return None + # Return a copy in original BGR format (OpenCV native) + return self.latest_frame.copy() + + def get_face_tracking_offsets( + self, + ) -> Tuple[float, float, float, float, float, float]: + """Get current face tracking offsets (thread-safe).""" + with self.face_tracking_lock: + offsets = self.face_tracking_offsets + return (offsets[0], offsets[1], offsets[2], offsets[3], offsets[4], offsets[5]) + + def set_head_tracking_enabled(self, enabled: bool) -> None: + """Enable/disable head tracking.""" + self.is_head_tracking_enabled = enabled + logger.info(f"Head tracking {'enabled' if enabled else 'disabled'}") + + def start(self) -> None: + """Start the camera worker loop in a thread.""" + self._stop_event.clear() + self._thread = threading.Thread(target=self.working_loop, daemon=True) + self._thread.start() + logger.debug("Camera worker started") + + def stop(self) -> None: + """Stop the camera worker loop.""" + self._stop_event.set() + if self._thread is not None: + self._thread.join() + + logger.debug("Camera worker stopped") + + def working_loop(self) -> None: + """Enable the camera worker loop. + + Ported from main_works.py camera_worker() with same logic. + """ + logger.debug("Starting camera working loop") + + # Initialize head tracker if available + neutral_pose = np.eye(4) # Neutral pose (identity matrix) + self.previous_head_tracking_state = self.is_head_tracking_enabled + + while not self._stop_event.is_set(): + try: + current_time = time.time() + + # Get frame from robot + frame = self.reachy_mini.media.get_frame() + + if frame is not None: + # Thread-safe frame storage + with self.frame_lock: + self.latest_frame = frame # .copy() + + # Check if face tracking was just disabled + if self.previous_head_tracking_state and not self.is_head_tracking_enabled: + # Face tracking was just disabled - start interpolation to neutral + self.last_face_detected_time = current_time # Trigger the face-lost logic + self.interpolation_start_time = None # Will be set by the face-lost interpolation + self.interpolation_start_pose = None + + # Update tracking state + self.previous_head_tracking_state = self.is_head_tracking_enabled + + # Handle face tracking if enabled and head tracker available + if self.is_head_tracking_enabled and self.head_tracker is not None: + eye_center, _ = self.head_tracker.get_head_position(frame) + + if eye_center is not None: + # Face detected - immediately switch to tracking + self.last_face_detected_time = current_time + self.interpolation_start_time = None # Stop any interpolation + + # Convert normalized coordinates to pixel coordinates + h, w, _ = frame.shape + eye_center_norm = (eye_center + 1) / 2 + eye_center_pixels = [ + eye_center_norm[0] * w, + eye_center_norm[1] * h, + ] + + # Get the head pose needed to look at the target, but don't perform movement + target_pose = self.reachy_mini.look_at_image( + eye_center_pixels[0], + eye_center_pixels[1], + duration=0.0, + perform_movement=False, + ) + + # Extract translation and rotation from the target pose directly + translation = target_pose[:3, 3] + rotation = R.from_matrix(target_pose[:3, :3]).as_euler("xyz", degrees=False) + + # Scale down translation and rotation because smaller FOV + translation *= 0.6 + rotation *= 0.6 + + # Thread-safe update of face tracking offsets (use pose as-is) + with self.face_tracking_lock: + self.face_tracking_offsets = [ + translation[0], + translation[1], + translation[2], # x, y, z + rotation[0], + rotation[1], + rotation[2], # roll, pitch, yaw + ] + + # No face detected while tracking enabled - set face lost timestamp + elif self.last_face_detected_time is None or self.last_face_detected_time == current_time: + # Only update if we haven't already set a face lost time + # (current_time check prevents overriding the disable-triggered timestamp) + pass + + # Handle smooth interpolation (works for both face-lost and tracking-disabled cases) + if self.last_face_detected_time is not None: + time_since_face_lost = current_time - self.last_face_detected_time + + if time_since_face_lost >= self.face_lost_delay: + # Start interpolation if not already started + if self.interpolation_start_time is None: + self.interpolation_start_time = current_time + # Capture current pose as start of interpolation + with self.face_tracking_lock: + current_translation = self.face_tracking_offsets[:3] + current_rotation_euler = self.face_tracking_offsets[3:] + # Convert to 4x4 pose matrix + pose_matrix = np.eye(4, dtype=np.float32) + pose_matrix[:3, 3] = current_translation + pose_matrix[:3, :3] = R.from_euler( + "xyz", + current_rotation_euler, + ).as_matrix() + self.interpolation_start_pose = pose_matrix + + # Calculate interpolation progress (t from 0 to 1) + elapsed_interpolation = current_time - self.interpolation_start_time + t = min(1.0, elapsed_interpolation / self.interpolation_duration) + + # Interpolate between current pose and neutral pose + interpolated_pose = linear_pose_interpolation( + self.interpolation_start_pose, + neutral_pose, + t, + ) + + # Extract translation and rotation from interpolated pose + translation = interpolated_pose[:3, 3] + rotation = R.from_matrix(interpolated_pose[:3, :3]).as_euler("xyz", degrees=False) + + # Thread-safe update of face tracking offsets + with self.face_tracking_lock: + self.face_tracking_offsets = [ + translation[0], + translation[1], + translation[2], # x, y, z + rotation[0], + rotation[1], + rotation[2], # roll, pitch, yaw + ] + + # If interpolation is complete, reset timing + if t >= 1.0: + self.last_face_detected_time = None + self.interpolation_start_time = None + self.interpolation_start_pose = None + # else: Keep current offsets (within 2s delay period) + + # Small sleep to prevent excessive CPU usage (same as main_works.py) + time.sleep(0.04) + + except Exception as e: + logger.error(f"Camera worker error: {e}") + time.sleep(0.1) # Longer sleep on error + + logger.debug("Camera worker thread exited") diff --git a/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/config.py b/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/config.py new file mode 100644 index 00000000..fe10c9fd --- /dev/null +++ b/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/config.py @@ -0,0 +1,73 @@ +import os +import sys +import logging +from pathlib import Path + +from dotenv import find_dotenv, load_dotenv + + +LOCKED_PROFILE = "_reachy_mini_conversation_app_locked_profile" +DEFAULT_PROFILES_DIRECTORY = Path(__file__).parent / "profiles" + +logger = logging.getLogger(__name__) + + +def _env_flag(name: str, default: bool = False) -> bool: + """Parse a boolean environment flag.""" + raw = os.getenv(name) + if raw is None: + return default + + value = raw.strip().lower() + if value in {"1", "true", "yes", "on"}: + return True + if value in {"0", "false", "no", "off"}: + return False + + logger.warning("Invalid boolean value for %s=%r, using default=%s", name, raw, default) + return default + + +_profile_path = DEFAULT_PROFILES_DIRECTORY / LOCKED_PROFILE +_instructions_file = _profile_path / "instructions.txt" +if not _profile_path.is_dir(): + print(f"Error: locked profile '{LOCKED_PROFILE}' does not exist in {DEFAULT_PROFILES_DIRECTORY}", file=sys.stderr) + sys.exit(1) +if not _instructions_file.is_file(): + print(f"Error: locked profile '{LOCKED_PROFILE}' has no instructions.txt", file=sys.stderr) + sys.exit(1) + +_skip_dotenv = _env_flag("REACHY_MINI_SKIP_DOTENV", default=False) + +if _skip_dotenv: + logger.info("Skipping .env loading because REACHY_MINI_SKIP_DOTENV is set") +else: + # Locate .env file (search upward from current working directory) + dotenv_path = find_dotenv(usecwd=True) + + if dotenv_path: + # Load .env and override environment variables + load_dotenv(dotenv_path=dotenv_path, override=True) + logger.info(f"Configuration loaded from {dotenv_path}") + else: + logger.warning("No .env file found, using environment variables") + + +class Config: + """Configuration class for the conversation app.""" + + OPENAI_API_KEY = os.getenv("OPENAI_API_KEY") + MODEL_NAME = os.getenv("MODEL_NAME", "gpt-realtime") + HF_HOME = os.getenv("HF_HOME", "./cache") + LOCAL_VISION_MODEL = os.getenv("LOCAL_VISION_MODEL", "HuggingFaceTB/SmolVLM2-2.2B-Instruct") + HF_TOKEN = os.getenv("HF_TOKEN") + + logger.debug(f"Model: {MODEL_NAME}, HF_HOME: {HF_HOME}, Vision Model: {LOCAL_VISION_MODEL}") + logger.debug(f"Locked profile: {LOCKED_PROFILE}") + + def __init__(self) -> None: + """Initialize the configuration.""" + logger.info("Using locked profile '%s' from %s", LOCKED_PROFILE, DEFAULT_PROFILES_DIRECTORY) + + +config = Config() diff --git a/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/console.py b/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/console.py new file mode 100644 index 00000000..57103578 --- /dev/null +++ b/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/console.py @@ -0,0 +1,419 @@ +"""Bidirectional local audio stream with optional settings UI. + +In headless mode, there is no Gradio UI. If the OpenAI API key is not +available via environment/.env, we expose a minimal settings page via the +Reachy Mini Apps settings server to let non-technical users enter it. + +The settings UI is served from this package's ``static/`` folder and offers a +single password field to set ``OPENAI_API_KEY``. Once set, we persist it to the +app instance's ``.env`` file (if available) and proceed to start streaming. +""" + +import os +import sys +import time +import asyncio +import logging +from typing import List, Optional +from pathlib import Path + +from fastrtc import AdditionalOutputs, audio_to_float32 +from scipy.signal import resample + +from reachy_mini import ReachyMini +from reachy_mini.media.media_manager import MediaBackend +from reachy_mini_conversation_app.config import config +from reachy_mini_conversation_app.openai_realtime import OpenaiRealtimeHandler + + +try: + # FastAPI is provided by the Reachy Mini Apps runtime + from fastapi import FastAPI, Response + from pydantic import BaseModel + from fastapi.responses import FileResponse, JSONResponse + from starlette.staticfiles import StaticFiles +except Exception: # pragma: no cover - only loaded when settings_app is used + FastAPI = object # type: ignore + FileResponse = object # type: ignore + JSONResponse = object # type: ignore + StaticFiles = object # type: ignore + BaseModel = object # type: ignore + + +logger = logging.getLogger(__name__) + + +class LocalStream: + """LocalStream using Reachy Mini's recorder/player.""" + + def __init__( + self, + handler: OpenaiRealtimeHandler, + robot: ReachyMini, + *, + settings_app: Optional[FastAPI] = None, + instance_path: Optional[str] = None, + ): + """Initialize the stream with an OpenAI realtime handler and pipelines. + + - ``settings_app``: the Reachy Mini Apps FastAPI to attach settings endpoints. + - ``instance_path``: directory where per-instance ``.env`` should be stored. + """ + self.handler = handler + self._robot = robot + self._stop_event = asyncio.Event() + self._tasks: List[asyncio.Task[None]] = [] + # Allow the handler to flush the player queue when appropriate. + self.handler._clear_queue = self.clear_audio_queue + self._settings_app: Optional[FastAPI] = settings_app + self._instance_path: Optional[str] = instance_path + self._settings_initialized = False + self._asyncio_loop = None + + # ---- Settings UI (only when API key is missing) ---- + def _read_env_lines(self, env_path: Path) -> list[str]: + """Load env file contents or a template as a list of lines.""" + inst = env_path.parent + try: + if env_path.exists(): + try: + return env_path.read_text(encoding="utf-8").splitlines() + except Exception: + return [] + template_text = None + ex = inst / ".env.example" + if ex.exists(): + try: + template_text = ex.read_text(encoding="utf-8") + except Exception: + template_text = None + if template_text is None: + try: + cwd_example = Path.cwd() / ".env.example" + if cwd_example.exists(): + template_text = cwd_example.read_text(encoding="utf-8") + except Exception: + template_text = None + if template_text is None: + packaged = Path(__file__).parent / ".env.example" + if packaged.exists(): + try: + template_text = packaged.read_text(encoding="utf-8") + except Exception: + template_text = None + return template_text.splitlines() if template_text else [] + except Exception: + return [] + + def _persist_api_key(self, key: str) -> None: + """Persist API key to environment and instance ``.env`` if possible. + + Behavior: + - Always sets ``OPENAI_API_KEY`` in process env and in-memory config. + - Writes/updates ``/.env``: + * If ``.env`` exists, replaces/append OPENAI_API_KEY line. + * Else, copies template from ``/.env.example`` when present, + otherwise falls back to the packaged template + ``reachy_mini_conversation_app/.env.example``. + * Ensures the resulting file contains the full template plus the key. + - Loads the written ``.env`` into the current process environment. + """ + k = (key or "").strip() + if not k: + return + # Update live process env and config so consumers see it immediately + try: + os.environ["OPENAI_API_KEY"] = k + except Exception: # best-effort + pass + try: + config.OPENAI_API_KEY = k + except Exception: + pass + + if not self._instance_path: + return + try: + inst = Path(self._instance_path) + env_path = inst / ".env" + lines = self._read_env_lines(env_path) + replaced = False + for i, ln in enumerate(lines): + if ln.strip().startswith("OPENAI_API_KEY="): + lines[i] = f"OPENAI_API_KEY={k}" + replaced = True + break + if not replaced: + lines.append(f"OPENAI_API_KEY={k}") + final_text = "\n".join(lines) + "\n" + env_path.write_text(final_text, encoding="utf-8") + logger.info("Persisted OPENAI_API_KEY to %s", env_path) + + # Load the newly written .env into this process to ensure downstream imports see it + try: + from dotenv import load_dotenv + + load_dotenv(dotenv_path=str(env_path), override=True) + except Exception: + pass + except Exception as e: + logger.warning("Failed to persist OPENAI_API_KEY: %s", e) + + def _init_settings_ui_if_needed(self) -> None: + """Attach minimal settings UI to the settings app. + + Always mounts the UI when a settings_app is provided so that users + see a confirmation message even if the API key is already configured. + """ + if self._settings_initialized: + return + if self._settings_app is None: + return + + static_dir = Path(__file__).parent / "static" + index_file = static_dir / "index.html" + + if hasattr(self._settings_app, "mount"): + try: + # Serve /static/* assets + self._settings_app.mount("/static", StaticFiles(directory=str(static_dir)), name="static") + except Exception: + pass + + class ApiKeyPayload(BaseModel): + openai_api_key: str + + # GET / -> index.html + @self._settings_app.get("/") + def _root() -> FileResponse: + return FileResponse(str(index_file)) + + # GET /favicon.ico -> optional, avoid noisy 404s on some browsers + @self._settings_app.get("/favicon.ico") + def _favicon() -> Response: + return Response(status_code=204) + + # GET /status -> whether key is set + @self._settings_app.get("/status") + def _status() -> JSONResponse: + has_key = bool(config.OPENAI_API_KEY and str(config.OPENAI_API_KEY).strip()) + return JSONResponse({"has_key": has_key}) + + # GET /ready -> whether backend finished loading tools + @self._settings_app.get("/ready") + def _ready() -> JSONResponse: + try: + mod = sys.modules.get("reachy_mini_conversation_app.tools.core_tools") + ready = bool(getattr(mod, "_TOOLS_INITIALIZED", False)) if mod else False + except Exception: + ready = False + return JSONResponse({"ready": ready}) + + # POST /openai_api_key -> set/persist key + @self._settings_app.post("/openai_api_key") + def _set_key(payload: ApiKeyPayload) -> JSONResponse: + key = (payload.openai_api_key or "").strip() + if not key: + return JSONResponse({"ok": False, "error": "empty_key"}, status_code=400) + self._persist_api_key(key) + return JSONResponse({"ok": True}) + + # POST /validate_api_key -> validate key without persisting it + @self._settings_app.post("/validate_api_key") + async def _validate_key(payload: ApiKeyPayload) -> JSONResponse: + key = (payload.openai_api_key or "").strip() + if not key: + return JSONResponse({"valid": False, "error": "empty_key"}, status_code=400) + + # Try to validate by checking if we can fetch the models + try: + import httpx + + headers = {"Authorization": f"Bearer {key}", "Content-Type": "application/json"} + async with httpx.AsyncClient(timeout=10.0) as client: + response = await client.get("https://api.openai.com/v1/models", headers=headers) + if response.status_code == 200: + return JSONResponse({"valid": True}) + elif response.status_code == 401: + return JSONResponse({"valid": False, "error": "invalid_api_key"}, status_code=401) + else: + return JSONResponse( + {"valid": False, "error": "validation_failed"}, status_code=response.status_code + ) + except Exception as e: + logger.warning(f"API key validation failed: {e}") + return JSONResponse({"valid": False, "error": "validation_error"}, status_code=500) + + self._settings_initialized = True + + def launch(self) -> None: + """Start the recorder/player and run the async processing loops. + + If the OpenAI key is missing, expose a tiny settings UI via the + Reachy Mini settings server to collect it before starting streams. + """ + self._stop_event.clear() + + # Try to load an existing instance .env first (covers subsequent runs) + if self._instance_path: + try: + from dotenv import load_dotenv + + env_path = Path(self._instance_path) / ".env" + if env_path.exists(): + load_dotenv(dotenv_path=str(env_path), override=True) + new_key = os.getenv("OPENAI_API_KEY", "").strip() + if new_key: + try: + config.OPENAI_API_KEY = new_key + except Exception: + pass + except Exception: + pass # Instance .env loading is optional; continue with defaults + + # If key is still missing, try to download one from HuggingFace + if not (config.OPENAI_API_KEY and str(config.OPENAI_API_KEY).strip()): + logger.info("OPENAI_API_KEY not set, attempting to download from HuggingFace...") + try: + from gradio_client import Client + client = Client("HuggingFaceM4/gradium_setup", verbose=False) + key, status = client.predict(api_name="/claim_b_key") + if key and key.strip(): + logger.info("Successfully downloaded API key from HuggingFace") + # Persist it immediately + self._persist_api_key(key) + except Exception as e: + logger.warning(f"Failed to download API key from HuggingFace: {e}") + + # Always expose settings UI if a settings app is available + # (do this AFTER loading/downloading the key so status endpoint sees the right value) + self._init_settings_ui_if_needed() + + # If key is still missing -> wait until provided via the settings UI + if not (config.OPENAI_API_KEY and str(config.OPENAI_API_KEY).strip()): + logger.warning("OPENAI_API_KEY not found. Open the app settings page to enter it.") + # Poll until the key becomes available (set via the settings UI) + try: + while not (config.OPENAI_API_KEY and str(config.OPENAI_API_KEY).strip()): + time.sleep(0.2) + except KeyboardInterrupt: + logger.info("Interrupted while waiting for API key.") + return + + # Start media after key is set/available + self._robot.media.start_recording() + self._robot.media.start_playing() + time.sleep(1) # give some time to the pipelines to start + + async def runner() -> None: + self._asyncio_loop = asyncio.get_running_loop() # type: ignore[assignment] + self._tasks = [ + asyncio.create_task(self.handler.start_up(), name="openai-handler"), + asyncio.create_task(self.record_loop(), name="stream-record-loop"), + asyncio.create_task(self.play_loop(), name="stream-play-loop"), + ] + try: + await asyncio.gather(*self._tasks) + except asyncio.CancelledError: + logger.info("Tasks cancelled during shutdown") + finally: + # Ensure handler connection is closed + await self.handler.shutdown() + + asyncio.run(runner()) + + def close(self) -> None: + """Stop the stream and underlying media pipelines. + + This method: + - Stops audio recording and playback first + - Sets the stop event to signal async loops to terminate + - Cancels all pending async tasks (openai-handler, record-loop, play-loop) + """ + logger.info("Stopping LocalStream...") + + # Stop media pipelines FIRST before cancelling async tasks + # This ensures clean shutdown before PortAudio cleanup + try: + self._robot.media.stop_recording() + except Exception as e: + logger.debug(f"Error stopping recording (may already be stopped): {e}") + + try: + self._robot.media.stop_playing() + except Exception as e: + logger.debug(f"Error stopping playback (may already be stopped): {e}") + + # Now signal async loops to stop + self._stop_event.set() + + # Cancel all running tasks + for task in self._tasks: + if not task.done(): + task.cancel() + + def clear_audio_queue(self) -> None: + """Flush the player's appsrc to drop any queued audio immediately.""" + logger.info("User intervention: flushing player queue") + if self._robot.media.backend == MediaBackend.GSTREAMER: + # Directly flush gstreamer audio pipe + self._robot.media.audio.clear_player() + elif self._robot.media.backend == MediaBackend.DEFAULT or self._robot.media.backend == MediaBackend.DEFAULT_NO_VIDEO: + self._robot.media.audio.clear_output_buffer() + self.handler.output_queue = asyncio.Queue() + + async def record_loop(self) -> None: + """Read mic frames from the recorder and forward them to the handler.""" + input_sample_rate = self._robot.media.get_input_audio_samplerate() + logger.debug(f"Audio recording started at {input_sample_rate} Hz") + + while not self._stop_event.is_set(): + audio_frame = self._robot.media.get_audio_sample() + if audio_frame is not None: + await self.handler.receive((input_sample_rate, audio_frame)) + await asyncio.sleep(0) # avoid busy loop + + async def play_loop(self) -> None: + """Fetch outputs from the handler: log text and play audio frames.""" + while not self._stop_event.is_set(): + handler_output = await self.handler.emit() + + if isinstance(handler_output, AdditionalOutputs): + for msg in handler_output.args: + content = msg.get("content", "") + if isinstance(content, str): + logger.info( + "role=%s content=%s", + msg.get("role"), + content if len(content) < 500 else content[:500] + "…", + ) + + elif isinstance(handler_output, tuple): + input_sample_rate, audio_data = handler_output + output_sample_rate = self._robot.media.get_output_audio_samplerate() + + # Reshape if needed + if audio_data.ndim == 2: + # Scipy channels last convention + if audio_data.shape[1] > audio_data.shape[0]: + audio_data = audio_data.T + # Multiple channels -> Mono channel + if audio_data.shape[1] > 1: + audio_data = audio_data[:, 0] + + # Cast if needed + audio_frame = audio_to_float32(audio_data) + + # Resample if needed + if input_sample_rate != output_sample_rate: + audio_frame = resample( + audio_frame, + int(len(audio_frame) * output_sample_rate / input_sample_rate), + ) + + self._robot.media.push_audio_sample(audio_frame) + + else: + logger.debug("Ignoring output type=%s", type(handler_output).__name__) + + await asyncio.sleep(0) # yield to event loop diff --git a/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/dance_emotion_moves.py b/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/dance_emotion_moves.py new file mode 100644 index 00000000..d2d7028d --- /dev/null +++ b/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/dance_emotion_moves.py @@ -0,0 +1,86 @@ +"""Dance and emotion moves for the movement queue system. + +This module implements dance moves and emotions as Move objects that can be queued +and executed sequentially by the MovementManager. +""" + +from __future__ import annotations +import logging + +import numpy as np +from numpy.typing import NDArray + +from reachy_mini.motion.move import Move +from reachy_mini.motion.recorded_move import RecordedMoves +from reachy_mini_dances_library.dance_move import DanceMove + + +logger = logging.getLogger(__name__) + + +class DanceQueueMove(Move): # type: ignore + """Wrapper for dance moves to work with the movement queue system.""" + + def __init__(self, move_name: str): + """Initialize a DanceQueueMove.""" + self.dance_move = DanceMove(move_name) + self.move_name = move_name + + @property + def duration(self) -> float: + """Duration property required by official Move interface.""" + return float(self.dance_move.duration) + + def evaluate(self, t: float) -> tuple[NDArray[np.float64] | None, NDArray[np.float64] | None, float | None]: + """Evaluate dance move at time t.""" + try: + # Get the pose from the dance move + head_pose, antennas, body_yaw = self.dance_move.evaluate(t) + + # Convert to numpy array if antennas is tuple and return in official Move format + if isinstance(antennas, tuple): + antennas = np.array([antennas[0], antennas[1]]) + + return (head_pose, antennas, body_yaw) + + except Exception as e: + logger.error(f"Error evaluating dance move '{self.move_name}' at t={t}: {e}") + # Return neutral pose on error + from reachy_mini.utils import create_head_pose + + neutral_head_pose = create_head_pose(0, 0, 0, 0, 0, 0, degrees=True) + return (neutral_head_pose, np.array([0.0, 0.0], dtype=np.float64), 0.0) + + +class EmotionQueueMove(Move): # type: ignore + """Wrapper for emotion moves to work with the movement queue system.""" + + def __init__(self, emotion_name: str, recorded_moves: RecordedMoves): + """Initialize an EmotionQueueMove.""" + self.emotion_move = recorded_moves.get(emotion_name) + self.emotion_name = emotion_name + + @property + def duration(self) -> float: + """Duration property required by official Move interface.""" + return float(self.emotion_move.duration) + + def evaluate(self, t: float) -> tuple[NDArray[np.float64] | None, NDArray[np.float64] | None, float | None]: + """Evaluate emotion move at time t.""" + try: + # Get the pose from the emotion move + head_pose, antennas, body_yaw = self.emotion_move.evaluate(t) + + # Convert to numpy array if antennas is tuple and return in official Move format + if isinstance(antennas, tuple): + antennas = np.array([antennas[0], antennas[1]]) + + return (head_pose, antennas, body_yaw) + + except Exception as e: + logger.error(f"Error evaluating emotion '{self.emotion_name}' at t={t}: {e}") + # Return neutral pose on error + from reachy_mini.utils import create_head_pose + + neutral_head_pose = create_head_pose(0, 0, 0, 0, 0, 0, degrees=True) + return (neutral_head_pose, np.array([0.0, 0.0], dtype=np.float64), 0.0) diff --git a/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/goto_queue_move.py b/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/goto_queue_move.py new file mode 100644 index 00000000..64801597 --- /dev/null +++ b/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/goto_queue_move.py @@ -0,0 +1,68 @@ +"""Queued goto move for direct head, antenna, and body-yaw targets.""" + +from __future__ import annotations +import logging +from typing import Tuple + +import numpy as np +from numpy.typing import NDArray + +from reachy_mini.motion.move import Move + + +logger = logging.getLogger(__name__) + + +class GotoQueueMove(Move): # type: ignore[misc] + """Interpolate from a current pose to a target pose.""" + + def __init__( + self, + target_head_pose: NDArray[np.float32], + start_head_pose: NDArray[np.float32] | None = None, + target_antennas: Tuple[float, float] = (0, 0), + start_antennas: Tuple[float, float] | None = None, + target_body_yaw: float = 0, + start_body_yaw: float | None = None, + duration: float = 1.0, + ): + """Initialize a queued goto move.""" + self._duration = duration + self.target_head_pose = target_head_pose + self.start_head_pose = start_head_pose + self.target_antennas = target_antennas + self.start_antennas = start_antennas or (0, 0) + self.target_body_yaw = target_body_yaw + self.start_body_yaw = start_body_yaw or 0 + + @property + def duration(self) -> float: + """Duration required by the Move interface.""" + return self._duration + + def evaluate(self, t: float) -> tuple[NDArray[np.float64] | None, NDArray[np.float64] | None, float | None]: + """Evaluate the move at elapsed time t.""" + try: + from reachy_mini.utils import create_head_pose + from reachy_mini.utils.interpolation import linear_pose_interpolation + + t_clamped = max(0, min(1, t / self.duration)) + start_pose = self.start_head_pose + if start_pose is None: + start_pose = create_head_pose(0, 0, 0, 0, 0, 0, degrees=True) + + head_pose = linear_pose_interpolation(start_pose, self.target_head_pose, t_clamped) + antennas = np.array( + [ + self.start_antennas[0] + (self.target_antennas[0] - self.start_antennas[0]) * t_clamped, + self.start_antennas[1] + (self.target_antennas[1] - self.start_antennas[1]) * t_clamped, + ], + dtype=np.float64, + ) + body_yaw = self.start_body_yaw + (self.target_body_yaw - self.start_body_yaw) * t_clamped + return (head_pose, antennas, body_yaw) + except Exception as e: + logger.error("Error evaluating goto move at t=%s: %s", t, e) + target_head_pose_f64 = self.target_head_pose.astype(np.float64) + target_antennas_array = np.array([self.target_antennas[0], self.target_antennas[1]], dtype=np.float64) + return (target_head_pose_f64, target_antennas_array, self.target_body_yaw) diff --git a/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/images/reachymini_avatar.png b/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/images/reachymini_avatar.png new file mode 100644 index 0000000000000000000000000000000000000000..2ed3249419fe85f096003f4ade6dcb713f53701e GIT binary patch literal 1228716 zcmeEuby!tR+wYXm*4f_N#ofrsOv1v<&ZW`R&dAoxTt-=)jo1F%(G+R{buqG0vv+ke 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z);G@*yl6y+cW$5snIoB0fPI#)_t7#p1bp7v1NxSc z`K40%(xKDuEF#Q+5dA#s7x;WO>u7EsDj&_yy<;0OHLAAt8KNp`G;S>sP`&@De_8VN z=lg4pZCjYDitB|H1B1_|&QiraTTFgb7k~9*_UjSqG#fOC6h*EtSGVcOhY0`p#iQ3^ r&uKwFl7YHIzs^?Bf+EW?OV$5B*CEXXEe*_j00000NkvXXu0mjf{)Iu> literal 0 HcmV?d00001 diff --git a/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/main.py b/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/main.py new file mode 100644 index 00000000..6b809e8a --- /dev/null +++ b/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/main.py @@ -0,0 +1,255 @@ +"""Entrypoint for the Reachy Mini conversation app.""" + +import os +import sys +import time +import asyncio +import argparse +import threading +from typing import Any, Dict, List, Optional + +from reachy_mini import ReachyMini, ReachyMiniApp +from reachy_mini_conversation_app.utils import ( + parse_args, + setup_logger, + handle_vision_stuff, + log_connection_troubleshooting, +) + + +def update_chatbot(chatbot: List[Dict[str, Any]], response: Dict[str, Any]) -> List[Dict[str, Any]]: + """Update the chatbot with AdditionalOutputs.""" + chatbot.append(response) + return chatbot + + +def main() -> None: + """Entrypoint for the Reachy Mini conversation app.""" + args, _ = parse_args() + run(args) + + +def run( + args: argparse.Namespace, + robot: ReachyMini = None, + app_stop_event: Optional[threading.Event] = None, + settings_app: Optional[Any] = None, + instance_path: Optional[str] = None, +) -> None: + """Run the Reachy Mini conversation app.""" + try: + import gradio as gr + from fastapi import FastAPI + from fastrtc import Stream + from gradio.utils import get_space + except ImportError as exc: + raise RuntimeError( + "Reachy OpenShell conversation dependencies are not installed. " + "Run `uv sync` or `pip install -e .` from this project directory." + ) from exc + + # Putting these dependencies here makes the dashboard faster to load when the conversation app is installed + from reachy_mini_conversation_app.moves import MovementManager + from reachy_mini_conversation_app.console import LocalStream + from reachy_mini_conversation_app.openai_realtime import OpenaiRealtimeHandler + from reachy_mini_conversation_app.tools.core_tools import ToolDependencies + from reachy_mini_conversation_app.audio.head_wobbler import HeadWobbler + + logger = setup_logger(args.debug) + logger.info("Starting Reachy Mini Conversation App") + + if args.no_camera and args.head_tracker is not None: + logger.warning( + "Head tracking disabled: --no-camera flag is set. " + "Remove --no-camera to enable head tracking." + ) + + if robot is None: + try: + robot_kwargs = {} + if args.robot_name is not None: + robot_kwargs["robot_name"] = args.robot_name + + logger.info("Initializing ReachyMini (SDK will auto-detect appropriate backend)") + robot = ReachyMini(**robot_kwargs) + + except TimeoutError as e: + logger.error( + "Connection timeout: Failed to connect to Reachy Mini daemon. " + f"Details: {e}" + ) + log_connection_troubleshooting(logger, args.robot_name) + sys.exit(1) + + except ConnectionError as e: + logger.error( + "Connection failed: Unable to establish connection to Reachy Mini. " + f"Details: {e}" + ) + log_connection_troubleshooting(logger, args.robot_name) + sys.exit(1) + + except Exception as e: + logger.error( + f"Unexpected error during robot initialization: {type(e).__name__}: {e}" + ) + logger.error("Please check your configuration and try again.") + sys.exit(1) + + # Auto-enable Gradio in simulation mode (both MuJoCo for daemon and mockup-sim for desktop app) + status = robot.client.get_status() + if isinstance(status, dict): + simulation_enabled = status.get("simulation_enabled", False) + mockup_sim_enabled = status.get("mockup_sim_enabled", False) + else: + simulation_enabled = getattr(status, "simulation_enabled", False) + mockup_sim_enabled = getattr(status, "mockup_sim_enabled", False) + + is_simulation = simulation_enabled or mockup_sim_enabled + + if is_simulation and not args.gradio: + logger.info("Simulation mode detected. Automatically enabling gradio flag.") + args.gradio = True + + camera_worker, _, vision_manager = handle_vision_stuff(args, robot) + + movement_manager = MovementManager( + current_robot=robot, + camera_worker=camera_worker, + ) + + head_wobbler = HeadWobbler(set_speech_offsets=movement_manager.set_speech_offsets) + + deps = ToolDependencies( + reachy_mini=robot, + movement_manager=movement_manager, + camera_worker=camera_worker, + vision_manager=vision_manager, + head_wobbler=head_wobbler, + ) + current_file_path = os.path.dirname(os.path.abspath(__file__)) + logger.debug(f"Current file absolute path: {current_file_path}") + chatbot = gr.Chatbot( + type="messages", + resizable=True, + avatar_images=( + os.path.join(current_file_path, "images", "user_avatar.png"), + os.path.join(current_file_path, "images", "reachymini_avatar.png"), + ), + ) + logger.debug(f"Chatbot avatar images: {chatbot.avatar_images}") + + handler = OpenaiRealtimeHandler(deps, gradio_mode=args.gradio, instance_path=instance_path) + + stream_manager: gr.Blocks | LocalStream | None = None + + if args.gradio: + api_key_textbox = gr.Textbox( + label="OPENAI API Key", + type="password", + value=os.getenv("OPENAI_API_KEY") if not get_space() else "", + ) + + stream = Stream( + handler=handler, + mode="send-receive", + modality="audio", + additional_inputs=[ + chatbot, + api_key_textbox, + ], + additional_outputs=[chatbot], + additional_outputs_handler=update_chatbot, + ui_args={"title": "Talk with Reachy Mini"}, + ) + stream_manager = stream.ui + if not settings_app: + app = FastAPI() + else: + app = settings_app + + app = gr.mount_gradio_app(app, stream.ui, path="/") + else: + # In headless mode, wire settings_app + instance_path to console LocalStream + stream_manager = LocalStream( + handler, + robot, + settings_app=settings_app, + instance_path=instance_path, + ) + + # Each async service → its own thread/loop + movement_manager.start() + head_wobbler.start() + if camera_worker: + camera_worker.start() + if vision_manager: + vision_manager.start() + + def poll_stop_event() -> None: + """Poll the stop event to allow graceful shutdown.""" + if app_stop_event is not None: + app_stop_event.wait() + + logger.info("App stop event detected, shutting down...") + try: + stream_manager.close() + except Exception as e: + logger.error(f"Error while closing stream manager: {e}") + + if app_stop_event: + threading.Thread(target=poll_stop_event, daemon=True).start() + + try: + stream_manager.launch() + except KeyboardInterrupt: + logger.info("Keyboard interruption in main thread... closing server.") + finally: + movement_manager.stop() + head_wobbler.stop() + if camera_worker: + camera_worker.stop() + if vision_manager: + vision_manager.stop() + + # Ensure media is explicitly closed before disconnecting + try: + robot.media.close() + except Exception as e: + logger.debug(f"Error closing media during shutdown: {e}") + + # prevent connection to keep alive some threads + robot.client.disconnect() + time.sleep(1) + logger.info("Shutdown complete.") + + +class ReachyMiniConversationApp(ReachyMiniApp): # type: ignore[misc] + """Reachy Mini Apps entry point for the conversation app.""" + + custom_app_url = "http://0.0.0.0:7860/" + dont_start_webserver = False + + def run(self, reachy_mini: ReachyMini, stop_event: threading.Event) -> None: + """Run the Reachy Mini conversation app.""" + loop = asyncio.new_event_loop() + asyncio.set_event_loop(loop) + + args, _ = parse_args() + + instance_path = self._get_instance_path().parent + run( + args, + robot=reachy_mini, + app_stop_event=stop_event, + settings_app=self.settings_app, + instance_path=instance_path, + ) + + +if __name__ == "__main__": + app = ReachyMiniConversationApp() + try: + app.wrapped_run() + except KeyboardInterrupt: + app.stop() diff --git a/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/moves.py b/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/moves.py new file mode 100644 index 00000000..3c319e73 --- /dev/null +++ b/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/moves.py @@ -0,0 +1,849 @@ +"""Movement system with sequential primary moves and additive secondary moves. + +Design overview +- Primary moves (emotions, dances, goto, breathing) are mutually exclusive and run + sequentially. +- Secondary moves (speech sway, face tracking) are additive offsets applied on top + of the current primary pose. +- There is a single control point to the robot: `ReachyMini.set_target`. +- The control loop runs near 100 Hz and is phase-aligned via a monotonic clock. +- Idle behaviour starts an infinite `BreathingMove` after a short inactivity delay + unless listening is active. + +Threading model +- A dedicated worker thread owns all real-time state and issues `set_target` + commands. +- Other threads communicate via a command queue (enqueue moves, mark activity, + toggle listening). +- Secondary offset producers set pending values guarded by locks; the worker + snaps them atomically. + +Units and frames +- Secondary offsets are interpreted as metres for x/y/z and radians for + roll/pitch/yaw in the world frame (unless noted by `compose_world_offset`). +- Antennas and `body_yaw` are in radians. +- Head pose composition uses `compose_world_offset(primary_head, secondary_head)`; + the secondary offset must therefore be expressed in the world frame. + +Safety +- Listening freezes antennas, then blends them back on unfreeze. +- Interpolations and blends are used to avoid jumps at all times. +- `set_target` errors are rate-limited in logs. +""" + +from __future__ import annotations +import time +import logging +import threading +from queue import Empty, Queue +from typing import Any, Dict, Tuple +from collections import deque +from dataclasses import dataclass + +import numpy as np +from numpy.typing import NDArray + +from reachy_mini import ReachyMini +from reachy_mini.utils import create_head_pose +from reachy_mini.motion.move import Move +from reachy_mini.utils.interpolation import ( + compose_world_offset, + linear_pose_interpolation, +) + + +logger = logging.getLogger(__name__) + +# Configuration constants +CONTROL_LOOP_FREQUENCY_HZ = 100.0 # Hz - Target frequency for the movement control loop + +# Type definitions +FullBodyPose = Tuple[NDArray[np.float32], Tuple[float, float], float] # (head_pose_4x4, antennas, body_yaw) + + +class BreathingMove(Move): # type: ignore + """Breathing move with interpolation to neutral and then continuous breathing patterns.""" + + def __init__( + self, + interpolation_start_pose: NDArray[np.float32], + interpolation_start_antennas: Tuple[float, float], + interpolation_duration: float = 1.0, + ): + """Initialize breathing move. + + Args: + interpolation_start_pose: 4x4 matrix of current head pose to interpolate from + interpolation_start_antennas: Current antenna positions to interpolate from + interpolation_duration: Duration of interpolation to neutral (seconds) + + """ + self.interpolation_start_pose = interpolation_start_pose + self.interpolation_start_antennas = np.array(interpolation_start_antennas) + self.interpolation_duration = interpolation_duration + + # Neutral positions for breathing base + self.neutral_head_pose = create_head_pose(0, 0, 0, 0, 0, 0, degrees=True) + self.neutral_antennas = np.array([0.0, 0.0]) + + # Breathing parameters + self.breathing_z_amplitude = 0.005 # 5mm gentle breathing + self.breathing_frequency = 0.1 # Hz (6 breaths per minute) + self.antenna_sway_amplitude = np.deg2rad(15) # 15 degrees + self.antenna_frequency = 0.5 # Hz (faster antenna sway) + + @property + def duration(self) -> float: + """Duration property required by official Move interface.""" + return float("inf") # Continuous breathing (never ends naturally) + + def evaluate(self, t: float) -> tuple[NDArray[np.float64] | None, NDArray[np.float64] | None, float | None]: + """Evaluate breathing move at time t.""" + if t < self.interpolation_duration: + # Phase 1: Interpolate to neutral base position + interpolation_t = t / self.interpolation_duration + + # Interpolate head pose + head_pose = linear_pose_interpolation( + self.interpolation_start_pose, self.neutral_head_pose, interpolation_t, + ) + + # Interpolate antennas + antennas_interp = ( + 1 - interpolation_t + ) * self.interpolation_start_antennas + interpolation_t * self.neutral_antennas + antennas = antennas_interp.astype(np.float64) + + else: + # Phase 2: Breathing patterns from neutral base + breathing_time = t - self.interpolation_duration + + # Gentle z-axis breathing + z_offset = self.breathing_z_amplitude * np.sin(2 * np.pi * self.breathing_frequency * breathing_time) + head_pose = create_head_pose(x=0, y=0, z=z_offset, roll=0, pitch=0, yaw=0, degrees=True, mm=False) + + # Antenna sway (opposite directions) + antenna_sway = self.antenna_sway_amplitude * np.sin(2 * np.pi * self.antenna_frequency * breathing_time) + antennas = np.array([antenna_sway, -antenna_sway], dtype=np.float64) + + # Return in official Move interface format: (head_pose, antennas_array, body_yaw) + return (head_pose, antennas, 0.0) + + +def combine_full_body(primary_pose: FullBodyPose, secondary_pose: FullBodyPose) -> FullBodyPose: + """Combine primary and secondary full body poses. + + Args: + primary_pose: (head_pose, antennas, body_yaw) - primary move + secondary_pose: (head_pose, antennas, body_yaw) - secondary offsets + + Returns: + Combined full body pose (head_pose, antennas, body_yaw) + + """ + primary_head, primary_antennas, primary_body_yaw = primary_pose + secondary_head, secondary_antennas, secondary_body_yaw = secondary_pose + + # Combine head poses using compose_world_offset; the secondary pose must be an + # offset expressed in the world frame (T_off_world) applied to the absolute + # primary transform (T_abs). + combined_head = compose_world_offset(primary_head, secondary_head, reorthonormalize=True) + + # Sum antennas and body_yaw + combined_antennas = ( + primary_antennas[0] + secondary_antennas[0], + primary_antennas[1] + secondary_antennas[1], + ) + combined_body_yaw = primary_body_yaw + secondary_body_yaw + + return (combined_head, combined_antennas, combined_body_yaw) + + +def clone_full_body_pose(pose: FullBodyPose) -> FullBodyPose: + """Create a deep copy of a full body pose tuple.""" + head, antennas, body_yaw = pose + return (head.copy(), (float(antennas[0]), float(antennas[1])), float(body_yaw)) + + +@dataclass +class MovementState: + """State tracking for the movement system.""" + + # Primary move state + current_move: Move | None = None + move_start_time: float | None = None + last_activity_time: float = 0.0 + + # Secondary move state (offsets) + speech_offsets: Tuple[float, float, float, float, float, float] = ( + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + ) + face_tracking_offsets: Tuple[float, float, float, float, float, float] = ( + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + ) + + # Status flags + last_primary_pose: FullBodyPose | None = None + + def update_activity(self) -> None: + """Update the last activity time.""" + self.last_activity_time = time.monotonic() + + +@dataclass +class LoopFrequencyStats: + """Track rolling loop frequency statistics.""" + + mean: float = 0.0 + m2: float = 0.0 + min_freq: float = float("inf") + count: int = 0 + last_freq: float = 0.0 + potential_freq: float = 0.0 + + def reset(self) -> None: + """Reset accumulators while keeping the last potential frequency.""" + self.mean = 0.0 + self.m2 = 0.0 + self.min_freq = float("inf") + self.count = 0 + + +class MovementManager: + """Coordinate sequential moves, additive offsets, and robot output at 100 Hz. + + Responsibilities: + - Own a real-time loop that samples the current primary move (if any), fuses + secondary offsets, and calls `set_target` exactly once per tick. + - Start an idle `BreathingMove` after `idle_inactivity_delay` when not + listening and no moves are queued. + - Expose thread-safe APIs so other threads can enqueue moves, mark activity, + or feed secondary offsets without touching internal state. + + Timing: + - All elapsed-time calculations rely on `time.monotonic()` through `self._now` + to avoid wall-clock jumps. + - The loop attempts 100 Hz + + Concurrency: + - External threads communicate via `_command_queue` messages. + - Secondary offsets are staged via dirty flags guarded by locks and consumed + atomically inside the worker loop. + """ + + def __init__( + self, + current_robot: ReachyMini, + camera_worker: "Any" = None, + ): + """Initialize movement manager.""" + self.current_robot = current_robot + self.camera_worker = camera_worker + + # Single timing source for durations + self._now = time.monotonic + + # Movement state + self.state = MovementState() + self.state.last_activity_time = self._now() + neutral_pose = create_head_pose(0, 0, 0, 0, 0, 0, degrees=True) + self.state.last_primary_pose = (neutral_pose, (0.0, 0.0), 0.0) + + # Move queue (primary moves) + self.move_queue: deque[Move] = deque() + + # Configuration + self.idle_inactivity_delay = 0.3 # seconds + self.target_frequency = CONTROL_LOOP_FREQUENCY_HZ + self.target_period = 1.0 / self.target_frequency + + self._stop_event = threading.Event() + self._thread: threading.Thread | None = None + self._is_listening = False + self._last_commanded_pose: FullBodyPose = clone_full_body_pose(self.state.last_primary_pose) + self._listening_antennas: Tuple[float, float] = self._last_commanded_pose[1] + self._antenna_unfreeze_blend = 1.0 + self._antenna_blend_duration = 0.4 # seconds to blend back after listening + self._last_listening_blend_time = self._now() + self._breathing_active = False # true when breathing move is running or queued + self._listening_debounce_s = 0.15 + self._last_listening_toggle_time = self._now() + self._last_set_target_err = 0.0 + self._set_target_err_interval = 1.0 # seconds between error logs + self._set_target_err_suppressed = 0 + + # Cross-thread signalling + self._command_queue: "Queue[Tuple[str, Any]]" = Queue() + self._speech_offsets_lock = threading.Lock() + self._pending_speech_offsets: Tuple[float, float, float, float, float, float] = ( + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + ) + self._speech_offsets_dirty = False + + self._face_offsets_lock = threading.Lock() + self._pending_face_offsets: Tuple[float, float, float, float, float, float] = ( + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + ) + self._face_offsets_dirty = False + + self._shared_state_lock = threading.Lock() + self._shared_last_activity_time = self.state.last_activity_time + self._shared_is_listening = self._is_listening + self._status_lock = threading.Lock() + self._freq_stats = LoopFrequencyStats() + self._freq_snapshot = LoopFrequencyStats() + + def queue_move(self, move: Move) -> None: + """Queue a primary move to run after the currently executing one. + + Thread-safe: the move is enqueued via the worker command queue so the + control loop remains the sole mutator of movement state. + """ + self._command_queue.put(("queue_move", move)) + + def clear_move_queue(self) -> None: + """Stop the active move and discard any queued primary moves. + + Thread-safe: executed by the worker thread via the command queue. + """ + self._command_queue.put(("clear_queue", None)) + + def set_speech_offsets(self, offsets: Tuple[float, float, float, float, float, float]) -> None: + """Update speech-induced secondary offsets (x, y, z, roll, pitch, yaw). + + Offsets are interpreted as metres for translation and radians for + rotation in the world frame. Thread-safe via a pending snapshot. + """ + with self._speech_offsets_lock: + self._pending_speech_offsets = offsets + self._speech_offsets_dirty = True + + def set_moving_state(self, duration: float) -> None: + """Mark the robot as actively moving for the provided duration. + + Legacy hook used by goto helpers to keep inactivity and breathing logic + aware of manual motions. Thread-safe via the command queue. + """ + self._command_queue.put(("set_moving_state", duration)) + + def is_idle(self) -> bool: + """Return True when the robot has been inactive longer than the idle delay.""" + with self._shared_state_lock: + last_activity = self._shared_last_activity_time + listening = self._shared_is_listening + + if listening: + return False + + return self._now() - last_activity >= self.idle_inactivity_delay + + def set_listening(self, listening: bool) -> None: + """Enable or disable listening mode without touching shared state directly. + + While listening: + - Antenna positions are frozen at the last commanded values. + - Blending is reset so that upon unfreezing the antennas return smoothly. + - Idle breathing is suppressed. + + Thread-safe: the change is posted to the worker command queue. + """ + with self._shared_state_lock: + if self._shared_is_listening == listening: + return + self._command_queue.put(("set_listening", listening)) + + def _poll_signals(self, current_time: float) -> None: + """Apply queued commands and pending offset updates.""" + self._apply_pending_offsets() + + while True: + try: + command, payload = self._command_queue.get_nowait() + except Empty: + break + self._handle_command(command, payload, current_time) + + def _apply_pending_offsets(self) -> None: + """Apply the most recent speech/face offset updates.""" + speech_offsets: Tuple[float, float, float, float, float, float] | None = None + with self._speech_offsets_lock: + if self._speech_offsets_dirty: + speech_offsets = self._pending_speech_offsets + self._speech_offsets_dirty = False + + if speech_offsets is not None: + self.state.speech_offsets = speech_offsets + self.state.update_activity() + + face_offsets: Tuple[float, float, float, float, float, float] | None = None + with self._face_offsets_lock: + if self._face_offsets_dirty: + face_offsets = self._pending_face_offsets + self._face_offsets_dirty = False + + if face_offsets is not None: + self.state.face_tracking_offsets = face_offsets + self.state.update_activity() + + def _handle_command(self, command: str, payload: Any, current_time: float) -> None: + """Handle a single cross-thread command.""" + if command == "queue_move": + if isinstance(payload, Move): + self.move_queue.append(payload) + self.state.update_activity() + duration = getattr(payload, "duration", None) + if duration is not None: + try: + duration_str = f"{float(duration):.2f}" + except (TypeError, ValueError): + duration_str = str(duration) + else: + duration_str = "?" + logger.debug( + "Queued move with duration %ss, queue size: %s", + duration_str, + len(self.move_queue), + ) + else: + logger.warning("Ignored queue_move command with invalid payload: %s", payload) + elif command == "clear_queue": + self.move_queue.clear() + self.state.current_move = None + self.state.move_start_time = None + self._breathing_active = False + logger.info("Cleared move queue and stopped current move") + elif command == "set_moving_state": + try: + duration = float(payload) + except (TypeError, ValueError): + logger.warning("Invalid moving state duration: %s", payload) + return + self.state.update_activity() + elif command == "mark_activity": + self.state.update_activity() + elif command == "set_listening": + desired_state = bool(payload) + now = self._now() + if now - self._last_listening_toggle_time < self._listening_debounce_s: + return + self._last_listening_toggle_time = now + + if self._is_listening == desired_state: + return + + self._is_listening = desired_state + self._last_listening_blend_time = now + if desired_state: + # Freeze: snapshot current commanded antennas and reset blend + self._listening_antennas = ( + float(self._last_commanded_pose[1][0]), + float(self._last_commanded_pose[1][1]), + ) + self._antenna_unfreeze_blend = 0.0 + else: + # Unfreeze: restart blending from frozen pose + self._antenna_unfreeze_blend = 0.0 + self.state.update_activity() + else: + logger.warning("Unknown command received by MovementManager: %s", command) + + def _publish_shared_state(self) -> None: + """Expose idle-related state for external threads.""" + with self._shared_state_lock: + self._shared_last_activity_time = self.state.last_activity_time + self._shared_is_listening = self._is_listening + + def _manage_move_queue(self, current_time: float) -> None: + """Manage the primary move queue (sequential execution).""" + if self.state.current_move is None or ( + self.state.move_start_time is not None + and current_time - self.state.move_start_time >= self.state.current_move.duration + ): + self.state.current_move = None + self.state.move_start_time = None + + if self.move_queue: + self.state.current_move = self.move_queue.popleft() + self.state.move_start_time = current_time + # Any real move cancels breathing mode flag + self._breathing_active = isinstance(self.state.current_move, BreathingMove) + logger.debug(f"Starting new move, duration: {self.state.current_move.duration}s") + + def _manage_breathing(self, current_time: float) -> None: + """Manage automatic breathing when idle.""" + if ( + self.state.current_move is None + and not self.move_queue + and not self._is_listening + and not self._breathing_active + ): + idle_for = current_time - self.state.last_activity_time + if idle_for >= self.idle_inactivity_delay: + try: + # These 2 functions return the latest available sensor data from the robot, but don't perform I/O synchronously. + # Therefore, we accept calling them inside the control loop. + _, current_antennas = self.current_robot.get_current_joint_positions() + current_head_pose = self.current_robot.get_current_head_pose() + + self._breathing_active = True + self.state.update_activity() + + breathing_move = BreathingMove( + interpolation_start_pose=current_head_pose, + interpolation_start_antennas=current_antennas, + interpolation_duration=1.0, + ) + self.move_queue.append(breathing_move) + logger.debug("Started breathing after %.1fs of inactivity", idle_for) + except Exception as e: + self._breathing_active = False + logger.error("Failed to start breathing: %s", e) + + if isinstance(self.state.current_move, BreathingMove) and self.move_queue: + self.state.current_move = None + self.state.move_start_time = None + self._breathing_active = False + logger.debug("Stopping breathing due to new move activity") + + if self.state.current_move is not None and not isinstance(self.state.current_move, BreathingMove): + self._breathing_active = False + + def _get_primary_pose(self, current_time: float) -> FullBodyPose: + """Get the primary full body pose from current move or neutral.""" + # When a primary move is playing, sample it and cache the resulting pose + if self.state.current_move is not None and self.state.move_start_time is not None: + move_time = current_time - self.state.move_start_time + head, antennas, body_yaw = self.state.current_move.evaluate(move_time) + + if head is None: + head = create_head_pose(0, 0, 0, 0, 0, 0, degrees=True) + if antennas is None: + antennas = np.array([0.0, 0.0]) + if body_yaw is None: + body_yaw = 0.0 + + antennas_tuple = (float(antennas[0]), float(antennas[1])) + head_copy = head.copy() + primary_full_body_pose = ( + head_copy, + antennas_tuple, + float(body_yaw), + ) + + self.state.last_primary_pose = clone_full_body_pose(primary_full_body_pose) + # Otherwise reuse the last primary pose so we avoid jumps between moves + elif self.state.last_primary_pose is not None: + primary_full_body_pose = clone_full_body_pose(self.state.last_primary_pose) + else: + neutral_head_pose = create_head_pose(0, 0, 0, 0, 0, 0, degrees=True) + primary_full_body_pose = (neutral_head_pose, (0.0, 0.0), 0.0) + self.state.last_primary_pose = clone_full_body_pose(primary_full_body_pose) + + return primary_full_body_pose + + def _get_secondary_pose(self) -> FullBodyPose: + """Get the secondary full body pose from speech and face tracking offsets.""" + # Combine speech sway offsets + face tracking offsets for secondary pose + secondary_offsets = [ + self.state.speech_offsets[0] + self.state.face_tracking_offsets[0], + self.state.speech_offsets[1] + self.state.face_tracking_offsets[1], + self.state.speech_offsets[2] + self.state.face_tracking_offsets[2], + self.state.speech_offsets[3] + self.state.face_tracking_offsets[3], + self.state.speech_offsets[4] + self.state.face_tracking_offsets[4], + self.state.speech_offsets[5] + self.state.face_tracking_offsets[5], + ] + + secondary_head_pose = create_head_pose( + x=secondary_offsets[0], + y=secondary_offsets[1], + z=secondary_offsets[2], + roll=secondary_offsets[3], + pitch=secondary_offsets[4], + yaw=secondary_offsets[5], + degrees=False, + mm=False, + ) + return (secondary_head_pose, (0.0, 0.0), 0.0) + + def _compose_full_body_pose(self, current_time: float) -> FullBodyPose: + """Compose primary and secondary poses into a single command pose.""" + primary = self._get_primary_pose(current_time) + secondary = self._get_secondary_pose() + return combine_full_body(primary, secondary) + + def _update_primary_motion(self, current_time: float) -> None: + """Advance queue state and idle behaviours for this tick.""" + self._manage_move_queue(current_time) + self._manage_breathing(current_time) + + def _calculate_blended_antennas(self, target_antennas: Tuple[float, float]) -> Tuple[float, float]: + """Blend target antennas with listening freeze state and update blending.""" + now = self._now() + listening = self._is_listening + listening_antennas = self._listening_antennas + blend = self._antenna_unfreeze_blend + blend_duration = self._antenna_blend_duration + last_update = self._last_listening_blend_time + self._last_listening_blend_time = now + + if listening: + antennas_cmd = listening_antennas + new_blend = 0.0 + else: + dt = max(0.0, now - last_update) + if blend_duration <= 0: + new_blend = 1.0 + else: + new_blend = min(1.0, blend + dt / blend_duration) + antennas_cmd = ( + listening_antennas[0] * (1.0 - new_blend) + target_antennas[0] * new_blend, + listening_antennas[1] * (1.0 - new_blend) + target_antennas[1] * new_blend, + ) + + if listening: + self._antenna_unfreeze_blend = 0.0 + else: + self._antenna_unfreeze_blend = new_blend + if new_blend >= 1.0: + self._listening_antennas = ( + float(target_antennas[0]), + float(target_antennas[1]), + ) + + return antennas_cmd + + def _issue_control_command(self, head: NDArray[np.float32], antennas: Tuple[float, float], body_yaw: float) -> None: + """Send the fused pose to the robot with throttled error logging.""" + try: + self.current_robot.set_target(head=head, antennas=antennas, body_yaw=body_yaw) + except Exception as e: + now = self._now() + if now - self._last_set_target_err >= self._set_target_err_interval: + msg = f"Failed to set robot target: {e}" + if self._set_target_err_suppressed: + msg += f" (suppressed {self._set_target_err_suppressed} repeats)" + self._set_target_err_suppressed = 0 + logger.error(msg) + self._last_set_target_err = now + else: + self._set_target_err_suppressed += 1 + else: + with self._status_lock: + self._last_commanded_pose = clone_full_body_pose((head, antennas, body_yaw)) + + def _update_frequency_stats( + self, loop_start: float, prev_loop_start: float, stats: LoopFrequencyStats, + ) -> LoopFrequencyStats: + """Update frequency statistics based on the current loop start time.""" + period = loop_start - prev_loop_start + if period > 0: + stats.last_freq = 1.0 / period + stats.count += 1 + delta = stats.last_freq - stats.mean + stats.mean += delta / stats.count + stats.m2 += delta * (stats.last_freq - stats.mean) + stats.min_freq = min(stats.min_freq, stats.last_freq) + return stats + + def _schedule_next_tick(self, loop_start: float, stats: LoopFrequencyStats) -> Tuple[float, LoopFrequencyStats]: + """Compute sleep time to maintain target frequency and update potential freq.""" + computation_time = self._now() - loop_start + stats.potential_freq = 1.0 / computation_time if computation_time > 0 else float("inf") + sleep_time = max(0.0, self.target_period - computation_time) + return sleep_time, stats + + def _record_frequency_snapshot(self, stats: LoopFrequencyStats) -> None: + """Store a thread-safe snapshot of current frequency statistics.""" + with self._status_lock: + self._freq_snapshot = LoopFrequencyStats( + mean=stats.mean, + m2=stats.m2, + min_freq=stats.min_freq, + count=stats.count, + last_freq=stats.last_freq, + potential_freq=stats.potential_freq, + ) + + def _maybe_log_frequency(self, loop_count: int, print_interval_loops: int, stats: LoopFrequencyStats) -> None: + """Emit frequency telemetry when enough loops have elapsed.""" + if loop_count % print_interval_loops != 0 or stats.count == 0: + return + + variance = stats.m2 / stats.count if stats.count > 0 else 0.0 + lowest = stats.min_freq if stats.min_freq != float("inf") else 0.0 + logger.debug( + "Loop freq - avg: %.2fHz, variance: %.4f, min: %.2fHz, last: %.2fHz, potential: %.2fHz, target: %.1fHz", + stats.mean, + variance, + lowest, + stats.last_freq, + stats.potential_freq, + self.target_frequency, + ) + stats.reset() + + def _update_face_tracking(self, current_time: float) -> None: + """Get face tracking offsets from camera worker thread.""" + if self.camera_worker is not None: + # Get face tracking offsets from camera worker thread + offsets = self.camera_worker.get_face_tracking_offsets() + self.state.face_tracking_offsets = offsets + else: + # No camera worker, use neutral offsets + self.state.face_tracking_offsets = (0.0, 0.0, 0.0, 0.0, 0.0, 0.0) + + def start(self) -> None: + """Start the worker thread that drives the 100 Hz control loop.""" + if self._thread is not None and self._thread.is_alive(): + logger.warning("Move worker already running; start() ignored") + return + self._stop_event.clear() + self._thread = threading.Thread(target=self.working_loop, daemon=True) + self._thread.start() + logger.debug("Move worker started") + + def stop(self) -> None: + """Request the worker thread to stop and wait for it to exit. + + Before stopping, resets the robot to a neutral position. + """ + if self._thread is None or not self._thread.is_alive(): + logger.debug("Move worker not running; stop() ignored") + return + + logger.info("Stopping movement manager and resetting to neutral position...") + + # Clear any queued moves and stop current move + self.clear_move_queue() + + # Stop the worker thread first so it doesn't interfere + self._stop_event.set() + if self._thread is not None: + self._thread.join() + self._thread = None + logger.debug("Move worker stopped") + + # Reset to neutral position using goto_target (same approach as wake_up) + try: + neutral_head_pose = create_head_pose(0, 0, 0, 0, 0, 0, degrees=True) + neutral_antennas = [0.0, 0.0] + neutral_body_yaw = 0.0 + + # Use goto_target directly on the robot + self.current_robot.goto_target( + head=neutral_head_pose, + antennas=neutral_antennas, + duration=2.0, + body_yaw=neutral_body_yaw, + ) + + logger.info("Reset to neutral position completed") + + except Exception as e: + logger.error(f"Failed to reset to neutral position: {e}") + + def get_status(self) -> Dict[str, Any]: + """Return a lightweight status snapshot for observability.""" + with self._status_lock: + pose_snapshot = clone_full_body_pose(self._last_commanded_pose) + freq_snapshot = LoopFrequencyStats( + mean=self._freq_snapshot.mean, + m2=self._freq_snapshot.m2, + min_freq=self._freq_snapshot.min_freq, + count=self._freq_snapshot.count, + last_freq=self._freq_snapshot.last_freq, + potential_freq=self._freq_snapshot.potential_freq, + ) + + head_matrix = pose_snapshot[0].tolist() if pose_snapshot else None + antennas = pose_snapshot[1] if pose_snapshot else None + body_yaw = pose_snapshot[2] if pose_snapshot else None + + return { + "queue_size": len(self.move_queue), + "is_listening": self._is_listening, + "breathing_active": self._breathing_active, + "last_commanded_pose": { + "head": head_matrix, + "antennas": antennas, + "body_yaw": body_yaw, + }, + "loop_frequency": { + "last": freq_snapshot.last_freq, + "mean": freq_snapshot.mean, + "min": freq_snapshot.min_freq, + "potential": freq_snapshot.potential_freq, + "samples": freq_snapshot.count, + }, + } + + def working_loop(self) -> None: + """Control loop main movements - reproduces main_works.py control architecture. + + Single set_target() call with pose fusion. + """ + logger.debug("Starting enhanced movement control loop (100Hz)") + + loop_count = 0 + prev_loop_start = self._now() + print_interval_loops = max(1, int(self.target_frequency * 2)) + freq_stats = self._freq_stats + + while not self._stop_event.is_set(): + loop_start = self._now() + loop_count += 1 + + if loop_count > 1: + freq_stats = self._update_frequency_stats(loop_start, prev_loop_start, freq_stats) + prev_loop_start = loop_start + + # 1) Poll external commands and apply pending offsets (atomic snapshot) + self._poll_signals(loop_start) + + # 2) Manage the primary move queue (start new move, end finished move, breathing) + self._update_primary_motion(loop_start) + + # 3) Update vision-based secondary offsets + self._update_face_tracking(loop_start) + + # 4) Build primary and secondary full-body poses, then fuse them + head, antennas, body_yaw = self._compose_full_body_pose(loop_start) + + # 5) Apply listening antenna freeze or blend-back + antennas_cmd = self._calculate_blended_antennas(antennas) + + # 6) Single set_target call - the only control point + self._issue_control_command(head, antennas_cmd, body_yaw) + + # 7) Adaptive sleep to align to next tick, then publish shared state + sleep_time, freq_stats = self._schedule_next_tick(loop_start, freq_stats) + self._publish_shared_state() + self._record_frequency_snapshot(freq_stats) + + # 8) Periodic telemetry on loop frequency + self._maybe_log_frequency(loop_count, print_interval_loops, freq_stats) + + if sleep_time > 0: + time.sleep(sleep_time) + + logger.debug("Movement control loop stopped") diff --git a/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/openai_realtime.py b/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/openai_realtime.py new file mode 100644 index 00000000..c43d6172 --- /dev/null +++ b/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/openai_realtime.py @@ -0,0 +1,811 @@ +import json +import uuid +import base64 +import random +import asyncio +import logging +from typing import Any, Final, Tuple, Literal, Optional +from pathlib import Path +from datetime import datetime + +import cv2 +import numpy as np +import gradio as gr +from openai import AsyncOpenAI +from fastrtc import AdditionalOutputs, AsyncStreamHandler, wait_for_item, audio_to_int16 +from numpy.typing import NDArray +from scipy.signal import resample +from websockets.exceptions import ConnectionClosedError + +from reachy_mini_conversation_app.config import LOCKED_PROFILE, config +from reachy_mini_conversation_app.prompts import get_session_voice, get_session_instructions +from reachy_mini_conversation_app.tools.core_tools import ( + ToolDependencies, + get_tool_specs, +) +from reachy_mini_conversation_app.tools.background_tool_manager import ( + ToolCallRoutine, + ToolNotification, + BackgroundToolManager, +) + + +logger = logging.getLogger(__name__) + +OPEN_AI_INPUT_SAMPLE_RATE: Final[Literal[24000]] = 24000 +OPEN_AI_OUTPUT_SAMPLE_RATE: Final[Literal[24000]] = 24000 + +# Cost tracking from usage data (pricing as of Feb 2026 https://openai.com/api/pricing/) +AUDIO_INPUT_COST_PER_1M = 32.0 +AUDIO_OUTPUT_COST_PER_1M = 64.0 +TEXT_INPUT_COST_PER_1M = 4.0 +TEXT_OUTPUT_COST_PER_1M = 16.0 +IMAGE_INPUT_COST_PER_1M = 5.0 + +_RESPONSE_DONE_TIMEOUT: Final[float] = 30.0 + + +def _compute_response_cost(usage: Any) -> float: + """Compute dollar cost from a response usage object.""" + inp = getattr(usage, "input_token_details", None) + out = getattr(usage, "output_token_details", None) + cost = 0.0 + if inp: + cost += (getattr(inp, "audio_tokens", 0) or 0) * AUDIO_INPUT_COST_PER_1M / 1e6 + cost += (getattr(inp, "text_tokens", 0) or 0) * TEXT_INPUT_COST_PER_1M / 1e6 + cost += (getattr(inp, "image_tokens", 0) or 0) * IMAGE_INPUT_COST_PER_1M / 1e6 + if out: + cost += (getattr(out, "audio_tokens", 0) or 0) * AUDIO_OUTPUT_COST_PER_1M / 1e6 + cost += (getattr(out, "text_tokens", 0) or 0) * TEXT_OUTPUT_COST_PER_1M / 1e6 + return cost + + +class OpenaiRealtimeHandler(AsyncStreamHandler): + """An OpenAI realtime handler for fastrtc Stream.""" + + def __init__(self, deps: ToolDependencies, gradio_mode: bool = False, instance_path: Optional[str] = None): + """Initialize the handler.""" + super().__init__( + expected_layout="mono", + output_sample_rate=OPEN_AI_OUTPUT_SAMPLE_RATE, + input_sample_rate=OPEN_AI_INPUT_SAMPLE_RATE, + ) + + # Override typing of the sample rates to match OpenAI's requirements + self.output_sample_rate: Literal[24000] = self.output_sample_rate + self.input_sample_rate: Literal[24000] = self.input_sample_rate + + self.deps = deps + + # Override type annotations for OpenAI strict typing (only for values used in API) + self.output_sample_rate = OPEN_AI_OUTPUT_SAMPLE_RATE + self.input_sample_rate = OPEN_AI_INPUT_SAMPLE_RATE + + self.connection: Any = None + self.output_queue: "asyncio.Queue[Tuple[int, NDArray[np.int16]] | AdditionalOutputs]" = asyncio.Queue() + + self.last_activity_time = asyncio.get_event_loop().time() + self.start_time = asyncio.get_event_loop().time() + self.is_idle_tool_call = False + self.gradio_mode = gradio_mode + self.instance_path = instance_path + # Track how the API key was provided (env vs textbox) and its value + self._key_source: Literal["env", "textbox"] = "env" + self._provided_api_key: str | None = None + + # Debouncing for partial transcripts + self.partial_transcript_task: asyncio.Task[None] | None = None + self.partial_transcript_sequence: int = 0 # sequence counter to prevent stale emissions + self.partial_debounce_delay = 0.5 # seconds + + # Internal lifecycle flags + self._shutdown_requested: bool = False + self._connected_event: asyncio.Event = asyncio.Event() + + # Background tool manager + self.tool_manager = BackgroundToolManager() + + # Cost tracking + self.cumulative_cost: float = 0.0 + + # Response-in-progress guard: the Realtime API only allows one active + # response per conversation at a time. A dedicated worker task + # (_response_sender_loop) dequeues and sends one request at a time + self._pending_responses: asyncio.Queue[dict[str, Any]] = asyncio.Queue() + self._response_done_event: asyncio.Event = asyncio.Event() + self._response_done_event.set() + self._last_response_rejected: bool = False + + def copy(self) -> "OpenaiRealtimeHandler": + """Create a copy of the handler.""" + return OpenaiRealtimeHandler(self.deps, self.gradio_mode, self.instance_path) + + async def _emit_debounced_partial(self, transcript: str, sequence: int) -> None: + """Emit partial transcript after debounce delay.""" + try: + await asyncio.sleep(self.partial_debounce_delay) + # Only emit if this is still the latest partial (by sequence number) + if self.partial_transcript_sequence == sequence: + await self.output_queue.put(AdditionalOutputs({"role": "user_partial", "content": transcript})) + logger.debug(f"Debounced partial emitted: {transcript}") + except asyncio.CancelledError: + logger.debug("Debounced partial cancelled") + raise + + async def start_up(self) -> None: + """Start the handler with minimal retries on unexpected websocket closure.""" + openai_api_key = config.OPENAI_API_KEY + if self.gradio_mode and not openai_api_key: + # api key was not found in .env or in the environment variables + await self.wait_for_args() # type: ignore[no-untyped-call] + args = list(self.latest_args) + textbox_api_key = args[3] if len(args[3]) > 0 else None + if textbox_api_key is not None: + openai_api_key = textbox_api_key + self._key_source = "textbox" + self._provided_api_key = textbox_api_key + else: + openai_api_key = config.OPENAI_API_KEY + else: + if not openai_api_key or not openai_api_key.strip(): + # In headless console mode, LocalStream now blocks startup until the key is provided. + # However, unit tests may invoke this handler directly with a stubbed client. + # To keep tests hermetic without requiring a real key, fall back to a placeholder. + logger.warning("OPENAI_API_KEY missing. Proceeding with a placeholder (tests/offline).") + openai_api_key = "DUMMY" + + self.client = AsyncOpenAI(api_key=openai_api_key) + + max_attempts = 3 + for attempt in range(1, max_attempts + 1): + try: + await self._run_realtime_session() + # Normal exit from the session, stop retrying + return + except ConnectionClosedError as e: + # Abrupt close (e.g., "no close frame received or sent") → retry + logger.warning("Realtime websocket closed unexpectedly (attempt %d/%d): %s", attempt, max_attempts, e) + if attempt < max_attempts: + # exponential backoff with jitter + base_delay = 2 ** (attempt - 1) # 1s, 2s, 4s, 8s, etc. + jitter = random.uniform(0, 0.5) + delay = base_delay + jitter + logger.info("Retrying in %.1f seconds...", delay) + await asyncio.sleep(delay) + continue + raise + finally: + # never keep a stale reference + self.connection = None + try: + self._connected_event.clear() + except Exception: + pass + + async def _restart_session(self) -> None: + """Force-close the current session and start a fresh one in background. + + Does not block the caller while the new session is establishing. + """ + try: + if self.connection is not None: + try: + await self.connection.close() + except Exception: + pass + finally: + self.connection = None + + # Ensure we have a client (start_up must have run once) + if getattr(self, "client", None) is None: + logger.warning("Cannot restart: OpenAI client not initialized yet.") + return + + # Fire-and-forget new session and wait briefly for connection + try: + self._connected_event.clear() + except Exception: + pass + asyncio.create_task(self._run_realtime_session(), name="openai-realtime-restart") + try: + await asyncio.wait_for(self._connected_event.wait(), timeout=5.0) + logger.info("Realtime session restarted and connected.") + except asyncio.TimeoutError: + logger.warning("Realtime session restart timed out; continuing in background.") + except Exception as e: + logger.warning("_restart_session failed: %s", e) + + async def _safe_response_create(self, **kwargs: Any) -> None: + """Enqueue a response.create() kwargs for the sender worker _response_sender_loop(). + + This method never blocks the caller. + """ + await self._pending_responses.put(kwargs) + + async def _response_sender_loop(self) -> None: + """Dedicated worker that sends ``response.create()`` calls serially. + + This logic was designed to comply with the response.create() docstring specification for event ordering: + https://github.com/openai/openai-python/blob/3e0c05b84a2056870abf3bd6a5e7849020209cc3/src/openai/resources/realtime/realtime.py#L649C1-L651C30 + + For each queued request the worker: + 1. Waits until no response is active (_response_done_event). + 2. Sends response.create(). + 3. Waits for the response cycle to complete (response.done). + 4. If the server rejected with active_response, retries from step 1. + """ + while self.connection: + try: + kwargs = await self._pending_responses.get() + except asyncio.CancelledError: + return + + sent = False + max_retries = 5 + attempts = 0 + while not sent and self.connection and attempts < max_retries: + try: + await asyncio.wait_for(self._response_done_event.wait(), timeout=_RESPONSE_DONE_TIMEOUT) + except asyncio.TimeoutError: + logger.debug("Timed out waiting for previous response to finish; forcing ahead") + self._response_done_event.set() + + if not self.connection: + break + + self._last_response_rejected = False + try: + await self.connection.response.create(**kwargs) + except Exception as e: + logger.debug("_response_sender_loop: send failed: %s", e) + self._response_done_event.set() + break + + try: + await asyncio.wait_for(self._response_done_event.wait(), timeout=_RESPONSE_DONE_TIMEOUT) + except asyncio.TimeoutError: + logger.debug("Timed out waiting for response.done; assuming response completed") + self._response_done_event.set() + break + + # Check if we were rejected + if self._last_response_rejected: + attempts += 1 + if attempts >= max_retries: + logger.debug("response.create rejected %d times; giving up", attempts) + break + logger.debug("response.create was rejected; retrying (%d/%d)", attempts, max_retries) + continue + + sent = True + + async def _handle_tool_result(self, bg_tool: ToolNotification) -> None: + """Process the result of a tool call.""" + if bg_tool.error is not None: + logger.error("Tool '%s' (id=%s) failed with error: %s", bg_tool.tool_name, bg_tool.id, bg_tool.error) + tool_result = {"error": bg_tool.error} + elif bg_tool.result is not None: + tool_result = bg_tool.result + logger.info( + "Tool '%s' (id=%s) executed successfully.", + bg_tool.tool_name, bg_tool.id, + ) + logger.debug("Tool '%s' full result: %s", bg_tool.tool_name, tool_result) + else: + logger.warning("Tool '%s' (id=%s) returned no result and no error", bg_tool.tool_name, bg_tool.id) + tool_result = {"error": "No result returned from tool execution"} + + # Connection may have closed while tool was running + if not self.connection: + logger.warning("Connection closed during tool '%s' (id=%s) execution; cannot send result back", bg_tool.tool_name, bg_tool.id) + return + + try: + # Send the tool result back + if isinstance(bg_tool.id, str): + await self.connection.conversation.item.create( + item={ + "type": "function_call_output", + "call_id": bg_tool.id, + "output": json.dumps(tool_result), + }, + ) + + await self.output_queue.put( + AdditionalOutputs( + { + "role": "assistant", + "content": json.dumps(tool_result), + # Gradio UI metadata.status accept only "pending" and "done". Do not accept bg.tool.status values. + "metadata": { + "title": f"🛠️ Used tool {bg_tool.tool_name}", + "status": "done", + }, + }, + ), + ) + + if bg_tool.tool_name == "camera" and "b64_im" in tool_result: + # use raw base64, don't json.dumps (which adds quotes) + b64_im = tool_result["b64_im"] + if not isinstance(b64_im, str): + logger.warning("Unexpected type for b64_im: %s", type(b64_im)) + b64_im = str(b64_im) + await self.connection.conversation.item.create( + item={ + "type": "message", + "role": "user", + "content": [ + { + "type": "input_image", + "image_url": f"data:image/jpeg;base64,{b64_im}", + }, + ], + }, + ) + logger.info("Added camera image to conversation") + + if self.deps.camera_worker is not None: + np_img = self.deps.camera_worker.get_latest_frame() + if np_img is not None: + # Camera frames are BGR from OpenCV; convert so Gradio displays correct colors. + rgb_frame = cv2.cvtColor(np_img, cv2.COLOR_BGR2RGB) + else: + rgb_frame = None + img = gr.Image(value=rgb_frame) + + await self.output_queue.put( + AdditionalOutputs( + { + "role": "assistant", + "content": img, + }, + ), + ) + + # If this tool call was triggered by an idle signal, don't make the robot speak. + # For other tool calls, let the robot reply out loud. + if not bg_tool.is_idle_tool_call: + await self._safe_response_create( + response={ + "instructions": "Use the tool result just returned and answer concisely in speech.", + }, + ) + + # Re-synchronize the head wobble after a tool call that may have taken some time + if self.deps.head_wobbler is not None: + self.deps.head_wobbler.reset() + + except ConnectionClosedError: + logger.warning("Connection closed while sending tool result") + self.connection = None + self._response_done_event.set() + + async def _run_realtime_session(self) -> None: + """Establish and manage a single realtime session.""" + async with self.client.realtime.connect(model=config.MODEL_NAME) as conn: + try: + await conn.session.update( + session={ + "type": "realtime", + "instructions": get_session_instructions(), + "audio": { + "input": { + "format": { + "type": "audio/pcm", + "rate": self.input_sample_rate, + }, + "transcription": {"model": "gpt-4o-transcribe", "language": "en"}, + "turn_detection": { + "type": "server_vad", + "interrupt_response": True, + }, + }, + "output": { + "format": { + "type": "audio/pcm", + "rate": self.output_sample_rate, + }, + "voice": get_session_voice(), + }, + }, + "tools": get_tool_specs(), # type: ignore[typeddict-item] + "tool_choice": "auto", + }, + ) + logger.info( + "Realtime session initialized with locked_profile=%r voice=%r", + LOCKED_PROFILE, + get_session_voice(), + ) + # If we reached here, the session update succeeded which implies the API key worked. + # Persist the key to a newly created .env (copied from .env.example) if needed. + self._persist_api_key_if_needed() + except Exception: + logger.exception("Realtime session.update failed; aborting startup") + return + + logger.info("Realtime session updated successfully") + + # Manage event received from the openai server + self.connection = conn + try: + self._connected_event.set() + except Exception: + pass + + + response_sender_task: asyncio.Task[None] | None = None + try: + # Start the background tool manager + self.tool_manager.start_up(tool_callbacks=[self._handle_tool_result]) + + # Start the response sender worker + response_sender_task = asyncio.create_task( + self._response_sender_loop(), name="response-sender" + ) + + async for event in self.connection: + logger.debug(f"OpenAI event: {event.type}") + if event.type == "input_audio_buffer.speech_started": + if hasattr(self, "_clear_queue") and callable(self._clear_queue): + self._clear_queue() + if self.deps.head_wobbler is not None: + self.deps.head_wobbler.reset() + self.deps.movement_manager.set_listening(True) + logger.debug("User speech started") + + if event.type == "input_audio_buffer.speech_stopped": + self.deps.movement_manager.set_listening(False) + logger.debug("User speech stopped - server will auto-commit with VAD") + + if event.type in ( + "response.audio.done", + "response.output_audio.done", + "response.audio.completed", + "response.completed", + ): + logger.debug("response completed") + + if event.type == "response.created": + self._response_done_event.clear() + logger.debug("Response created (active)") + + if event.type == "response.done": + # Doesn't mean the audio is done playing + self._response_done_event.set() + logger.debug("Response done") + + response = getattr(event, "response", None) + usage = getattr(response, "usage", None) if response else None + if usage: + cost = _compute_response_cost(usage) + self.cumulative_cost += cost + logger.debug("Cost: $%.4f | Cumulative: $%.4f", cost, self.cumulative_cost) + else: + logger.warning("No usage data available for cost tracking") + + # Handle partial transcription (user speaking in real-time) + if event.type == "conversation.item.input_audio_transcription.partial": + logger.debug(f"User partial transcript: {event.transcript}") + + # Increment sequence + self.partial_transcript_sequence += 1 + current_sequence = self.partial_transcript_sequence + + # Cancel previous debounce task if it exists + if self.partial_transcript_task and not self.partial_transcript_task.done(): + self.partial_transcript_task.cancel() + try: + await self.partial_transcript_task + except asyncio.CancelledError: + pass + + # Start new debounce timer with sequence number + self.partial_transcript_task = asyncio.create_task( + self._emit_debounced_partial(event.transcript, current_sequence) + ) + + # Handle completed transcription (user finished speaking) + if event.type == "conversation.item.input_audio_transcription.completed": + logger.debug(f"User transcript: {event.transcript}") + + # Cancel any pending partial emission + if self.partial_transcript_task and not self.partial_transcript_task.done(): + self.partial_transcript_task.cancel() + try: + await self.partial_transcript_task + except asyncio.CancelledError: + pass + + await self.output_queue.put(AdditionalOutputs({"role": "user", "content": event.transcript})) + + # Handle assistant transcription + if event.type in ("response.audio_transcript.done", "response.output_audio_transcript.done"): + logger.debug(f"Assistant transcript: {event.transcript}") + await self.output_queue.put(AdditionalOutputs({"role": "assistant", "content": event.transcript})) + + # Handle audio delta + if event.type in ("response.audio.delta", "response.output_audio.delta"): + if self.deps.head_wobbler is not None: + self.deps.head_wobbler.feed(event.delta) + self.last_activity_time = asyncio.get_event_loop().time() + logger.debug("last activity time updated to %s", self.last_activity_time) + await self.output_queue.put( + ( + self.output_sample_rate, + np.frombuffer(base64.b64decode(event.delta), dtype=np.int16).reshape(1, -1), + ), + ) + + # ---- tool-calling plumbing ---- + if event.type == "response.function_call_arguments.done": + tool_name = getattr(event, "name", None) + args_json_str = getattr(event, "arguments", None) + call_id: str = str(getattr(event, "call_id", uuid.uuid4())) + + logger.info( + "Tool call received — tool_name=%r, call_id=%s, is_idle=%s, args=%s", + tool_name, call_id, self.is_idle_tool_call, args_json_str, + ) + + if not isinstance(tool_name, str) or not isinstance(args_json_str, str): + logger.error( + "Invalid tool call: tool_name=%s (type=%s), args=%s (type=%s), call_id=%s", + tool_name, type(tool_name).__name__, + args_json_str, type(args_json_str).__name__, + call_id, + ) + continue + + bg_tool = await self.tool_manager.start_tool( + call_id=call_id, + tool_call_routine=ToolCallRoutine( + tool_name=tool_name, + args_json_str=args_json_str, + deps=self.deps, + ), + is_idle_tool_call=self.is_idle_tool_call, + ) + + await self.output_queue.put( + AdditionalOutputs( + { + "role": "assistant", + "content": f"🛠️ Used tool {tool_name} with args {args_json_str}. The tool is now running. Tool ID: {bg_tool.tool_id}", + }, + ), + ) + + if self.is_idle_tool_call: + self.is_idle_tool_call = False + else: + await self._safe_response_create( + response={ + "instructions": "Notify what the tool has been running giving meaningful information about the task", + }, + ) + + logger.info("Started background tool: %s (id=%s, call_id=%s)", tool_name, bg_tool.tool_id, call_id) + + # server error + if event.type == "error": + err = getattr(event, "error", None) + msg = getattr(err, "message", str(err) if err else "unknown error") + code = getattr(err, "code", "") + + if code == "conversation_already_has_active_response": + # response.create was rejected. The sender worker + # is waiting on _response_done_event; when the active + # response finishes it will wake up and see this flag. + self._last_response_rejected = True + logger.debug("response.create rejected; worker will retry after active response finishes") + else: + logger.error("Realtime error [%s]: %s (raw=%s)", code, msg, err) + + # Only show user-facing errors, not internal state errors + if code not in ("input_audio_buffer_commit_empty",): + await self.output_queue.put( + AdditionalOutputs({"role": "assistant", "content": f"[error] {msg}"}) + ) + finally: + # Stop the response sender worker. + if response_sender_task is not None: + response_sender_task.cancel() + try: + await response_sender_task + except asyncio.CancelledError: + pass + + # Stop background tool manager tasks (listener + cleanup) in all paths. + await self.tool_manager.shutdown() + + # Microphone receive + async def receive(self, frame: Tuple[int, NDArray[np.int16]]) -> None: + """Receive audio frame from the microphone and send it to the OpenAI server. + + Handles both mono and stereo audio formats, converting to the expected + mono format for OpenAI's API. Resamples if the input sample rate differs + from the expected rate. + + Args: + frame: A tuple containing (sample_rate, audio_data). + + """ + if not self.connection: + return + + input_sample_rate, audio_frame = frame + + # Reshape if needed + if audio_frame.ndim == 2: + # Scipy channels last convention + if audio_frame.shape[1] > audio_frame.shape[0]: + audio_frame = audio_frame.T + # Multiple channels -> Mono channel + if audio_frame.shape[1] > 1: + audio_frame = audio_frame[:, 0] + + # Resample if needed + if self.input_sample_rate != input_sample_rate: + audio_frame = resample(audio_frame, int(len(audio_frame) * self.input_sample_rate / input_sample_rate)) + + # Cast if needed + audio_frame = audio_to_int16(audio_frame) + + # Send to OpenAI (guard against races during reconnect) + try: + audio_message = base64.b64encode(audio_frame.tobytes()).decode("utf-8") + await self.connection.input_audio_buffer.append(audio=audio_message) + except Exception as e: + logger.debug("Dropping audio frame: connection not ready (%s)", e) + return + + async def emit(self) -> Tuple[int, NDArray[np.int16]] | AdditionalOutputs | None: + """Emit audio frame to be played by the speaker.""" + # sends to the stream the stuff put in the output queue by the openai event handler + # This is called periodically by the fastrtc Stream + + # Handle idle + idle_duration = asyncio.get_event_loop().time() - self.last_activity_time + if idle_duration > 15.0 and self.deps.movement_manager.is_idle(): + try: + await self.send_idle_signal(idle_duration) + except Exception as e: + logger.warning("Idle signal skipped (connection closed?): %s", e) + return None + + self.last_activity_time = asyncio.get_event_loop().time() # avoid repeated resets + + return await wait_for_item(self.output_queue) # type: ignore[no-any-return] + + async def shutdown(self) -> None: + """Shutdown the handler.""" + self._shutdown_requested = True + + # Unblock the response sender worker so it can exit + self._response_done_event.set() + + # Stop background tool manager tasks (listener + cleanup) + await self.tool_manager.shutdown() + + # Cancel any pending debounce task + if self.partial_transcript_task and not self.partial_transcript_task.done(): + self.partial_transcript_task.cancel() + try: + await self.partial_transcript_task + except asyncio.CancelledError: + pass + + if self.connection: + try: + await self.connection.close() + except ConnectionClosedError as e: + logger.debug(f"Connection already closed during shutdown: {e}") + except Exception as e: + logger.debug(f"connection.close() ignored: {e}") + finally: + self.connection = None + + # Clear any remaining items in the output queue + while not self.output_queue.empty(): + try: + self.output_queue.get_nowait() + except asyncio.QueueEmpty: + break + + def format_timestamp(self) -> str: + """Format current timestamp with date, time, and elapsed seconds.""" + loop_time = asyncio.get_event_loop().time() # monotonic + elapsed_seconds = loop_time - self.start_time + dt = datetime.now() # wall-clock + return f"[{dt.strftime('%Y-%m-%d %H:%M:%S')} | +{elapsed_seconds:.1f}s]" + + async def send_idle_signal(self, idle_duration: float) -> None: + """Send an idle signal to the openai server.""" + logger.debug("Sending idle signal") + self.is_idle_tool_call = True + timestamp_msg = f"[Idle time update: {self.format_timestamp()} - No activity for {idle_duration:.1f}s] You've been idle for a while. Feel free to get creative - dance, show an emotion, look around, do nothing, or just be yourself!" + if not self.connection: + logger.debug("No connection, cannot send idle signal") + return + await self.connection.conversation.item.create( + item={ + "type": "message", + "role": "user", + "content": [{"type": "input_text", "text": timestamp_msg}], + }, + ) + await self._safe_response_create( + response={ + "instructions": "You MUST respond with function calls only - no speech or text. Choose appropriate actions for idle behavior.", + "tool_choice": "required", + }, + ) + + def _persist_api_key_if_needed(self) -> None: + """Persist the API key into `.env` inside `instance_path/` when appropriate. + + - Only runs in Gradio mode when key came from the textbox and is non-empty. + - Only saves if `self.instance_path` is not None. + - Writes `.env` to `instance_path/.env` (does not overwrite if it already exists). + - If `instance_path/.env.example` exists, copies its contents while overriding OPENAI_API_KEY. + """ + try: + if not self.gradio_mode: + logger.warning("Not in Gradio mode; skipping API key persistence.") + return + + if self._key_source != "textbox": + logger.info("API key not provided via textbox; skipping persistence.") + return + + key = (self._provided_api_key or "").strip() + if not key: + logger.warning("No API key provided via textbox; skipping persistence.") + return + if self.instance_path is None: + logger.warning("Instance path is None; cannot persist API key.") + return + + # Update the current process environment for downstream consumers + try: + import os + + os.environ["OPENAI_API_KEY"] = key + except Exception: # best-effort + pass + + target_dir = Path(self.instance_path) + env_path = target_dir / ".env" + if env_path.exists(): + # Respect existing user configuration + logger.info(".env already exists at %s; not overwriting.", env_path) + return + + example_path = target_dir / ".env.example" + content_lines: list[str] = [] + if example_path.exists(): + try: + content = example_path.read_text(encoding="utf-8") + content_lines = content.splitlines() + except Exception as e: + logger.warning("Failed to read .env.example at %s: %s", example_path, e) + + # Replace or append the OPENAI_API_KEY line + replaced = False + for i, line in enumerate(content_lines): + if line.strip().startswith("OPENAI_API_KEY="): + content_lines[i] = f"OPENAI_API_KEY={key}" + replaced = True + break + if not replaced: + content_lines.append(f"OPENAI_API_KEY={key}") + + # Ensure file ends with newline + final_text = "\n".join(content_lines) + "\n" + env_path.write_text(final_text, encoding="utf-8") + logger.info("Created %s and stored OPENAI_API_KEY for future runs.", env_path) + except Exception as e: + # Never crash the app for QoL persistence; just log. + logger.warning("Could not persist OPENAI_API_KEY to .env: %s", e) diff --git a/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/profiles/__init__.py b/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/profiles/__init__.py new file mode 100644 index 00000000..f2f5f454 --- /dev/null +++ b/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/profiles/__init__.py @@ -0,0 +1 @@ +"""Profiles for Reachy Mini conversation app.""" diff --git a/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/profiles/_reachy_mini_conversation_app_locked_profile/__init__.py b/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/profiles/_reachy_mini_conversation_app_locked_profile/__init__.py new file mode 100644 index 00000000..2657e8cf --- /dev/null +++ b/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/profiles/_reachy_mini_conversation_app_locked_profile/__init__.py @@ -0,0 +1 @@ +"""Locked Reachy OpenShell profile.""" diff --git a/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/profiles/_reachy_mini_conversation_app_locked_profile/instructions.txt b/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/profiles/_reachy_mini_conversation_app_locked_profile/instructions.txt new file mode 100644 index 00000000..358102c5 --- /dev/null +++ b/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/profiles/_reachy_mini_conversation_app_locked_profile/instructions.txt @@ -0,0 +1,3 @@ +You are a helpful assistant controlling a Reachy Mini robot for OpenShell research. +Keep responses concise, friendly, and concrete. +Use the sweep_look tool when looking around would help. diff --git a/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/profiles/_reachy_mini_conversation_app_locked_profile/sweep_look.py b/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/profiles/_reachy_mini_conversation_app_locked_profile/sweep_look.py new file mode 100644 index 00000000..f80499d1 --- /dev/null +++ b/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/profiles/_reachy_mini_conversation_app_locked_profile/sweep_look.py @@ -0,0 +1,115 @@ +import logging +from typing import Any, Dict + +import numpy as np + +from reachy_mini.utils import create_head_pose +from reachy_mini_conversation_app.goto_queue_move import GotoQueueMove +from reachy_mini_conversation_app.tools.core_tools import Tool, ToolDependencies + + +logger = logging.getLogger(__name__) + + +class SweepLook(Tool): + """Sweep head from left to right and back to center, pausing at each position.""" + + name = "sweep_look" + description = "Sweep head from left to right while rotating the body, pausing at each extreme, then return to center" + parameters_schema = { + "type": "object", + "properties": {}, + "required": [], + } + + async def __call__(self, deps: ToolDependencies, **kwargs: Any) -> Dict[str, Any]: + """Execute sweep look: left -> hold -> right -> hold -> center.""" + logger.info("Tool call: sweep_look") + + deps.movement_manager.clear_move_queue() + + current_head_pose = deps.reachy_mini.get_current_head_pose() + head_joints, antenna_joints = deps.reachy_mini.get_current_joint_positions() + + current_body_yaw = head_joints[0] + current_antenna1 = antenna_joints[0] + current_antenna2 = antenna_joints[1] + + max_angle = 0.9 * np.pi + transition_duration = 3.0 + hold_duration = 1.0 + + left_head_pose = create_head_pose(0, 0, 0, 0, 0, max_angle, degrees=False) + move_to_left = GotoQueueMove( + target_head_pose=left_head_pose, + start_head_pose=current_head_pose, + target_antennas=(current_antenna1, current_antenna2), + start_antennas=(current_antenna1, current_antenna2), + target_body_yaw=current_body_yaw + max_angle, + start_body_yaw=current_body_yaw, + duration=transition_duration, + ) + + hold_left = GotoQueueMove( + target_head_pose=left_head_pose, + start_head_pose=left_head_pose, + target_antennas=(current_antenna1, current_antenna2), + start_antennas=(current_antenna1, current_antenna2), + target_body_yaw=current_body_yaw + max_angle, + start_body_yaw=current_body_yaw + max_angle, + duration=hold_duration, + ) + + center_head_pose = create_head_pose(0, 0, 0, 0, 0, 0, degrees=False) + return_to_center_from_left = GotoQueueMove( + target_head_pose=center_head_pose, + start_head_pose=left_head_pose, + target_antennas=(current_antenna1, current_antenna2), + start_antennas=(current_antenna1, current_antenna2), + target_body_yaw=current_body_yaw, + start_body_yaw=current_body_yaw + max_angle, + duration=transition_duration, + ) + + right_head_pose = create_head_pose(0, 0, 0, 0, 0, -max_angle, degrees=False) + move_to_right = GotoQueueMove( + target_head_pose=right_head_pose, + start_head_pose=center_head_pose, + target_antennas=(current_antenna1, current_antenna2), + start_antennas=(current_antenna1, current_antenna2), + target_body_yaw=current_body_yaw - max_angle, + start_body_yaw=current_body_yaw, + duration=transition_duration, + ) + + hold_right = GotoQueueMove( + target_head_pose=right_head_pose, + start_head_pose=right_head_pose, + target_antennas=(current_antenna1, current_antenna2), + start_antennas=(current_antenna1, current_antenna2), + target_body_yaw=current_body_yaw - max_angle, + start_body_yaw=current_body_yaw - max_angle, + duration=hold_duration, + ) + + return_to_center_final = GotoQueueMove( + target_head_pose=center_head_pose, + start_head_pose=right_head_pose, + target_antennas=(current_antenna1, current_antenna2), + start_antennas=(current_antenna1, current_antenna2), + target_body_yaw=current_body_yaw, + start_body_yaw=current_body_yaw - max_angle, + duration=transition_duration, + ) + + deps.movement_manager.queue_move(move_to_left) + deps.movement_manager.queue_move(hold_left) + deps.movement_manager.queue_move(return_to_center_from_left) + deps.movement_manager.queue_move(move_to_right) + deps.movement_manager.queue_move(hold_right) + deps.movement_manager.queue_move(return_to_center_final) + + total_duration = transition_duration * 4 + hold_duration * 2 + deps.movement_manager.set_moving_state(total_duration) + + return {"status": f"sweeping look left-right-center, total {total_duration:.1f}s"} diff --git a/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/profiles/_reachy_mini_conversation_app_locked_profile/tools.txt b/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/profiles/_reachy_mini_conversation_app_locked_profile/tools.txt new file mode 100644 index 00000000..d5f05cb2 --- /dev/null +++ b/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/profiles/_reachy_mini_conversation_app_locked_profile/tools.txt @@ -0,0 +1,5 @@ +dance +stop_dance +play_emotion +stop_emotion +sweep_look diff --git a/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/prompts.py b/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/prompts.py new file mode 100644 index 00000000..d174c6b6 --- /dev/null +++ b/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/prompts.py @@ -0,0 +1,47 @@ +import sys +import logging +from pathlib import Path + +from reachy_mini_conversation_app.config import LOCKED_PROFILE, DEFAULT_PROFILES_DIRECTORY + + +logger = logging.getLogger(__name__) + + +INSTRUCTIONS_FILENAME = "instructions.txt" +VOICE_FILENAME = "voice.txt" + + +def _locked_profile_path() -> Path: + return DEFAULT_PROFILES_DIRECTORY / LOCKED_PROFILE + + +def get_session_instructions() -> str: + """Load the locked profile instructions for the realtime session.""" + instructions_file = _locked_profile_path() / INSTRUCTIONS_FILENAME + logger.info("Loading prompt from locked profile '%s'", LOCKED_PROFILE) + + try: + if instructions_file.exists(): + instructions = instructions_file.read_text(encoding="utf-8").strip() + if instructions: + return instructions + logger.error("Locked profile '%s' has empty %s", LOCKED_PROFILE, INSTRUCTIONS_FILENAME) + sys.exit(1) + logger.error("Locked profile '%s' has no %s", LOCKED_PROFILE, INSTRUCTIONS_FILENAME) + sys.exit(1) + except Exception as e: + logger.error("Failed to load instructions from locked profile '%s': %s", LOCKED_PROFILE, e) + sys.exit(1) + + +def get_session_voice(default: str = "cedar") -> str: + """Resolve the locked profile voice.""" + try: + voice_file = _locked_profile_path() / VOICE_FILENAME + if voice_file.exists(): + voice = voice_file.read_text(encoding="utf-8").strip() + return voice or default + except Exception: + pass + return default diff --git a/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/static/index.html b/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/static/index.html new file mode 100644 index 00000000..058cff29 --- /dev/null +++ b/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/static/index.html @@ -0,0 +1,54 @@ + + + + + + Reachy OpenShell - Settings + + + +
    +
    + +

    Loading…

    +
    +
    +
    +
    Headless control
    +

    Reachy OpenShell

    +

    Configure your OpenAI API key for the conversation app.

    +
    + + + + +
    + + + + diff --git a/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/static/main.js b/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/static/main.js new file mode 100644 index 00000000..4932fc8d --- /dev/null +++ b/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/static/main.js @@ -0,0 +1,136 @@ +const sleep = (ms) => new Promise((resolve) => setTimeout(resolve, ms)); + +async function fetchWithTimeout(url, options = {}, timeoutMs = 2000) { + const controller = new AbortController(); + const id = setTimeout(() => controller.abort(), timeoutMs); + try { + return await fetch(url, { ...options, signal: controller.signal }); + } finally { + clearTimeout(id); + } +} + +async function waitForStatus(timeoutMs = 15000) { + const loadingText = document.querySelector("#loading p"); + let attempts = 0; + const deadline = Date.now() + timeoutMs; + while (true) { + attempts += 1; + try { + const url = new URL("/status", window.location.origin); + url.searchParams.set("_", Date.now().toString()); + const resp = await fetchWithTimeout(url, {}, 2000); + if (resp.ok) return await resp.json(); + } catch (e) {} + if (loadingText) { + loadingText.textContent = attempts > 8 ? "Starting backend…" : "Loading…"; + } + if (Date.now() >= deadline) return null; + await sleep(500); + } +} + +async function validateKey(key) { + const body = { openai_api_key: key }; + const resp = await fetch("/validate_api_key", { + method: "POST", + headers: { "Content-Type": "application/json" }, + body: JSON.stringify(body), + }); + const data = await resp.json().catch(() => ({})); + if (!resp.ok) { + throw new Error(data.error || "validation_failed"); + } + return data; +} + +async function saveKey(key) { + const body = { openai_api_key: key }; + const resp = await fetch("/openai_api_key", { + method: "POST", + headers: { "Content-Type": "application/json" }, + body: JSON.stringify(body), + }); + if (!resp.ok) { + const data = await resp.json().catch(() => ({})); + throw new Error(data.error || "save_failed"); + } + return await resp.json(); +} + +function show(el, flag) { + el.classList.toggle("hidden", !flag); +} + +async function init() { + const loading = document.getElementById("loading"); + const statusEl = document.getElementById("status"); + const formPanel = document.getElementById("form-panel"); + const configuredPanel = document.getElementById("configured"); + const saveBtn = document.getElementById("save-btn"); + const changeKeyBtn = document.getElementById("change-key-btn"); + const input = document.getElementById("api-key"); + + show(loading, true); + show(formPanel, false); + show(configuredPanel, false); + + const st = (await waitForStatus()) || { has_key: false }; + + if (st.has_key) { + show(configuredPanel, true); + } else { + show(formPanel, true); + } + show(loading, false); + + changeKeyBtn.addEventListener("click", () => { + show(configuredPanel, false); + show(formPanel, true); + input.value = ""; + statusEl.textContent = ""; + statusEl.className = "status"; + }); + + input.addEventListener("input", () => { + input.classList.remove("error"); + }); + + saveBtn.addEventListener("click", async () => { + const key = input.value.trim(); + if (!key) { + statusEl.textContent = "Please enter a valid key."; + statusEl.className = "status warn"; + input.classList.add("error"); + return; + } + statusEl.textContent = "Validating API key..."; + statusEl.className = "status"; + input.classList.remove("error"); + try { + const validation = await validateKey(key); + if (!validation.valid) { + statusEl.textContent = "Invalid API key. Please check your key and try again."; + statusEl.className = "status error"; + input.classList.add("error"); + return; + } + statusEl.textContent = "Key valid! Saving..."; + statusEl.className = "status ok"; + await saveKey(key); + statusEl.textContent = "Saved. Reloading…"; + statusEl.className = "status ok"; + window.location.reload(); + } catch (e) { + input.classList.add("error"); + if (e.message === "invalid_api_key") { + statusEl.textContent = "Invalid API key. Please check your key and try again."; + } else { + statusEl.textContent = "Failed to validate/save key. Please try again."; + } + statusEl.className = "status error"; + } + }); +} + +window.addEventListener("DOMContentLoaded", init); \ No newline at end of file diff --git a/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/static/style.css b/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/static/style.css new file mode 100644 index 00000000..1f8f0c8f --- /dev/null +++ b/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/static/style.css @@ -0,0 +1,210 @@ +:root { + --bg: #060b1a; + --bg-2: #071023; + --panel: rgba(11, 18, 36, 0.8); + --border: rgba(255, 255, 255, 0.08); + --text: #eaf2ff; + --muted: #9fb6d7; + --ok: #4ce0b3; + --warn: #ffb547; + --error: #ff5c70; + --accent: #45c4ff; + --accent-2: #5ef0c1; + --shadow: 0 20px 70px rgba(0, 0, 0, 0.45); +} + +* { box-sizing: border-box; } +body { + margin: 0; + min-height: 100vh; + font-family: "Space Grotesk", "Inter", "Segoe UI", sans-serif; + background: radial-gradient(circle at 20% 20%, rgba(69, 196, 255, 0.16), transparent 35%), + radial-gradient(circle at 80% 0%, rgba(94, 240, 193, 0.16), transparent 32%), + linear-gradient(135deg, var(--bg), var(--bg-2)); + color: var(--text); +} + +.ambient { + position: fixed; + inset: 0; + background: radial-gradient(circle at 30% 60%, rgba(255, 255, 255, 0.05), transparent 35%), + radial-gradient(circle at 75% 30%, rgba(69, 196, 255, 0.08), transparent 32%); + filter: blur(60px); + z-index: 0; + pointer-events: none; +} + +.loading { + position: fixed; + inset: 0; + background: rgba(5, 10, 24, 0.92); + backdrop-filter: blur(4px); + display: flex; + flex-direction: column; + align-items: center; + justify-content: center; + z-index: 9999; +} +.loading .spinner { + width: 46px; + height: 46px; + border: 4px solid rgba(255,255,255,0.15); + border-top-color: var(--accent); + border-radius: 50%; + animation: spin 1s linear infinite; + margin-bottom: 12px; +} +.loading p { color: var(--muted); margin: 0; letter-spacing: 0.4px; } +@keyframes spin { to { transform: rotate(360deg); } } + +.container { + position: relative; + max-width: 600px; + margin: 10vh auto; + padding: 0 24px 40px; + z-index: 1; +} + +.hero { + margin-bottom: 24px; +} +.hero h1 { + margin: 6px 0 6px; + font-size: 32px; + letter-spacing: -0.4px; +} +.subtitle { + margin: 0; + color: var(--muted); + line-height: 1.5; +} +.pill { + display: inline-flex; + align-items: center; + gap: 6px; + padding: 6px 12px; + border-radius: 999px; + background: rgba(94, 240, 193, 0.1); + color: var(--accent-2); + font-size: 12px; + letter-spacing: 0.3px; + border: 1px solid rgba(94, 240, 193, 0.25); +} + +.panel { + background: var(--panel); + border: 1px solid var(--border); + border-radius: 14px; + padding: 18px 18px 16px; + box-shadow: var(--shadow); + backdrop-filter: blur(10px); + margin-top: 16px; +} +.panel-heading { + display: flex; + align-items: center; + justify-content: space-between; + gap: 12px; + margin-bottom: 8px; +} +.panel-heading h2 { + margin: 2px 0; + font-size: 22px; +} +.eyebrow { + margin: 0; + text-transform: uppercase; + font-size: 11px; + letter-spacing: 0.5px; + color: var(--muted); +} +.muted { color: var(--muted); } +.chip { + display: inline-flex; + align-items: center; + padding: 6px 10px; + border-radius: 999px; + font-size: 12px; + color: var(--text); + background: rgba(255, 255, 255, 0.08); + border: 1px solid var(--border); +} +.chip-ok { + background: rgba(76, 224, 179, 0.15); + color: var(--ok); + border-color: rgba(76, 224, 179, 0.4); +} + +.hidden { display: none; } +label { + display: block; + margin: 8px 0 6px; + font-size: 13px; + color: var(--muted); + letter-spacing: 0.2px; +} +input[type="password"], +input[type="text"] { + width: 100%; + padding: 12px 14px; + border: 1px solid var(--border); + border-radius: 10px; + background: rgba(255, 255, 255, 0.04); + color: var(--text); + transition: border 0.15s ease, box-shadow 0.15s ease; +} +input:focus { + border-color: rgba(94, 240, 193, 0.7); + outline: none; + box-shadow: 0 0 0 3px rgba(94, 240, 193, 0.15); +} +input.error { + border-color: var(--error); + box-shadow: 0 0 0 3px rgba(255, 92, 112, 0.15); +} + +button { + display: inline-flex; + align-items: center; + justify-content: center; + margin-top: 12px; + padding: 11px 16px; + border: none; + border-radius: 10px; + background: linear-gradient(120deg, var(--accent), var(--accent-2)); + color: #031022; + cursor: pointer; + font-weight: 600; + letter-spacing: 0.2px; + box-shadow: 0 14px 40px rgba(69, 196, 255, 0.25); + transition: transform 0.12s ease, filter 0.12s ease, box-shadow 0.12s ease; +} +button:hover { filter: brightness(1.06); transform: translateY(-1px); } +button:active { transform: translateY(0); } +button.ghost { + background: rgba(255, 255, 255, 0.05); + color: var(--text); + box-shadow: none; + border: 1px solid var(--border); +} +button.ghost:hover { border-color: rgba(94, 240, 193, 0.4); } +.actions { + display: flex; + align-items: center; + gap: 12px; + flex-wrap: wrap; +} +.status { + margin: 0; + color: var(--muted); + font-size: 13px; +} +.status.ok { color: var(--ok); } +.status.warn { color: var(--warn); } +.status.error { color: var(--error); } + +@media (max-width: 760px) { + .hero h1 { font-size: 26px; } + button { width: 100%; justify-content: center; } + .actions { flex-direction: column; align-items: flex-start; } +} \ No newline at end of file diff --git a/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/tools/__init__.py b/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/tools/__init__.py new file mode 100644 index 00000000..6bc971c2 --- /dev/null +++ b/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/tools/__init__.py @@ -0,0 +1 @@ +"""Tools loaded by the locked Reachy OpenShell profile.""" diff --git a/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/tools/background_tool_manager.py b/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/tools/background_tool_manager.py new file mode 100644 index 00000000..c7859c81 --- /dev/null +++ b/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/tools/background_tool_manager.py @@ -0,0 +1,412 @@ +"""Background tool orchestrator for non-blocking tool execution. + +Allows tools to run long operations asynchronously while the robot +continues conversing. Tools can be tracked, cancelled, and their +completion is announced vocally via a silent notification queue. +""" + +from __future__ import annotations +import time +import asyncio +import logging +from typing import Any, Dict, Callable, Optional, Coroutine + +from pydantic import Field, BaseModel, PrivateAttr + +from reachy_mini_conversation_app.tools.core_tools import ( + ToolDependencies, + dispatch_tool_call, + dispatch_tool_call_with_manager, +) +from reachy_mini_conversation_app.tools.tool_constants import ToolState, SystemTool + + +logger = logging.getLogger(__name__) + +_SYSTEM_TOOL_NAMES: set[str] = {t.value for t in SystemTool} + +class ToolProgress(BaseModel): + """Progress of a background tool.""" + + """the progress of the tool""" + progress: float = Field(..., ge=0.0, le=1.0) + + """the message of the tool""" + message: Optional[str] = None + + +class ToolCallRoutine(BaseModel): + """Encapsulates an async callable with its arguments for deferred execution.""" + + model_config = {"arbitrary_types_allowed": True} + + """the name of the tool""" + tool_name: str + + """the JSON arguments for the tool call""" + args_json_str: str + + """the dependencies for the tool call""" + deps: "ToolDependencies" + + async def __call__(self, tool_manager: BackgroundToolManager) -> Any: + """Execute the stored callable with its arguments.""" + if self.tool_name in _SYSTEM_TOOL_NAMES: + # For safety purposes, we only allow system tools to be called with the tool manager + return await dispatch_tool_call_with_manager(tool_name=self.tool_name, args_json=self.args_json_str, deps=self.deps, tool_manager=tool_manager) + return await dispatch_tool_call(tool_name=self.tool_name, args_json=self.args_json_str, deps=self.deps) + + +class ToolNotification(BaseModel): + """Notification payload for completed tools.""" + + """the ID of the tool""" + id: str + + """the name of the tool""" + tool_name: str + + """whether the tool call was triggered by an idle signal""" + is_idle_tool_call: bool + + """the status of the tool""" + status: ToolState + + """the result of the tool""" + result: Optional[Dict[str, Any]] = None + + """the error of the tool""" + error: Optional[str] = None + + +class BackgroundTool(ToolNotification): + """Represents a background tool.""" + + """the progress of the tool""" + progress: Optional[ToolProgress] = None + + """the start time of the tool""" + started_at: float = Field(default_factory=time.monotonic) + + """the completion time of the tool""" + completed_at: Optional[float] = None + + """the async tool execution task""" + _task: Optional[asyncio.Task[None]] = PrivateAttr(default=None) + + @property + def tool_id(self) -> str: + """Get the name of the tool.""" + return f"{self.tool_name}-{self.id}-{self.started_at}" + + def get_notification(self) -> ToolNotification: + """Get the notification for the tool.""" + return ToolNotification( + id=self.id, + tool_name=self.tool_name, + is_idle_tool_call=self.is_idle_tool_call, + status=self.status, + result=self.result, + error=self.error, + ) + + +class BackgroundToolManager(BaseModel): + """Manages background tools for non-blocking tool execution. + + Features: + - Start async tools without blocking the conversation + - Track tool status and progress + - Cancel running tools + + """ + + """the dictionary of tools""" + _tools: Dict[str, BackgroundTool] = PrivateAttr(default_factory=dict) + + """the async queue for notifications""" + _notification_queue: asyncio.Queue[ToolNotification] = PrivateAttr(default_factory=asyncio.Queue) + + """the event loop""" + _loop: Optional[asyncio.AbstractEventLoop] = PrivateAttr(default=None) + + """internal lifecycle tasks (notification listener, periodic cleanup)""" + _lifecycle_tasks: list[asyncio.Task[None]] = PrivateAttr(default_factory=list) + + """the maximum duration of a tool execution in seconds (default: 1 day)""" + _max_tool_duration_seconds: float = PrivateAttr(default=86400) + + """the maximum time to keep a completed/failed/cancelled tool in memory (default: 1 hour)""" + _max_tool_memory_seconds: float = PrivateAttr(default=3600) + + def set_loop( + self, + loop: Optional[asyncio.AbstractEventLoop] = None, + ) -> None: + """Set the event loop. + + Args: + loop: The event loop (defaults to current running loop) + + """ + if loop is not None: + self._loop = loop + else: + try: + self._loop = asyncio.get_running_loop() + except RuntimeError: + self._loop = asyncio.new_event_loop() + logger.debug("BackgroundToolManager: event loop set") + + + async def start_tool( + self, + call_id: str, + tool_call_routine: ToolCallRoutine, + is_idle_tool_call: bool, + with_progress: bool = False, + ) -> BackgroundTool: + """Start a new background tool. + + Args: + call_id: The ID of the tool + tool_call_routine: The ToolCallRoutine containing the callable and its arguments + with_progress: Whether to track progress (0.0-1.0) + is_idle_tool_call: Whether the tool call was triggered by an idle signal + + Returns: + BackgroundTool object with tool ID + + """ + tool_name = tool_call_routine.tool_name + id = call_id + bg_tool = BackgroundTool( + id=id, + tool_name=tool_name, + is_idle_tool_call=is_idle_tool_call, + progress=ToolProgress(progress=0.0) if with_progress else None, + status=ToolState.RUNNING, + ) + self._tools[bg_tool.tool_id] = bg_tool + + async_task = asyncio.create_task( + self._run_tool(bg_tool, tool_call_routine), + name=f"bg-{tool_name}-{id}", + ) + bg_tool._task = async_task + + logger.info(f"Started background tool: {bg_tool.tool_name} (id={id})") + + return bg_tool + + async def _run_tool( + self, + bg_tool: BackgroundTool, + tool_call_routine: ToolCallRoutine, + ) -> None: + """Execute the tool and handle completion.""" + result: dict[str, Any] = await tool_call_routine(self) + bg_tool.completed_at = time.monotonic() + error = result.get("error") + + if error is not None: + if error == "Tool cancelled": + bg_tool.status = ToolState.CANCELLED + logger.debug(f"Background tool cancelled: {bg_tool.tool_name} (id={bg_tool.id})") + else: + bg_tool.status = ToolState.FAILED + logger.debug(f"Background tool failed: {bg_tool.tool_name} (id={bg_tool.id}): {bg_tool.error}") + bg_tool.error = result["error"] + + else: + bg_tool.result = result + bg_tool.status = ToolState.COMPLETED + logger.debug(f"Background tool completed: {bg_tool.tool_name} (id={bg_tool.id})") + + await self._notification_queue.put(bg_tool.get_notification()) + logger.debug(f"Queued notification for tool: {bg_tool.tool_name} (id={bg_tool.id})") + + async def update_progress( + self, + tool_id: str, + progress: float, + message: Optional[str] = None, + ) -> bool: + """Update progress for a tool (for tools with with_progress=True). + + Args: + tool_id: The tool ID + progress: Progress value between 0.0 and 1.0 + message: Optional progress message (e.g., "50% downloaded") + + Returns: + True if updated successfully, False if tool not found or not tracking progress + + """ + tool = self._tools.get(tool_id) + if tool is None: + return False + + if tool.progress is None: + # Tool not tracking progress + return False + + tool.progress = ToolProgress(progress=max(0.0, min(1.0, progress)), message=message) + logger.debug(f"Tool {tool_id} progress: {progress:.1%} - {message or ''}") + return True + + async def cancel_tool(self, tool_id: str, log: bool = True) -> bool: + """Cancel a running tool by ID. + + Args: + tool_id: The tool ID to cancel + log: Whether to log the cancellation + + Returns: + True if cancelled, False if tool not found or not running + + """ + tool = self._tools.get(tool_id) + if tool is None: + if log: + logger.warning(f"Cannot cancel tool {tool_id}: not found") + return False + + if tool.status != ToolState.RUNNING: + if log: + logger.warning(f"Cannot cancel tool {tool_id}: status is {tool.status.value}") + return True + + if tool._task: + tool._task.cancel() + if log: + logger.info(f"Cancelled tool: {tool.tool_name} (id={tool_id})") + return True + + return False + + def start_up(self, tool_callbacks: list[Callable[[ToolNotification], Coroutine[Any, Any, None]]]) -> None: + """Start the background tool manager. + + This method starts two concurrent tasks: + - _listener: Listens for completed BackgroundTool notifications and calls the callbacks. + - _cleanup: Cleans up completed/failed/cancelled tools that have been in memory for too long and times out tools that have been running too long. + + Args: + tool_callbacks: A list of async or sync callables that receive the completed BackgroundTool notifications. + + """ + self.set_loop() + + async def _listener() -> None: + while True: + bg_tool = await self._notification_queue.get() + for callback in tool_callbacks: + await callback(bg_tool) + + async def _cleanup(interval_seconds: float = 5 * 60) -> None: + while True: + await asyncio.sleep(interval_seconds) + await self.cleanup_tools() + await self.timeout_tools() + + self._lifecycle_tasks = [ + asyncio.create_task(_cleanup(), name="bg-tool-cleanup"), + asyncio.create_task(_listener(), name="bg-tool-listener-callback"), + ] + + logger.info( + "BackgroundToolManager started. " + "Max tool execution duration: %s seconds (tools running longer will be auto-cancelled). " + "Max tool memory retention: %s seconds (completed/failed/cancelled tools older than this are purged).", + self._max_tool_duration_seconds, self._max_tool_memory_seconds, + ) + + async def shutdown(self) -> None: + """Cancel all background tasks (listener, cleanup) and running tools.""" + for task in self._lifecycle_tasks: + task.cancel() + for task in self._lifecycle_tasks: + try: + await task + except asyncio.CancelledError: + pass + self._lifecycle_tasks.clear() + + for tool_id in list(self._tools): + await self.cancel_tool(tool_id, log=False) + + logger.info("BackgroundToolManager shut down") + + async def timeout_tools(self) -> int: + """Cancel tools that have been running too long. + + Returns: + Number of tools cancelled + + """ + now = time.monotonic() + to_cancel = [] + + for tool_id, tool in self._tools.items(): + if tool.status == ToolState.RUNNING: + if tool.started_at and (now - tool.started_at) > self._max_tool_duration_seconds: + to_cancel.append(tool_id) + + for tool_id in to_cancel: + await self.cancel_tool(tool_id) + + if to_cancel: + logger.debug(f"Timed out {len(to_cancel)} tools") + + return len(to_cancel) + + async def cleanup_tools(self) -> int: + """Remove completed/failed/cancelled tools that have been in memory for too long. + + Returns: + Number of tools removed + + """ + now = time.monotonic() + to_remove = [] + + for tool_id, tool in self._tools.items(): + if tool.status in (ToolState.COMPLETED, ToolState.FAILED, ToolState.CANCELLED): + if tool.completed_at and (now - tool.completed_at) > self._max_tool_memory_seconds: + to_remove.append(tool_id) + + for tool_id in to_remove: + del self._tools[tool_id] + + if to_remove: + logger.debug(f"Cleaned up {len(to_remove)} old tools") + + return len(to_remove) + + def get_tool(self, tool_id: str) -> Optional[BackgroundTool]: + """Get a tool by ID.""" + return self._tools.get(tool_id) + + def get_running_tools(self) -> list[BackgroundTool]: + """Get all currently running tools.""" + return [t for t in self._tools.values() if t.status == ToolState.RUNNING] + + def get_all_tools(self, limit: Optional[int] = None) -> list[BackgroundTool]: + """Get recent tools (most recent first). + + Args: + limit: Maximum number of tools to return (None means all) + + Returns: + List of tools sorted by start time (most recent first) + + """ + sorted_tools = sorted( + self._tools.values(), + key=lambda t: t.started_at, + reverse=True, + ) + if limit is not None: + return sorted_tools[:limit] + return sorted_tools diff --git a/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/tools/camera.py b/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/tools/camera.py new file mode 100644 index 00000000..0c7fbb8f --- /dev/null +++ b/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/tools/camera.py @@ -0,0 +1,68 @@ +import base64 +import asyncio +import logging +from typing import Any, Dict + +import cv2 + +from reachy_mini_conversation_app.tools.core_tools import Tool, ToolDependencies + + +logger = logging.getLogger(__name__) + + +class Camera(Tool): + """Take a picture with the camera and ask a question about it.""" + + name = "camera" + description = "Take a picture with the camera and ask a question about it." + parameters_schema = { + "type": "object", + "properties": { + "question": { + "type": "string", + "description": "The question to ask about the picture", + }, + }, + "required": ["question"], + } + + async def __call__(self, deps: ToolDependencies, **kwargs: Any) -> Dict[str, Any]: + """Take a picture with the camera and ask a question about it.""" + image_query = (kwargs.get("question") or "").strip() + if not image_query: + logger.warning("camera: empty question") + return {"error": "question must be a non-empty string"} + + logger.info("Tool call: camera question=%s", image_query[:120]) + + # Get frame from camera worker buffer (like main_works.py) + if deps.camera_worker is not None: + frame = deps.camera_worker.get_latest_frame() + if frame is None: + logger.error("No frame available from camera worker") + return {"error": "No frame available"} + else: + logger.error("Camera worker not available") + return {"error": "Camera worker not available"} + + # Use vision manager for processing if available + if deps.vision_manager is not None: + vision_result = await asyncio.to_thread( + deps.vision_manager.processor.process_image, frame, image_query, + ) + if isinstance(vision_result, dict) and "error" in vision_result: + return vision_result + return ( + {"image_description": vision_result} + if isinstance(vision_result, str) + else {"error": "vision returned non-string"} + ) + + # Encode image directly to JPEG bytes without writing to file + success, buffer = cv2.imencode('.jpg', frame) + if not success: + raise RuntimeError("Failed to encode frame as JPEG") + + b64_encoded = base64.b64encode(buffer.tobytes()).decode("utf-8") + return {"b64_im": b64_encoded} diff --git a/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/tools/core_tools.py b/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/tools/core_tools.py new file mode 100644 index 00000000..38bd525e --- /dev/null +++ b/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/tools/core_tools.py @@ -0,0 +1,213 @@ +from __future__ import annotations +import abc +import json +import asyncio +import inspect +import logging +import importlib +from typing import TYPE_CHECKING, Any, Dict, List +from dataclasses import dataclass + +from reachy_mini import ReachyMini +from reachy_mini_conversation_app.config import LOCKED_PROFILE, DEFAULT_PROFILES_DIRECTORY +from reachy_mini_conversation_app.tools.tool_constants import SystemTool + + +if TYPE_CHECKING: + from reachy_mini_conversation_app.tools.background_tool_manager import BackgroundToolManager + + +logger = logging.getLogger(__name__) + + +DEFAULT_PROFILES_MODULE = "reachy_mini_conversation_app.profiles" + + +if not logger.handlers: + handler = logging.StreamHandler() + formatter = logging.Formatter("%(asctime)s %(levelname)s %(name)s:%(lineno)d | %(message)s") + handler.setFormatter(formatter) + logger.addHandler(handler) + logger.setLevel(logging.INFO) + + +ALL_TOOLS: Dict[str, "Tool"] = {} +ALL_TOOL_SPECS: List[Dict[str, Any]] = [] +_TOOLS_INITIALIZED = False + + +def get_concrete_subclasses(base: type[Tool]) -> List[type[Tool]]: + """Recursively find all concrete (non-abstract) subclasses of a base class.""" + result: List[type[Tool]] = [] + for cls in base.__subclasses__(): + if not inspect.isabstract(cls): + result.append(cls) + result.extend(get_concrete_subclasses(cls)) + return result + + +@dataclass +class ToolDependencies: + """External dependencies injected into tools.""" + + reachy_mini: ReachyMini + movement_manager: Any + camera_worker: Any | None = None + vision_manager: Any | None = None + head_wobbler: Any | None = None + motion_duration_s: float = 1.0 + + +class Tool(abc.ABC): + """Base abstraction for tools used in function-calling.""" + + name: str + description: str + parameters_schema: Dict[str, Any] + + def spec(self) -> Dict[str, Any]: + """Return the function spec for LLM consumption.""" + return { + "type": "function", + "name": self.name, + "description": self.description, + "parameters": self.parameters_schema, + } + + @abc.abstractmethod + async def __call__(self, deps: ToolDependencies, **kwargs: Any) -> Dict[str, Any]: + """Async tool execution entrypoint.""" + raise NotImplementedError + + +def _try_import_tool(module_path: str) -> bool: + """Import a tool module, returning False only when that module does not exist.""" + try: + importlib.import_module(module_path) + return True + except ModuleNotFoundError as exc: + if exc.name != module_path: + raise + return False + + +def _format_error(error: Exception) -> str: + """Format an exception for logging.""" + if isinstance(error, ModuleNotFoundError): + return f"Missing dependency: {error}" + if isinstance(error, ImportError): + return f"Import error: {error}" + return f"{type(error).__name__}: {error}" + + +def _load_profile_tools() -> None: + """Load tools from the locked profile's tools.txt file.""" + profile = LOCKED_PROFILE + logger.info("Loading tools for locked profile: %s", profile) + + profile_module_path = DEFAULT_PROFILES_DIRECTORY / profile + tools_txt_path = profile_module_path / "tools.txt" + + if not tools_txt_path.exists(): + raise RuntimeError(f"tools.txt not found at {tools_txt_path}") + + try: + lines = tools_txt_path.read_text(encoding="utf-8").splitlines() + except Exception as e: + raise RuntimeError(f"Failed to read tools.txt: {e}") from e + + tool_names = [] + for line in lines: + line = line.strip() + if not line or line.startswith("#"): + continue + tool_names.append(line) + + tool_names.extend({tool.value for tool in SystemTool}) + + logger.info("Found %d tools to load: %s", len(tool_names), tool_names) + + for tool_name in tool_names: + profile_import_path = f"{DEFAULT_PROFILES_MODULE}.{profile}.{tool_name}" + shared_module_path = f"reachy_mini_conversation_app.tools.{tool_name}" + + try: + if _try_import_tool(profile_import_path): + logger.info("Loaded profile tool: %s", tool_name) + continue + except Exception as e: + raise RuntimeError(f"Failed to load profile tool '{tool_name}': {_format_error(e)}") from e + + try: + if _try_import_tool(shared_module_path): + logger.info("Loaded built-in tool: %s", tool_name) + continue + except Exception as e: + raise RuntimeError(f"Failed to load built-in tool '{tool_name}': {_format_error(e)}") from e + + raise RuntimeError(f"Tool '{tool_name}' was not found in the locked profile or built-in tools") + + +def _initialize_tools() -> None: + """Populate registry once, even if module is imported repeatedly.""" + global ALL_TOOLS, ALL_TOOL_SPECS, _TOOLS_INITIALIZED + + if _TOOLS_INITIALIZED: + logger.debug("Tools already initialized; skipping reinitialization.") + return + + _load_profile_tools() + + ALL_TOOLS = {cls.name: cls() for cls in get_concrete_subclasses(Tool)} # type: ignore[type-abstract] + ALL_TOOL_SPECS = [tool.spec() for tool in ALL_TOOLS.values()] + + for tool_name, tool in ALL_TOOLS.items(): + logger.info(f"tool registered: {tool_name} - {tool.description}") + + _TOOLS_INITIALIZED = True + + +_initialize_tools() + + +def get_tool_specs(exclusion_list: list[str] | None = None) -> list[Dict[str, Any]]: + """Get tool specs, optionally excluding some tools.""" + exclusion_list = exclusion_list or [] + return [spec for spec in ALL_TOOL_SPECS if spec.get("name") not in exclusion_list] + + +# Dispatcher +def _safe_load_obj(args_json: str) -> Dict[str, Any]: + try: + parsed_args = json.loads(args_json or "{}") + return parsed_args if isinstance(parsed_args, dict) else {} + except Exception: + logger.warning("bad args_json=%r", args_json) + return {} + + +async def _dispatch_tool_call(tool_name: str, args: Dict[str, Any], deps: ToolDependencies) -> Dict[str, Any]: + tool = ALL_TOOLS.get(tool_name) + if not tool: + return {"error": f"unknown tool: {tool_name}"} + try: + return await tool(deps, **args) + except asyncio.CancelledError: + logger.info("Tool cancelled: %s", tool_name) + return {"error": "Tool cancelled"} + except Exception as e: + msg = f"{type(e).__name__}: {e}" + logger.exception("Tool error in %s: %s", tool_name, msg) + return {"error": msg} + + +async def dispatch_tool_call(tool_name: str, args_json: str, deps: ToolDependencies) -> Dict[str, Any]: + """Dispatch a tool call by name with JSON args and dependencies.""" + return await _dispatch_tool_call(tool_name, _safe_load_obj(args_json), deps) + + +async def dispatch_tool_call_with_manager(tool_name: str, args_json: str, deps: ToolDependencies, tool_manager: "BackgroundToolManager") -> Dict[str, Any]: + """Dispatch a tool call, injecting a BackgroundToolManager into the args.""" + args = _safe_load_obj(args_json) + args["tool_manager"] = tool_manager + return await _dispatch_tool_call(tool_name, args, deps) diff --git a/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/tools/dance.py b/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/tools/dance.py new file mode 100644 index 00000000..833cd552 --- /dev/null +++ b/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/tools/dance.py @@ -0,0 +1,86 @@ +import logging +from typing import Any, Dict + +from reachy_mini_conversation_app.tools.core_tools import Tool, ToolDependencies + + +logger = logging.getLogger(__name__) + +# Initialize dance library +try: + from reachy_mini_dances_library.collection.dance import AVAILABLE_MOVES + from reachy_mini_conversation_app.dance_emotion_moves import DanceQueueMove + + DANCE_AVAILABLE = True +except ImportError as e: + logger.warning(f"Dance library not available: {e}") + AVAILABLE_MOVES = {} + DANCE_AVAILABLE = False + + +class Dance(Tool): + """Play a named or random dance move once (or repeat). Non-blocking.""" + + name = "dance" + description = "Play a named or random dance move once (or repeat). Non-blocking." + parameters_schema = { + "type": "object", + "properties": { + "move": { + "type": "string", + "description": """Name of the move; use 'random' or omit for random. + Here is a list of the available moves: + simple_nod: A simple, continuous up-and-down nodding motion. + head_tilt_roll: A continuous side-to-side head roll (ear to shoulder). + side_to_side_sway: A smooth, side-to-side sway of the entire head. + dizzy_spin: A circular 'dizzy' head motion combining roll and pitch. + stumble_and_recover: A simulated stumble and recovery with multiple axis movements. Good vibes + interwoven_spirals: A complex spiral motion using three axes at different frequencies. + sharp_side_tilt: A sharp, quick side-to-side tilt using a triangle waveform. + side_peekaboo: A multi-stage peekaboo performance, hiding and peeking to each side. + yeah_nod: An emphatic two-part yeah nod using transient motions. + uh_huh_tilt: A combined roll-and-pitch uh-huh gesture of agreement. + neck_recoil: A quick, transient backward recoil of the neck. + chin_lead: A forward motion led by the chin, combining translation and pitch. + groovy_sway_and_roll: A side-to-side sway combined with a corresponding roll for a groovy effect. + chicken_peck: A sharp, forward, chicken-like pecking motion. + side_glance_flick: A quick glance to the side that holds, then returns. + polyrhythm_combo: A 3-beat sway and a 2-beat nod create a polyrhythmic feel. + grid_snap: A robotic, grid-snapping motion using square waveforms. + pendulum_swing: A simple, smooth pendulum-like swing using a roll motion. + jackson_square: Traces a rectangle via a 5-point path, with sharp twitches on arrival at each checkpoint. + """, + }, + "repeat": { + "type": "integer", + "description": "How many times to repeat the move (default 1).", + }, + }, + "required": [], + } + + async def __call__(self, deps: ToolDependencies, **kwargs: Any) -> Dict[str, Any]: + """Play a named or random dance move once (or repeat). Non-blocking.""" + if not DANCE_AVAILABLE: + return {"error": "Dance system not available"} + + move_name = kwargs.get("move") + repeat = int(kwargs.get("repeat", 1)) + + logger.info("Tool call: dance move=%s repeat=%d", move_name, repeat) + + if not move_name or move_name == "random": + import random + + move_name = random.choice(list(AVAILABLE_MOVES.keys())) + + if move_name not in AVAILABLE_MOVES: + return {"error": f"Unknown dance move '{move_name}'. Available: {list(AVAILABLE_MOVES.keys())}"} + + # Add dance moves to queue + movement_manager = deps.movement_manager + for _ in range(repeat): + dance_move = DanceQueueMove(move_name) + movement_manager.queue_move(dance_move) + + return {"status": "queued", "move": move_name, "repeat": repeat} diff --git a/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/tools/do_nothing.py b/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/tools/do_nothing.py new file mode 100644 index 00000000..c64588f6 --- /dev/null +++ b/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/tools/do_nothing.py @@ -0,0 +1,30 @@ +import logging +from typing import Any, Dict + +from reachy_mini_conversation_app.tools.core_tools import Tool, ToolDependencies + + +logger = logging.getLogger(__name__) + + +class DoNothing(Tool): + """Choose to do nothing - stay still and silent. Use when you want to be contemplative or just chill.""" + + name = "do_nothing" + description = "Choose to do nothing - stay still and silent. Use when you want to be contemplative or just chill." + parameters_schema = { + "type": "object", + "properties": { + "reason": { + "type": "string", + "description": "Optional reason for doing nothing (e.g., 'contemplating existence', 'saving energy', 'being mysterious')", + }, + }, + "required": [], + } + + async def __call__(self, deps: ToolDependencies, **kwargs: Any) -> Dict[str, Any]: + """Do nothing - stay still and silent.""" + reason = kwargs.get("reason", "just chilling") + logger.info("Tool call: do_nothing reason=%s", reason) + return {"status": "doing nothing", "reason": reason} diff --git a/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/tools/head_tracking.py b/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/tools/head_tracking.py new file mode 100644 index 00000000..57fa178d --- /dev/null +++ b/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/tools/head_tracking.py @@ -0,0 +1,31 @@ +import logging +from typing import Any, Dict + +from reachy_mini_conversation_app.tools.core_tools import Tool, ToolDependencies + + +logger = logging.getLogger(__name__) + + +class HeadTracking(Tool): + """Toggle head tracking state.""" + + name = "head_tracking" + description = "Toggle head tracking state." + parameters_schema = { + "type": "object", + "properties": {"start": {"type": "boolean"}}, + "required": ["start"], + } + + async def __call__(self, deps: ToolDependencies, **kwargs: Any) -> Dict[str, Any]: + """Enable or disable head tracking.""" + enable = bool(kwargs.get("start")) + + # Update camera worker head tracking state + if deps.camera_worker is not None: + deps.camera_worker.set_head_tracking_enabled(enable) + + status = "started" if enable else "stopped" + logger.info("Tool call: head_tracking %s", status) + return {"status": f"head tracking {status}"} diff --git a/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/tools/move_head.py b/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/tools/move_head.py new file mode 100644 index 00000000..4633572e --- /dev/null +++ b/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/tools/move_head.py @@ -0,0 +1,79 @@ +import logging +from typing import Any, Dict, Tuple, Literal + +from reachy_mini.utils import create_head_pose +from reachy_mini_conversation_app.goto_queue_move import GotoQueueMove +from reachy_mini_conversation_app.tools.core_tools import Tool, ToolDependencies + + +logger = logging.getLogger(__name__) + +Direction = Literal["left", "right", "up", "down", "front"] + + +class MoveHead(Tool): + """Move head in a given direction.""" + + name = "move_head" + description = "Move your head in a given direction: left, right, up, down or front." + parameters_schema = { + "type": "object", + "properties": { + "direction": { + "type": "string", + "enum": ["left", "right", "up", "down", "front"], + }, + }, + "required": ["direction"], + } + + # mapping: direction -> args for create_head_pose + DELTAS: Dict[str, Tuple[int, int, int, int, int, int]] = { + "left": (0, 0, 0, 0, 0, 40), + "right": (0, 0, 0, 0, 0, -40), + "up": (0, 0, 0, 0, -30, 0), + "down": (0, 0, 0, 0, 30, 0), + "front": (0, 0, 0, 0, 0, 0), + } + + async def __call__(self, deps: ToolDependencies, **kwargs: Any) -> Dict[str, Any]: + """Move head in a given direction.""" + direction_raw = kwargs.get("direction") + if not isinstance(direction_raw, str): + return {"error": "direction must be a string"} + direction: Direction = direction_raw # type: ignore[assignment] + logger.info("Tool call: move_head direction=%s", direction) + + deltas = self.DELTAS.get(direction, self.DELTAS["front"]) + target = create_head_pose(*deltas, degrees=True) + + # Use new movement manager + try: + movement_manager = deps.movement_manager + + # Get current state for interpolation + current_head_pose = deps.reachy_mini.get_current_head_pose() + _, current_antennas = deps.reachy_mini.get_current_joint_positions() + + # Create goto move + goto_move = GotoQueueMove( + target_head_pose=target, + start_head_pose=current_head_pose, + target_antennas=(0, 0), # Reset antennas to default + start_antennas=( + current_antennas[0], + current_antennas[1], + ), # Skip body_yaw + target_body_yaw=0, # Reset body yaw + start_body_yaw=current_antennas[0], # body_yaw is first in joint positions + duration=deps.motion_duration_s, + ) + + movement_manager.queue_move(goto_move) + movement_manager.set_moving_state(deps.motion_duration_s) + + return {"status": f"looking {direction}"} + + except Exception as e: + logger.error("move_head failed") + return {"error": f"move_head failed: {type(e).__name__}: {e}"} diff --git a/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/tools/play_emotion.py b/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/tools/play_emotion.py new file mode 100644 index 00000000..34b2fdac --- /dev/null +++ b/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/tools/play_emotion.py @@ -0,0 +1,84 @@ +import logging +from typing import Any, Dict + +from reachy_mini_conversation_app.tools.core_tools import Tool, ToolDependencies + + +logger = logging.getLogger(__name__) + +# Initialize emotion library +try: + from reachy_mini.motion.recorded_move import RecordedMoves + from reachy_mini_conversation_app.dance_emotion_moves import EmotionQueueMove + + # Note: huggingface_hub automatically reads HF_TOKEN from environment variables + RECORDED_MOVES = RecordedMoves("pollen-robotics/reachy-mini-emotions-library") + EMOTION_AVAILABLE = True +except ImportError as e: + logger.warning(f"Emotion library not available: {e}") + RECORDED_MOVES = None + EMOTION_AVAILABLE = False + + +def get_available_emotions_and_descriptions() -> str: + """Get formatted list of available emotions with descriptions.""" + if not EMOTION_AVAILABLE: + return "Emotions not available" + + try: + emotion_names = RECORDED_MOVES.list_moves() + output = "Available emotions:\n" + for name in emotion_names: + description = RECORDED_MOVES.get(name).description + output += f" - {name}: {description}\n" + return output + except Exception as e: + return f"Error getting emotions: {e}" + + +class PlayEmotion(Tool): + """Play a pre-recorded emotion.""" + + name = "play_emotion" + description = "Play a pre-recorded emotion" + parameters_schema = { + "type": "object", + "properties": { + "emotion": { + "type": "string", + "description": f"""Name of the emotion to play. + Here is a list of the available emotions: + {get_available_emotions_and_descriptions()} + """, + }, + }, + "required": ["emotion"], + } + + async def __call__(self, deps: ToolDependencies, **kwargs: Any) -> Dict[str, Any]: + """Play a pre-recorded emotion.""" + if not EMOTION_AVAILABLE: + return {"error": "Emotion system not available"} + + emotion_name = kwargs.get("emotion") + if not emotion_name: + return {"error": "Emotion name is required"} + + logger.info("Tool call: play_emotion emotion=%s", emotion_name) + + # Check if emotion exists + try: + emotion_names = RECORDED_MOVES.list_moves() + if emotion_name not in emotion_names: + return {"error": f"Unknown emotion '{emotion_name}'. Available: {emotion_names}"} + + # Add emotion to queue + movement_manager = deps.movement_manager + emotion_move = EmotionQueueMove(emotion_name, RECORDED_MOVES) + movement_manager.queue_move(emotion_move) + + return {"status": "queued", "emotion": emotion_name} + + except Exception as e: + logger.exception("Failed to play emotion") + return {"error": f"Failed to play emotion: {e!s}"} diff --git a/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/tools/stop_dance.py b/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/tools/stop_dance.py new file mode 100644 index 00000000..ab14e84a --- /dev/null +++ b/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/tools/stop_dance.py @@ -0,0 +1,31 @@ +import logging +from typing import Any, Dict + +from reachy_mini_conversation_app.tools.core_tools import Tool, ToolDependencies + + +logger = logging.getLogger(__name__) + + +class StopDance(Tool): + """Stop the current dance move.""" + + name = "stop_dance" + description = "Stop the current dance move" + parameters_schema = { + "type": "object", + "properties": { + "dummy": { + "type": "boolean", + "description": "dummy boolean, set it to true", + }, + }, + "required": ["dummy"], + } + + async def __call__(self, deps: ToolDependencies, **kwargs: Any) -> Dict[str, Any]: + """Stop the current dance move.""" + logger.info("Tool call: stop_dance") + movement_manager = deps.movement_manager + movement_manager.clear_move_queue() + return {"status": "stopped dance and cleared queue"} diff --git a/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/tools/stop_emotion.py b/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/tools/stop_emotion.py new file mode 100644 index 00000000..b5d2323f --- /dev/null +++ b/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/tools/stop_emotion.py @@ -0,0 +1,31 @@ +import logging +from typing import Any, Dict + +from reachy_mini_conversation_app.tools.core_tools import Tool, ToolDependencies + + +logger = logging.getLogger(__name__) + + +class StopEmotion(Tool): + """Stop the current emotion.""" + + name = "stop_emotion" + description = "Stop the current emotion" + parameters_schema = { + "type": "object", + "properties": { + "dummy": { + "type": "boolean", + "description": "dummy boolean, set it to true", + }, + }, + "required": ["dummy"], + } + + async def __call__(self, deps: ToolDependencies, **kwargs: Any) -> Dict[str, Any]: + """Stop the current emotion.""" + logger.info("Tool call: stop_emotion") + movement_manager = deps.movement_manager + movement_manager.clear_move_queue() + return {"status": "stopped emotion and cleared queue"} diff --git a/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/tools/task_cancel.py b/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/tools/task_cancel.py new file mode 100644 index 00000000..6e3c6e89 --- /dev/null +++ b/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/tools/task_cancel.py @@ -0,0 +1,74 @@ +"""Tool cancel tool - cancel running background tools.""" + +import logging +from typing import TYPE_CHECKING, Any, Dict + +from reachy_mini_conversation_app.tools.core_tools import Tool, ToolDependencies +from reachy_mini_conversation_app.tools.tool_constants import ToolState + + +if TYPE_CHECKING: + from reachy_mini_conversation_app.tools.background_tool_manager import BackgroundToolManager + + +logger = logging.getLogger(__name__) + + +class TaskCancel(Tool): + """Cancel a running background tool task.""" + + name = "task_cancel" + description = ( + "Cancel a running background tool task. " + "Use this when the user wants to stop a tool that's running in the background. " + "Requires confirmation before cancelling." + ) + parameters_schema = { + "type": "object", + "properties": { + "tool_id": { + "type": "string", + "description": "The tool ID to cancel", + } + }, + "required": ["tool_id"], + } + + async def __call__(self, deps: ToolDependencies, **kwargs: Any) -> Dict[str, Any]: + """Cancel a background tool.""" + tool_id = kwargs.get("tool_id", "") + tool_manager: BackgroundToolManager | None = kwargs.get("tool_manager") + + if tool_manager is None: + return {"error": "Tool manager is required."} + + logger.info(f"Tool call: tool_cancel tool_id={tool_id}") + + if not tool_id: + return {"error": "Tool ID is required."} + + tool = tool_manager.get_tool(tool_id) + + if not tool: + return {"error": f"Tool {tool_id} not found."} + + # Check if tool is still running + if tool.status != ToolState.RUNNING: + return { + "status": f"{tool.status.value}", + "message": f"Tool '{tool.tool_name}' is not running (status: {tool.status.value}).", + "tool_id": tool_id, + } + + # Cancel the tool + if await tool_manager.cancel_tool(tool_id): + return { + "status": "cancelled", + "message": f"Tool '{tool.tool_name}' has been cancelled.", + "tool_id": tool_id, + "tool_name": tool.tool_name, + } + else: + return { + "error": f"Could not cancel tool {tool_id}. It may have already completed.", + } diff --git a/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/tools/task_status.py b/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/tools/task_status.py new file mode 100644 index 00000000..a5d0138d --- /dev/null +++ b/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/tools/task_status.py @@ -0,0 +1,104 @@ +"""Tool status tool - check status of background tools.""" + +import time +import logging +from typing import TYPE_CHECKING, Any, Dict + +from reachy_mini_conversation_app.tools.core_tools import Tool, ToolDependencies +from reachy_mini_conversation_app.tools.tool_constants import SystemTool + + +if TYPE_CHECKING: + from reachy_mini_conversation_app.tools.background_tool_manager import BackgroundToolManager + + +logger = logging.getLogger(__name__) + + +class TaskStatus(Tool): + """Check status of background tool tasks.""" + + name = "task_status" + description = ( + "Check the status of background tool tasks. " + "Use this when the user asks about running tools or wants to know what's happening in the background." + ) + parameters_schema = { + "type": "object", + "properties": { + "tool_id": { + "type": "string", + "description": "Specific tool ID to check (optional, shows all running tools if omitted)", + }, + }, + "required": [], + } + + async def __call__(self, deps: ToolDependencies, **kwargs: Any) -> Dict[str, Any]: + """Get status of background tools.""" + tool_id: str | None = kwargs.get("tool_id") + tool_manager: BackgroundToolManager | None = kwargs.get("tool_manager") + + if tool_manager is None: + return {"error": "Tool manager is required."} + + logger.info(f"Tool call: tool_status tool_id={tool_id}") + + if tool_id: + tool = tool_manager.get_tool(tool_id) + if not tool: + return {"error": f"Tool {tool_id} not found."} + + result: Dict[str, Any] = { + "tool_id": tool.tool_id, + "name": tool.tool_name, + "status": tool.status.value, + "started_at": tool.started_at, + } + if tool.completed_at: + result["completed_at"] = tool.completed_at + + if tool.progress is not None: + result["progress_percent"] = f"{tool.progress.progress:.0%}" + if tool.progress.message: + result["progress_message"] = tool.progress.message + + if tool.result: + result["result"] = tool.result + if tool.error: + result["error"] = tool.error + + return result + + # Get all running tools + running = tool_manager.get_running_tools() + if not running: + return { + "status": "idle", + "message": "No tools running in the background.", + } + + tools_info = [] + for tool in [tool for tool in running if tool.tool_name not in [system_tool.value for system_tool in SystemTool]]: + elapsed = time.monotonic() - tool.started_at + tool_info: Dict[str, Any] = { + "tool_id": tool.tool_id, + "name": tool.tool_name, + "status": tool.status.value, + "elapsed_seconds": round(elapsed, 1), + } + + # Add progress if tracking + if tool.progress is not None: + tool_info["progress_percent"] = f"{tool.progress.progress:.0%}" + if tool.progress.message: + tool_info["progress_message"] = tool.progress.message + + tools_info.append(tool_info) + + return { + "status": "running", + "count": len(tools_info), + "message": f"{len(tools_info)} tool(s) running in the background.", + "tools": tools_info, + } diff --git a/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/tools/tool_constants.py b/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/tools/tool_constants.py new file mode 100644 index 00000000..da163c09 --- /dev/null +++ b/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/tools/tool_constants.py @@ -0,0 +1,17 @@ +from enum import Enum + + +class ToolState(Enum): + """Status of a background tool.""" + + RUNNING = "running" + COMPLETED = "completed" + FAILED = "failed" + CANCELLED = "cancelled" + + +class SystemTool(Enum): + """System tools are tools that are used to manage the background tool manager.""" + + TASK_STATUS = "task_status" + TASK_CANCEL = "task_cancel" diff --git a/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/utils.py b/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/utils.py new file mode 100644 index 00000000..67e28275 --- /dev/null +++ b/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/utils.py @@ -0,0 +1,123 @@ +import logging +import argparse +import warnings +from typing import Any, Tuple, Optional + +from reachy_mini import ReachyMini +from reachy_mini_conversation_app.camera_worker import CameraWorker + + +def parse_args() -> Tuple[argparse.Namespace, list]: # type: ignore + """Parse command line arguments.""" + parser = argparse.ArgumentParser("Reachy Mini Conversation App") + parser.add_argument( + "--head-tracker", + choices=["yolo", "mediapipe", None], + default=None, + help="Choose head tracker (default: None)", + ) + parser.add_argument("--no-camera", default=False, action="store_true", help="Disable camera usage") + parser.add_argument( + "--local-vision", + default=False, + action="store_true", + help="Use local vision model instead of gpt-realtime vision", + ) + parser.add_argument("--gradio", default=False, action="store_true", help="Open gradio interface") + parser.add_argument("--debug", default=False, action="store_true", help="Enable debug logging") + parser.add_argument( + "--robot-name", + type=str, + default=None, + help="[Optional] Robot name/prefix for Zenoh topics (must match daemon's --robot-name). Only needed for development with multiple robots.", + ) + return parser.parse_known_args() + + +def handle_vision_stuff(args: argparse.Namespace, current_robot: ReachyMini) -> Tuple[CameraWorker | None, Any, Any]: + """Initialize camera, head tracker, camera worker, and vision manager. + + By default, vision is handled by gpt-realtime model when camera tool is used. + If --local-vision flag is used, a local vision model will process images periodically. + """ + camera_worker = None + head_tracker = None + vision_manager = None + + if not args.no_camera: + # Initialize head tracker if specified + if args.head_tracker is not None: + if args.head_tracker == "yolo": + from reachy_mini_conversation_app.vision.yolo_head_tracker import HeadTracker + + head_tracker = HeadTracker() + elif args.head_tracker == "mediapipe": + from reachy_mini_toolbox.vision import HeadTracker # type: ignore[no-redef] + + head_tracker = HeadTracker() + + # Initialize camera worker + camera_worker = CameraWorker(current_robot, head_tracker) + + # Initialize vision manager only if local vision is requested + if args.local_vision: + try: + from reachy_mini_conversation_app.vision.processors import initialize_vision_manager + + vision_manager = initialize_vision_manager(camera_worker) + except ImportError as e: + raise ImportError( + "To use --local-vision, please install the extra dependencies: pip install '.[local_vision]'", + ) from e + else: + logging.getLogger(__name__).info( + "Using gpt-realtime for vision (default). Use --local-vision for local processing.", + ) + + return camera_worker, head_tracker, vision_manager + + +def setup_logger(debug: bool) -> logging.Logger: + """Setups the logger.""" + log_level = "DEBUG" if debug else "INFO" + logging.basicConfig( + level=getattr(logging, log_level, logging.INFO), + format="%(asctime)s %(levelname)s %(name)s:%(lineno)d | %(message)s", + ) + logger = logging.getLogger(__name__) + + # Suppress WebRTC warnings + warnings.filterwarnings("ignore", message=".*AVCaptureDeviceTypeExternal.*") + warnings.filterwarnings("ignore", category=UserWarning, module="aiortc") + + # Tame third-party noise (looser in DEBUG) + if log_level == "DEBUG": + logging.getLogger("aiortc").setLevel(logging.INFO) + logging.getLogger("fastrtc").setLevel(logging.INFO) + logging.getLogger("aioice").setLevel(logging.INFO) + logging.getLogger("openai").setLevel(logging.INFO) + logging.getLogger("websockets").setLevel(logging.INFO) + else: + logging.getLogger("aiortc").setLevel(logging.ERROR) + logging.getLogger("fastrtc").setLevel(logging.ERROR) + logging.getLogger("aioice").setLevel(logging.WARNING) + return logger + +def log_connection_troubleshooting(logger: logging.Logger, robot_name: Optional[str]) -> None: + """Log troubleshooting steps for connection issues.""" + logger.error("Troubleshooting steps:") + logger.error(" 1. Verify reachy-mini-daemon is running") + + if robot_name is not None: + logger.error( + f" 2. Daemon must be started with: --robot-name '{robot_name}'" + ) + else: + logger.error( + " 2. If daemon uses --robot-name, add the same flag here: " + "--robot-name " + ) + + logger.error(" 3. For wireless: check network connectivity") + logger.error(" 4. Review daemon logs") + logger.error(" 5. Restart the daemon") diff --git a/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/vision/__init__.py b/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/vision/__init__.py new file mode 100644 index 00000000..60dc15c4 --- /dev/null +++ b/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/vision/__init__.py @@ -0,0 +1 @@ +"""Nothing (for ruff).""" diff --git a/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/vision/processors.py b/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/vision/processors.py new file mode 100644 index 00000000..71598d8b --- /dev/null +++ b/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/vision/processors.py @@ -0,0 +1,331 @@ +import os +import time +import base64 +import logging +import threading +from typing import Any, Dict +from dataclasses import dataclass + +import cv2 +import numpy as np +import torch +from numpy.typing import NDArray +from transformers import AutoProcessor, AutoModelForImageTextToText +from huggingface_hub import snapshot_download + +from reachy_mini_conversation_app.config import config + + +logger = logging.getLogger(__name__) + + +@dataclass +class VisionConfig: + """Configuration for vision processing.""" + + model_path: str = config.LOCAL_VISION_MODEL + vision_interval: float = 5.0 + max_new_tokens: int = 64 + jpeg_quality: int = 85 + max_retries: int = 3 + retry_delay: float = 1.0 + device_preference: str = "auto" # "auto", "cuda", "cpu" + + +class VisionProcessor: + """Handles SmolVLM2 model loading and inference.""" + + def __init__(self, vision_config: VisionConfig | None = None): + """Initialize the vision processor.""" + self.vision_config = vision_config or VisionConfig() + self.model_path = self.vision_config.model_path + self.device = self._determine_device() + self.processor = None + self.model = None + self._initialized = False + + def _determine_device(self) -> str: + pref = self.vision_config.device_preference + if pref == "cpu": + return "cpu" + if pref == "cuda": + return "cuda" if torch.cuda.is_available() else "cpu" + if pref == "mps": + return "mps" if torch.backends.mps.is_available() else "cpu" + # auto: prefer mps on Apple, then cuda, else cpu + if torch.backends.mps.is_available(): + return "mps" + return "cuda" if torch.cuda.is_available() else "cpu" + + def initialize(self) -> bool: + """Load model and processor onto the selected device.""" + try: + logger.info(f"Loading SmolVLM2 model on {self.device} (HF_HOME={config.HF_HOME})") + self.processor = AutoProcessor.from_pretrained(self.model_path) # type: ignore + + # Select dtype depending on device + if self.device == "cuda": + dtype = torch.bfloat16 + elif self.device == "mps": + dtype = torch.float32 # best for MPS + else: + dtype = torch.float32 + + model_kwargs: Dict[str, Any] = {"dtype": dtype} + + # flash_attention_2 is CUDA-only; skip on MPS/CPU + if self.device == "cuda": + model_kwargs["_attn_implementation"] = "flash_attention_2" + + # Load model weights + self.model = AutoModelForImageTextToText.from_pretrained(self.model_path, **model_kwargs).to(self.device) # type: ignore + + if self.model is not None: + self.model.eval() + self._initialized = True + return True + + except Exception as e: + logger.error(f"Failed to initialize vision model: {e}") + return False + + def process_image( + self, + cv2_image: NDArray[np.uint8], + prompt: str = "Briefly describe what you see in one sentence.", + ) -> str: + """Process CV2 image and return description with retry logic.""" + if not self._initialized or self.processor is None or self.model is None: + return "Vision model not initialized" + + for attempt in range(self.vision_config.max_retries): + try: + # Convert to JPEG bytes + success, jpeg_buffer = cv2.imencode( + ".jpg", + cv2_image, + [cv2.IMWRITE_JPEG_QUALITY, self.vision_config.jpeg_quality], + ) + if not success: + return "Failed to encode image" + + # Convert to base64 + image_base64 = base64.b64encode(jpeg_buffer.tobytes()).decode("utf-8") + + messages = [ + { + "role": "user", + "content": [ + { + "type": "image", + "url": f"data:image/jpeg;base64,{image_base64}", + }, + {"type": "text", "text": prompt}, + ], + }, + ] + + inputs = self.processor.apply_chat_template( + messages, + add_generation_prompt=True, + tokenize=True, + return_dict=True, + return_tensors="pt", + ) + + # Move tensors to device WITHOUT forcing dtype (keeps input_ids as torch.long) + inputs = {k: (v.to(self.device) if hasattr(v, "to") else v) for k, v in inputs.items()} + + with torch.no_grad(): + generated_ids = self.model.generate( + **inputs, + do_sample=False, + max_new_tokens=self.vision_config.max_new_tokens, + pad_token_id=self.processor.tokenizer.eos_token_id, + ) + + generated_texts = self.processor.batch_decode( + generated_ids, + skip_special_tokens=True, + ) + + # Extract just the response part + full_text = generated_texts[0] + response = self._extract_response(full_text) + + # Clean up GPU memory if using CUDA + if self.device == "cuda": + torch.cuda.empty_cache() + elif self.device == "mps": + torch.mps.empty_cache() + + return response.replace(chr(10), " ").strip() + + except torch.cuda.OutOfMemoryError as e: + logger.error(f"CUDA OOM on attempt {attempt + 1}: {e}") + if self.device == "cuda": + torch.cuda.empty_cache() + if attempt < self.vision_config.max_retries - 1: + time.sleep(self.vision_config.retry_delay * (attempt + 1)) + else: + return "GPU out of memory - vision processing failed" + + except Exception as e: + logger.error(f"Vision processing failed (attempt {attempt + 1}): {e}") + if attempt < self.vision_config.max_retries - 1: + time.sleep(self.vision_config.retry_delay) + else: + return f"Vision processing error after {self.vision_config.max_retries} attempts" + + def _extract_response(self, full_text: str) -> str: + """Extract the assistant's response from the full generated text.""" + # Handle different response formats + markers = ["assistant\n", "Assistant:", "Response:", "\n\n"] + + for marker in markers: + if marker in full_text: + response = full_text.split(marker)[-1].strip() + if response: # Ensure we got a meaningful response + return response + + # Fallback: return the full text cleaned up + return full_text.strip() + + def get_model_info(self) -> Dict[str, Any]: + """Get information about the loaded model.""" + return { + "initialized": self._initialized, + "device": self.device, + "model_path": self.model_path, + "cuda_available": torch.cuda.is_available(), + "gpu_memory": torch.cuda.get_device_properties(0).total_memory // (1024**3) + if torch.cuda.is_available() + else "N/A", + } + + +class VisionManager: + """Manages periodic vision processing and scene understanding.""" + + def __init__(self, camera: Any, vision_config: VisionConfig | None = None): + """Initialize vision manager with camera and configuration.""" + self.camera = camera + self.vision_config = vision_config or VisionConfig() + self.vision_interval = self.vision_config.vision_interval + self.processor = VisionProcessor(self.vision_config) + + self._last_processed_time = 0.0 + self._stop_event = threading.Event() + self._thread: threading.Thread | None = None + + # Initialize processor + if not self.processor.initialize(): + logger.error("Failed to initialize vision processor") + raise RuntimeError("Vision processor initialization failed") + + def start(self) -> None: + """Start the vision processing loop in a thread.""" + self._stop_event.clear() + self._thread = threading.Thread(target=self._working_loop, daemon=True) + self._thread.start() + logger.info("Local vision processing started") + + def stop(self) -> None: + """Stop the vision processing loop.""" + self._stop_event.set() + if self._thread is not None: + self._thread.join() + logger.info("Local vision processing stopped") + + def _working_loop(self) -> None: + """Vision processing loop (runs in separate thread).""" + while not self._stop_event.is_set(): + try: + current_time = time.time() + + if current_time - self._last_processed_time >= self.vision_interval: + frame = self.camera.get_latest_frame() + if frame is not None: + description = self.processor.process_image( + frame, + "Briefly describe what you see in one sentence.", + ) + + # Only update if we got a valid response + if description and not description.startswith(("Vision", "Failed", "Error")): + self._last_processed_time = current_time + logger.debug(f"Vision update: {description}") + else: + logger.warning(f"Invalid vision response: {description}") + + time.sleep(1.0) # Check every second + + except Exception: + logger.exception("Vision processing loop error") + time.sleep(5.0) # Longer sleep on error + + logger.info("Vision loop finished") + + def get_status(self) -> Dict[str, Any]: + """Get comprehensive status information.""" + return { + "last_processed": self._last_processed_time, + "processor_info": self.processor.get_model_info(), + "config": { + "interval": self.vision_interval, + }, + } + + +def initialize_vision_manager(camera_worker: Any) -> VisionManager | None: + """Initialize vision manager with model download and configuration. + + Args: + camera_worker: CameraWorker instance for frame capture + Returns: + VisionManager instance or None if initialization fails + + """ + try: + model_id = config.LOCAL_VISION_MODEL + cache_dir = os.path.expanduser(config.HF_HOME) + + # Prepare cache directory + os.makedirs(cache_dir, exist_ok=True) + os.environ["HF_HOME"] = cache_dir + logger.info("HF_HOME set to %s", cache_dir) + + # Download model to cache + logger.info(f"Downloading vision model {model_id} to cache...") + snapshot_download( + repo_id=model_id, + repo_type="model", + cache_dir=cache_dir, + ) + logger.info(f"Model {model_id} downloaded to {cache_dir}") + + # Configure vision processing + vision_config = VisionConfig( + model_path=model_id, + vision_interval=5.0, + max_new_tokens=64, + jpeg_quality=85, + max_retries=3, + retry_delay=1.0, + device_preference="auto", + ) + + # Initialize vision manager + vision_manager = VisionManager(camera_worker, vision_config) + + # Log device info + device_info = vision_manager.processor.get_model_info() + logger.info( + f"Vision processing enabled: {device_info.get('model_path')} on {device_info.get('device')}", + ) + + return vision_manager + + except Exception as e: + logger.error(f"Failed to initialize vision manager: {e}") + return None diff --git a/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/vision/yolo_head_tracker.py b/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/vision/yolo_head_tracker.py new file mode 100644 index 00000000..3619bc7e --- /dev/null +++ b/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/vision/yolo_head_tracker.py @@ -0,0 +1,148 @@ +from __future__ import annotations +import logging +from typing import Tuple + +import numpy as np +from numpy.typing import NDArray + + +try: + from supervision import Detections + from ultralytics import YOLO # type: ignore +except ImportError as e: + raise ImportError( + "To use YOLO head tracker, please install the extra dependencies: pip install '.[yolo_vision]'", + ) from e +from huggingface_hub import hf_hub_download + + +logger = logging.getLogger(__name__) + + +class HeadTracker: + """Lightweight head tracker using YOLO for face detection.""" + + def __init__( + self, + model_repo: str = "AdamCodd/YOLOv11n-face-detection", + model_filename: str = "model.pt", + confidence_threshold: float = 0.3, + device: str = "cpu", + ) -> None: + """Initialize YOLO-based head tracker. + + Args: + model_repo: HuggingFace model repository + model_filename: Model file name + confidence_threshold: Minimum confidence for face detection + device: Device to run inference on ('cpu' or 'cuda') + + """ + self.confidence_threshold = confidence_threshold + + try: + # Download and load YOLO model + model_path = hf_hub_download(repo_id=model_repo, filename=model_filename) + self.model = YOLO(model_path).to(device) + logger.info(f"YOLO face detection model loaded from {model_repo}") + except Exception as e: + logger.error(f"Failed to load YOLO model: {e}") + raise + + def _select_best_face(self, detections: Detections) -> int | None: + """Select the best face based on confidence and area (largest face with highest confidence). + + Args: + detections: Supervision detections object + + Returns: + Index of best face or None if no valid faces + + """ + if detections.xyxy.shape[0] == 0: + return None + + # Check if confidence is available + if detections.confidence is None: + return None + + # Filter by confidence threshold + valid_mask = detections.confidence >= self.confidence_threshold + if not np.any(valid_mask): + return None + + valid_indices = np.where(valid_mask)[0] + + # Calculate areas for valid detections + boxes = detections.xyxy[valid_indices] + areas = (boxes[:, 2] - boxes[:, 0]) * (boxes[:, 3] - boxes[:, 1]) + + # Combine confidence and area (weighted towards larger faces) + confidences = detections.confidence[valid_indices] + scores = confidences * 0.7 + (areas / np.max(areas)) * 0.3 + + # Return index of best face + best_idx = valid_indices[np.argmax(scores)] + return int(best_idx) + + def _bbox_to_mp_coords(self, bbox: NDArray[np.float32], w: int, h: int) -> NDArray[np.float32]: + """Convert bounding box center to MediaPipe-style coordinates [-1, 1]. + + Args: + bbox: Bounding box [x1, y1, x2, y2] + w: Image width + h: Image height + + Returns: + Center point in [-1, 1] coordinates + + """ + center_x = (bbox[0] + bbox[2]) / 2.0 + center_y = (bbox[1] + bbox[3]) / 2.0 + + # Normalize to [0, 1] then to [-1, 1] + norm_x = (center_x / w) * 2.0 - 1.0 + norm_y = (center_y / h) * 2.0 - 1.0 + + return np.array([norm_x, norm_y], dtype=np.float32) + + def get_head_position(self, img: NDArray[np.uint8]) -> Tuple[NDArray[np.float32] | None, float | None]: + """Get head position from face detection. + + Args: + img: Input image + + Returns: + Tuple of (eye_center [-1,1], roll_angle) + + """ + h, w = img.shape[:2] + + try: + # Run YOLO inference + results = self.model(img, verbose=False) + detections = Detections.from_ultralytics(results[0]) + + # Select best face + face_idx = self._select_best_face(detections) + if face_idx is None: + logger.debug("No face detected above confidence threshold") + return None, None + + bbox = detections.xyxy[face_idx] + + if detections.confidence is not None: + confidence = detections.confidence[face_idx] + logger.debug(f"Face detected with confidence: {confidence:.2f}") + + # Get face center in [-1, 1] coordinates + face_center = self._bbox_to_mp_coords(bbox, w, h) + + # Roll is 0 since we don't have keypoints for precise angle estimation + roll = 0.0 + + return face_center, roll + + except Exception as e: + logger.error(f"Error in head position detection: {e}") + return None, None diff --git a/projects/reachy-mini-openshell/src/reachy_openshell/__init__.py b/projects/reachy-mini-openshell/src/reachy_openshell/__init__.py deleted file mode 100644 index 3dc1f76b..00000000 --- a/projects/reachy-mini-openshell/src/reachy_openshell/__init__.py +++ /dev/null @@ -1 +0,0 @@ -__version__ = "0.1.0" diff --git a/projects/reachy-mini-openshell/src/reachy_openshell/backend.py b/projects/reachy-mini-openshell/src/reachy_openshell/backend.py deleted file mode 100644 index c9f97acf..00000000 --- a/projects/reachy-mini-openshell/src/reachy_openshell/backend.py +++ /dev/null @@ -1,195 +0,0 @@ -from __future__ import annotations - -import argparse -import asyncio -import os -import sys -import urllib.error -import urllib.request -from dataclasses import asdict, dataclass -from typing import Any - -from . import __version__ - -LOCAL_HOSTS = {"localhost", "127.0.0.1", "::1"} - -try: - from fastapi import FastAPI, HTTPException -except ImportError: # pragma: no cover - exercised only when optional deps are absent. - FastAPI = None # type: ignore[assignment] - HTTPException = None # type: ignore[assignment] - - -@dataclass(frozen=True) -class Settings: - reachy_host: str - reachy_port: int - connection_mode: str - media_backend: str - timeout: float - - @classmethod - def from_env(cls) -> "Settings": - host = os.getenv("REACHY_HOST", "localhost") - return cls( - reachy_host=host, - reachy_port=_env_int("REACHY_PORT", 8000), - connection_mode=os.getenv("REACHY_CONNECTION_MODE", _default_connection_mode(host)), - media_backend=os.getenv("REACHY_MEDIA_BACKEND", "no_media"), - timeout=_env_float("REACHY_TIMEOUT", 5.0), - ) - - @property - def daemon_base_url(self) -> str: - return f"http://{self.reachy_host}:{self.reachy_port}" - - -def _env_int(name: str, default: int) -> int: - raw = os.getenv(name) - if raw is None: - return default - try: - return int(raw) - except ValueError as exc: - raise ValueError(f"{name} must be an integer, got {raw!r}") from exc - - -def _env_float(name: str, default: float) -> float: - raw = os.getenv(name) - if raw is None: - return default - try: - return float(raw) - except ValueError as exc: - raise ValueError(f"{name} must be a number, got {raw!r}") from exc - - -def _default_connection_mode(host: str) -> str: - return "localhost_only" if host in LOCAL_HOSTS else "network" - - -def daemon_status(settings: Settings) -> dict[str, Any]: - url = f"{settings.daemon_base_url}/api/daemon/status" - try: - with urllib.request.urlopen(url, timeout=settings.timeout) as response: - body = response.read(4096).decode("utf-8", errors="replace") - return { - "ok": 200 <= response.status < 500, - "status_code": response.status, - "url": url, - "body": body, - } - except (urllib.error.URLError, TimeoutError, OSError) as exc: - return { - "ok": False, - "url": url, - "error": str(exc), - } - - -def run_smoke_motion(settings: Settings) -> dict[str, Any]: - try: - from reachy_mini import ReachyMini - from reachy_mini.utils import create_head_pose - except ImportError as exc: - raise RuntimeError( - "Reachy Mini SDK is not installed. Install with `uv pip install -e '.[sdk]'` " - "or include the `sim` extra for local simulator work." - ) from exc - - with ReachyMini( - host=settings.reachy_host, - port=settings.reachy_port, - connection_mode=settings.connection_mode, - spawn_daemon=False, - media_backend=settings.media_backend, - timeout=settings.timeout, - ) as mini: - mini.goto_target( - head=create_head_pose(z=20, roll=10, mm=True, degrees=True), - duration=1.0, - ) - mini.goto_target(antennas=[0.6, -0.6], duration=0.3) - mini.goto_target(antennas=[-0.6, 0.6], duration=0.3) - mini.goto_target( - head=create_head_pose(), - antennas=[0.0, 0.0], - duration=1.0, - ) - - return { - "ok": True, - "reachy": asdict(settings), - "motion": "smoke", - } - - -def _create_app() -> Any: - if FastAPI is None: - return None - - api = FastAPI( - title="Reachy Mini OpenShell Backend", - version=__version__, - ) - - @api.get("/health") - def health() -> dict[str, Any]: - settings = Settings.from_env() - status = daemon_status(settings) - return { - "ok": status["ok"], - "reachy": asdict(settings), - "daemon": status, - } - - @api.post("/moves/smoke") - async def smoke_move() -> dict[str, Any]: - settings = Settings.from_env() - try: - return await asyncio.to_thread(run_smoke_motion, settings) - except Exception as exc: # pragma: no cover - depends on live daemon. - raise HTTPException(status_code=502, detail=str(exc)) from exc - - return api - - -app = _create_app() - - -def main(argv: list[str] | None = None) -> int: - if FastAPI is None: - print( - "FastAPI is not installed. Install backend dependencies with " - '`uv pip install -e ".[backend]"`.', - file=sys.stderr, - ) - return 2 - - parser = argparse.ArgumentParser(description="Run the Reachy Mini OpenShell backend.") - parser.add_argument("--host", default=os.getenv("BACKEND_HOST", "127.0.0.1")) - parser.add_argument("--port", type=int, default=_env_int("BACKEND_PORT", 8080)) - parser.add_argument("--reachy-host", default=None) - parser.add_argument("--reachy-port", type=int, default=None) - parser.add_argument("--connection-mode", default=None) - parser.add_argument("--media-backend", default=None) - parser.add_argument("--log-level", default=os.getenv("UVICORN_LOG_LEVEL", "info")) - args = parser.parse_args(argv) - - if args.reachy_host is not None: - os.environ["REACHY_HOST"] = args.reachy_host - if args.reachy_port is not None: - os.environ["REACHY_PORT"] = str(args.reachy_port) - if args.connection_mode is not None: - os.environ["REACHY_CONNECTION_MODE"] = args.connection_mode - if args.media_backend is not None: - os.environ["REACHY_MEDIA_BACKEND"] = args.media_backend - - import uvicorn - - uvicorn.run(app, host=args.host, port=args.port, log_level=args.log_level) - return 0 - - -if __name__ == "__main__": - raise SystemExit(main()) diff --git a/projects/reachy-mini-openshell/src/reachy_openshell/smoke.py b/projects/reachy-mini-openshell/src/reachy_openshell/smoke.py deleted file mode 100644 index 5933427c..00000000 --- a/projects/reachy-mini-openshell/src/reachy_openshell/smoke.py +++ /dev/null @@ -1,115 +0,0 @@ -from __future__ import annotations - -import argparse -import os -import sys -from dataclasses import dataclass - -LOCAL_HOSTS = {"localhost", "127.0.0.1", "::1"} - - -@dataclass(frozen=True) -class ReachyTarget: - host: str - port: int - connection_mode: str - media_backend: str - timeout: float - - -def _env_int(name: str, default: int) -> int: - raw = os.getenv(name) - if raw is None: - return default - try: - return int(raw) - except ValueError as exc: - raise ValueError(f"{name} must be an integer, got {raw!r}") from exc - - -def _env_float(name: str, default: float) -> float: - raw = os.getenv(name) - if raw is None: - return default - try: - return float(raw) - except ValueError as exc: - raise ValueError(f"{name} must be a number, got {raw!r}") from exc - - -def _default_connection_mode(host: str) -> str: - return "localhost_only" if host in LOCAL_HOSTS else "network" - - -def build_parser() -> argparse.ArgumentParser: - default_host = os.getenv("REACHY_HOST", "localhost") - parser = argparse.ArgumentParser(description="Run a small Reachy Mini SDK smoke motion.") - parser.add_argument("--host", default=default_host) - parser.add_argument("--port", type=int, default=_env_int("REACHY_PORT", 8000)) - parser.add_argument( - "--connection-mode", - choices=["auto", "localhost_only", "network"], - default=os.getenv("REACHY_CONNECTION_MODE"), - ) - parser.add_argument("--media-backend", default=os.getenv("REACHY_MEDIA_BACKEND", "no_media")) - parser.add_argument("--timeout", type=float, default=_env_float("REACHY_TIMEOUT", 5.0)) - return parser - - -def target_from_args(args: argparse.Namespace) -> ReachyTarget: - return ReachyTarget( - host=args.host, - port=args.port, - connection_mode=args.connection_mode or _default_connection_mode(args.host), - media_backend=args.media_backend, - timeout=args.timeout, - ) - - -def run_motion(target: ReachyTarget) -> None: - try: - from reachy_mini import ReachyMini - from reachy_mini.utils import create_head_pose - except ImportError as exc: - raise RuntimeError( - "Reachy Mini SDK is not installed. Install with `uv pip install -e '.[sdk]'` " - "or `uv pip install -e '.[sim]'` for simulator work." - ) from exc - - with ReachyMini( - host=target.host, - port=target.port, - connection_mode=target.connection_mode, - spawn_daemon=False, - media_backend=target.media_backend, - timeout=target.timeout, - ) as mini: - print(f"Connected to Reachy Mini daemon at {target.host}:{target.port}") - print("Moving head and antennas...") - mini.goto_target( - head=create_head_pose(z=20, roll=10, mm=True, degrees=True), - duration=1.0, - ) - mini.goto_target(antennas=[0.6, -0.6], duration=0.3) - mini.goto_target(antennas=[-0.6, 0.6], duration=0.3) - mini.goto_target( - head=create_head_pose(), - antennas=[0.0, 0.0], - duration=1.0, - ) - print("Smoke motion complete.") - - -def main(argv: list[str] | None = None) -> int: - args = build_parser().parse_args(argv) - target = target_from_args(args) - try: - run_motion(target) - except Exception as exc: - print(f"Reachy smoke motion failed: {exc}", file=sys.stderr) - return 1 - return 0 - - -if __name__ == "__main__": - raise SystemExit(main()) diff --git a/projects/reachy-mini-openshell/style.css b/projects/reachy-mini-openshell/style.css new file mode 100644 index 00000000..c8bbe123 --- /dev/null +++ b/projects/reachy-mini-openshell/style.css @@ -0,0 +1,113 @@ +:root { + --bg: #060b1a; + --bg-2: #071023; + --panel: rgba(11, 18, 36, 0.8); + --border: rgba(255, 255, 255, 0.08); + --text: #eaf2ff; + --muted: #9fb6d7; + --accent: #45c4ff; + --accent-2: #5ef0c1; + --shadow: 0 20px 70px rgba(0, 0, 0, 0.45); +} + +* { box-sizing: border-box; } +body { + margin: 0; + min-height: 100vh; + font-family: "Space Grotesk", "Inter", "Segoe UI", sans-serif; + background: radial-gradient(circle at 20% 20%, rgba(69, 196, 255, 0.16), transparent 35%), + radial-gradient(circle at 80% 0%, rgba(94, 240, 193, 0.16), transparent 32%), + linear-gradient(135deg, var(--bg), var(--bg-2)); + color: var(--text); +} + +.ambient { + position: fixed; + inset: 0; + background: radial-gradient(circle at 30% 60%, rgba(255, 255, 255, 0.05), transparent 35%), + radial-gradient(circle at 75% 30%, rgba(69, 196, 255, 0.08), transparent 32%); + filter: blur(60px); + z-index: 0; + pointer-events: none; +} + +.container { + position: relative; + max-width: 600px; + margin: 10vh auto; + padding: 0 24px 40px; + z-index: 1; +} + +.hero { + margin-bottom: 24px; +} +.hero h1 { + margin: 6px 0 6px; + font-size: 32px; + letter-spacing: -0.4px; +} +.subtitle { + margin: 0; + color: var(--muted); + line-height: 1.5; +} +.pill { + display: inline-flex; + align-items: center; + gap: 6px; + padding: 6px 12px; + border-radius: 999px; + background: rgba(94, 240, 193, 0.1); + color: var(--accent-2); + font-size: 12px; + letter-spacing: 0.3px; + border: 1px solid rgba(94, 240, 193, 0.25); +} + +.panel { + background: var(--panel); + border: 1px solid var(--border); + border-radius: 14px; + padding: 18px 18px 16px; + box-shadow: var(--shadow); + backdrop-filter: blur(10px); + margin-top: 16px; +} +.panel-heading { + display: flex; + align-items: center; + justify-content: space-between; + gap: 12px; + margin-bottom: 8px; +} +.panel-heading h2 { + margin: 2px 0; + font-size: 22px; +} +.eyebrow { + margin: 0; + text-transform: uppercase; + font-size: 11px; + letter-spacing: 0.5px; + color: var(--muted); +} +.muted { color: var(--muted); } + +pre { + background: rgba(0, 0, 0, 0.3); + border: 1px solid var(--border); + border-radius: 8px; + padding: 12px 14px; + overflow-x: auto; + margin: 12px 0 0; +} +code { + font-family: "SF Mono", "Fira Code", monospace; + font-size: 13px; + color: var(--accent); +} + +@media (max-width: 760px) { + .hero h1 { font-size: 26px; } +} \ No newline at end of file diff --git a/projects/reachy-mini-openshell/tests/audio/test_head_wobbler.py b/projects/reachy-mini-openshell/tests/audio/test_head_wobbler.py new file mode 100644 index 00000000..853dcfbe --- /dev/null +++ b/projects/reachy-mini-openshell/tests/audio/test_head_wobbler.py @@ -0,0 +1,110 @@ +"""Regression tests for the audio-driven head wobble behaviour.""" + +import math +import time +import base64 +import threading +from typing import Any, List, Tuple +from collections.abc import Callable + +import numpy as np + +from reachy_mini_conversation_app.audio.head_wobbler import HeadWobbler + + +def _make_audio_chunk(duration_s: float = 0.3, frequency_hz: float = 220.0) -> str: + """Generate a base64-encoded mono PCM16 sine wave.""" + sample_rate = 24000 + sample_count = int(sample_rate * duration_s) + t = np.linspace(0, duration_s, sample_count, endpoint=False) + wave = 0.6 * np.sin(2 * math.pi * frequency_hz * t) + pcm = np.clip(wave * np.iinfo(np.int16).max, -32768, 32767).astype(np.int16) + return base64.b64encode(pcm.tobytes()).decode("ascii") + + +def _wait_for(predicate: Callable[[], bool], timeout: float = 0.6) -> bool: + """Poll `predicate` until true or timeout.""" + end_time = time.time() + timeout + while time.time() < end_time: + if predicate(): + return True + time.sleep(0.01) + return False + + +def _start_wobbler() -> Tuple[HeadWobbler, List[Tuple[float, Tuple[float, float, float, float, float, float]]]]: + captured: List[Tuple[float, Tuple[float, float, float, float, float, float]]] = [] + + def capture(offsets: Tuple[float, float, float, float, float, float]) -> None: + captured.append((time.time(), offsets)) + + wobbler = HeadWobbler(set_speech_offsets=capture) + wobbler.start() + return wobbler, captured + + +def test_reset_drops_pending_offsets() -> None: + """Reset should stop wobble output derived from pre-reset audio.""" + wobbler, captured = _start_wobbler() + try: + wobbler.feed(_make_audio_chunk(duration_s=0.35)) + assert _wait_for(lambda: len(captured) > 0), "wobbler did not emit initial offsets" + + pre_reset_count = len(captured) + wobbler.reset() + time.sleep(0.3) + assert len(captured) == pre_reset_count, "offsets continued after reset without new audio" + finally: + wobbler.stop() + + +def test_reset_allows_future_offsets() -> None: + """After reset, fresh audio must still produce wobble offsets.""" + wobbler, captured = _start_wobbler() + try: + wobbler.feed(_make_audio_chunk(duration_s=0.35)) + assert _wait_for(lambda: len(captured) > 0), "wobbler did not emit initial offsets" + + wobbler.reset() + pre_second_count = len(captured) + + wobbler.feed(_make_audio_chunk(duration_s=0.35, frequency_hz=440.0)) + assert _wait_for(lambda: len(captured) > pre_second_count), "no offsets after reset" + assert wobbler._thread is not None and wobbler._thread.is_alive() + finally: + wobbler.stop() + + +def test_reset_during_inflight_chunk_keeps_worker(monkeypatch: Any) -> None: + """Simulate reset during chunk processing to ensure the worker survives.""" + wobbler, captured = _start_wobbler() + ready = threading.Event() + release = threading.Event() + + original_feed = wobbler.sway.feed + + def blocking_feed(pcm, sr): # type: ignore[no-untyped-def] + ready.set() + release.wait(timeout=2.0) + return original_feed(pcm, sr) + + monkeypatch.setattr(wobbler.sway, "feed", blocking_feed) + + try: + wobbler.feed(_make_audio_chunk(duration_s=0.35)) + assert ready.wait(timeout=1.0), "worker thread did not dequeue audio" + + wobbler.reset() + release.set() + + # Allow the worker to finish processing the first chunk (which should be discarded) + time.sleep(0.1) + + assert wobbler._thread is not None and wobbler._thread.is_alive(), "worker thread died after reset" + + pre_second = len(captured) + wobbler.feed(_make_audio_chunk(duration_s=0.35, frequency_hz=440.0)) + assert _wait_for(lambda: len(captured) > pre_second), "no offsets emitted after in-flight reset" + assert wobbler._thread.is_alive() + finally: + wobbler.stop() diff --git a/projects/reachy-mini-openshell/tests/conftest.py b/projects/reachy-mini-openshell/tests/conftest.py new file mode 100644 index 00000000..0e7310d4 --- /dev/null +++ b/projects/reachy-mini-openshell/tests/conftest.py @@ -0,0 +1,15 @@ +"""Pytest configuration for path setup.""" + +import os +import sys +from pathlib import Path + + +PROJECT_ROOT = Path(__file__).resolve().parents[1] +SRC_PATH = PROJECT_ROOT / "src" +if str(SRC_PATH) not in sys.path: + sys.path.insert(0, str(SRC_PATH)) + + +# Make tests reproducible by ignoring machine-specific .env config. +os.environ["REACHY_MINI_SKIP_DOTENV"] = "1" diff --git a/projects/reachy-mini-openshell/tests/test_openai_realtime.py b/projects/reachy-mini-openshell/tests/test_openai_realtime.py new file mode 100644 index 00000000..39a82e3e --- /dev/null +++ b/projects/reachy-mini-openshell/tests/test_openai_realtime.py @@ -0,0 +1,544 @@ +import random +import asyncio +import logging +from typing import Any +from datetime import datetime, timezone +from unittest.mock import MagicMock + +import pytest + +import reachy_mini_conversation_app.openai_realtime as rt_mod +import reachy_mini_conversation_app.tools.background_tool_manager as btm_mod +from reachy_mini_conversation_app.openai_realtime import OpenaiRealtimeHandler, _compute_response_cost +from reachy_mini_conversation_app.tools.core_tools import ToolDependencies +from reachy_mini_conversation_app.tools.background_tool_manager import ToolCallRoutine + + +def _build_handler(loop: asyncio.AbstractEventLoop) -> OpenaiRealtimeHandler: + asyncio.set_event_loop(loop) + deps = ToolDependencies(reachy_mini=MagicMock(), movement_manager=MagicMock()) + return OpenaiRealtimeHandler(deps) + + +def test_format_timestamp_uses_wall_clock() -> None: + """Test that format_timestamp uses wall clock time.""" + loop = asyncio.new_event_loop() + try: + print("Testing format_timestamp...") + handler = _build_handler(loop) + formatted = handler.format_timestamp() + print(f"Formatted timestamp: {formatted}") + finally: + asyncio.set_event_loop(None) + loop.close() + + # Extract year from "[YYYY-MM-DD ...]" + year = int(formatted[1:5]) + assert year == datetime.now(timezone.utc).year + +@pytest.mark.asyncio +async def test_start_up_retries_on_abrupt_close(monkeypatch: Any, caplog: Any) -> None: + """First connection dies with ConnectionClosedError during iteration -> retried. + + Second connection iterates cleanly (no events) -> start_up returns without raising. + Ensures handler clears self.connection at the end. + """ + caplog.set_level(logging.WARNING) + + # Use a local Exception as the module's ConnectionClosedError to avoid ws dependency + FakeCCE = type("FakeCCE", (Exception,), {}) + monkeypatch.setattr(rt_mod, "ConnectionClosedError", FakeCCE) + + # Make asyncio.sleep return immediately (for backoff) + _real_sleep = asyncio.sleep + async def _mock_sleep(*_a: Any, **_kw: Any) -> None: await _real_sleep(0) + monkeypatch.setattr(asyncio, "sleep", _mock_sleep, raising=False) + + attempt_counter = {"n": 0} + + class FakeConn: + """Minimal realtime connection stub.""" + + def __init__(self, mode: str): + self._mode = mode + + class _Session: + async def update(self, **_kw: Any) -> None: return None + self.session = _Session() + + class _InputAudioBuffer: + async def append(self, **_kw: Any) -> None: return None + self.input_audio_buffer = _InputAudioBuffer() + + class _Item: + async def create(self, **_kw: Any) -> None: return None + + class _Conversation: + item = _Item() + self.conversation = _Conversation() + + class _Response: + async def create(self, **_kw: Any) -> None: return None + async def cancel(self, **_kw: Any) -> None: return None + self.response = _Response() + + async def __aenter__(self) -> "FakeConn": return self + async def __aexit__(self, exc_type: Any, exc: Any, tb: Any) -> bool: return False + async def close(self) -> None: return None + + # Async iterator protocol + def __aiter__(self) -> "FakeConn": return self + async def __anext__(self) -> None: + if self._mode == "raise_on_iter": + raise FakeCCE("abrupt close (simulated)") + raise StopAsyncIteration # clean exit (no events) + + class FakeRealtime: + def connect(self, **_kw: Any) -> FakeConn: + attempt_counter["n"] += 1 + mode = "raise_on_iter" if attempt_counter["n"] == 1 else "clean" + return FakeConn(mode) + + class FakeClient: + def __init__(self, **_kw: Any) -> None: self.realtime = FakeRealtime() + + # Patch the OpenAI client used by the handler + monkeypatch.setattr(rt_mod, "AsyncOpenAI", FakeClient) + + # Build handler with minimal deps + deps = ToolDependencies(reachy_mini=MagicMock(), movement_manager=MagicMock()) + handler = rt_mod.OpenaiRealtimeHandler(deps) + + # Run: should retry once and exit cleanly + await handler.start_up() + + # Validate: two attempts total (fail -> retry -> succeed), and connection cleared + assert attempt_counter["n"] == 2 + assert handler.connection is None + + # Optional: confirm we logged the unexpected close once + warnings = [r for r in caplog.records if r.levelname == "WARNING" and "closed unexpectedly" in r.msg] + assert len(warnings) == 1 + +# ---- Cost calculation tests ---- + + +def _make_usage( + audio_in: int | None = 0, + text_in: int | None = 0, + image_in: int | None = 0, + audio_out: int | None = 0, + text_out: int | None = 0, + has_input: bool = True, + has_output: bool = True, +) -> MagicMock: + """Build a fake usage object matching the OpenAI response.usage shape.""" + usage = MagicMock() + if has_input: + inp = MagicMock() + inp.audio_tokens = audio_in + inp.text_tokens = text_in + inp.image_tokens = image_in + usage.input_token_details = inp + else: + usage.input_token_details = None + if has_output: + out = MagicMock() + out.audio_tokens = audio_out + out.text_tokens = text_out + usage.output_token_details = out + else: + usage.output_token_details = None + return usage + + +@pytest.mark.parametrize( + "usage_kwargs, expect_positive", + [ + # All token types present → positive cost + ({"audio_in": 1000, "text_in": 2000, "image_in": 500, "audio_out": 800, "text_out": 300}, True), + # All None tokens → must not crash + ({"audio_in": None, "text_in": None, "image_in": None, "audio_out": None, "text_out": None}, False), + # Mix of None and valid ints + ({"audio_in": None, "text_in": 500, "image_in": None, "audio_out": 1000, "text_out": None}, True), + # Missing input/output details entirely + ({"has_input": False, "has_output": False}, False), + ], + ids=["normal", "all_none", "mixed", "missing_details"], +) +def test_compute_response_cost(usage_kwargs: dict[str, Any], expect_positive: bool) -> None: + """Verify _compute_response_cost handles various token combinations without crashing.""" + usage = _make_usage(**usage_kwargs) + cost = _compute_response_cost(usage) + if expect_positive: + assert cost > 0 + else: + assert cost == 0.0 + + +# ---- Stress test: response.create rejection + retry ---- + + +@pytest.mark.asyncio +async def test_response_sender_retries_on_active_response_rejection(monkeypatch: Any, caplog: Any) -> None: + """Stress test: response.create rejection + retry via real event processing. + + Tool results (is_idle_tool_call=False) queue response.create calls via + _safe_response_create. When the server rejects some with + ``conversation_already_has_active_response``, the error event flows through + the event handler and _response_sender_loop retries the rejected request. + + The full _run_realtime_session event loop runs so that the error-handling + code path (setting _last_response_rejected) is exercised by real event + processing, not mocked out. + """ + caplog.set_level(logging.DEBUG) + + FakeCCE = type("FakeCCE", (Exception,), {}) + monkeypatch.setattr(rt_mod, "ConnectionClosedError", FakeCCE) + monkeypatch.setattr(rt_mod, "get_session_instructions", lambda: "test") + monkeypatch.setattr(rt_mod, "get_session_voice", lambda: "alloy") + monkeypatch.setattr(rt_mod, "get_tool_specs", lambda: []) + + N_TOOL_RESULTS = 400 + REJECT_CALL_NUMBERS = {1, 3, 5, 10, 25, 50, 75, 100, 150, 200, 300, 399} + EXPECTED_TOTAL_CALLS = N_TOOL_RESULTS + len(REJECT_CALL_NUMBERS) + + event_queue: asyncio.Queue[Any] = asyncio.Queue() + response_create_log: list[tuple[int, dict[str, Any]]] = [] + handler_ref: list[Any] = [] + + # ---- Fake event / error objects mirroring the OpenAI SDK shapes ---- + + class FakeError: + def __init__(self, message: str, code: str) -> None: + self.message = message + self.code = code + self.type = "invalid_request_error" + self.event_id = None + self.param = None + + def __repr__(self) -> str: + return ( + f"RealtimeError(message='{self.message}', type='{self.type}', " + f"code='{self.code}', event_id=None, param=None)" + ) + + class FakeEvent: + def __init__(self, etype: str, **kwargs: Any) -> None: + self.type = etype + for k, v in kwargs.items(): + setattr(self, k, v) + + # ---- Fake connection components ---- + + class FakeResponseAPI: + """Mimics connection.response. + + Pushes server events into the shared event_queue so they flow + through the real event-handling code. Also guards the serialization + invariant: every create() must arrive when no response is active. + """ + + def __init__(self) -> None: + self._call_count = 0 + self._serialization_violations: list[int] = [] + + async def create(self, **kwargs: Any) -> None: + self._call_count += 1 + n = self._call_count + response_create_log.append((n, kwargs)) + + h = handler_ref[0] + + # Real backend rejects when a response is already active. + if not h._response_done_event.is_set(): + self._serialization_violations.append(n) + await event_queue.put( + FakeEvent( + "error", + error=FakeError( + message=( + f"Conversation already has an active response in " + f"progress: resp_fake{n}. Wait until the response " + f"is finished before creating a new one." + ), + code="conversation_already_has_active_response", + ), + ) + ) + await asyncio.sleep(0) + await event_queue.put( + FakeEvent("response.done", response=MagicMock()) + ) + return + + # Intentional rejections (simulating a race where another + # response sneaks in right after our check). + if n in REJECT_CALL_NUMBERS: + await event_queue.put( + FakeEvent( + "error", + error=FakeError( + message=( + f"Conversation already has an active response in " + f"progress: resp_fake{n}. Wait until the response " + f"is finished before creating a new one." + ), + code="conversation_already_has_active_response", + ), + ) + ) + await asyncio.sleep(0) + else: + await event_queue.put(FakeEvent("response.created")) + + await event_queue.put( + FakeEvent("response.done", response=MagicMock()) + ) + + + async def cancel(self, **_kw: Any) -> None: + pass + + fake_response_api = FakeResponseAPI() + + class FakeSession: + async def update(self, **_kw: Any) -> None: + pass + + class FakeInputAudioBuffer: + async def append(self, **_kw: Any) -> None: + pass + + class FakeItem: + async def create(self, **_kw: Any) -> None: + pass + + class FakeConversation: + item = FakeItem() + + class FakeConn: + session = FakeSession() + input_audio_buffer = FakeInputAudioBuffer() + conversation = FakeConversation() + response = fake_response_api + + async def __aenter__(self) -> "FakeConn": + return self + + async def __aexit__(self, *_a: Any) -> bool: + return False + + async def close(self) -> None: + pass + + def __aiter__(self) -> "FakeConn": + return self + + async def __anext__(self) -> FakeEvent: + event: FakeEvent = await event_queue.get() + if event is None: # sentinel → end iteration + raise StopAsyncIteration + return event + + class FakeRealtime: + def connect(self, **_kw: Any) -> FakeConn: + return FakeConn() + + class FakeClient: + def __init__(self, **_kw: Any) -> None: + self.realtime = FakeRealtime() + + monkeypatch.setattr(rt_mod, "AsyncOpenAI", FakeClient) + + # Patch dispatch_tool_call so tools complete with a result. + async def _fake_dispatch( + tool_name: str, args_json: str, deps: Any, **_kw: Any + ) -> dict[str, Any]: + await asyncio.sleep(random.uniform(0.3, 0.5)) + return {"ok": True, "tool": tool_name} + + monkeypatch.setattr(btm_mod, "dispatch_tool_call", _fake_dispatch) + + # ---- Build handler and start the full realtime session ---- + + deps = ToolDependencies(reachy_mini=MagicMock(), movement_manager=MagicMock()) + handler = rt_mod.OpenaiRealtimeHandler(deps) + handler_ref.append(handler) + + asyncio.create_task(handler.start_up()) + + # ---- Start tools via the real BackgroundToolManager pipeline ---- + # start_tool → _run_tool → notification queue → listener → _handle_tool_result + + for i in range(N_TOOL_RESULTS): + await handler.tool_manager.start_tool( + call_id=f"call_{i}", + tool_call_routine=ToolCallRoutine( + tool_name="test_tool", + args_json_str=f'{{"index": {i}}}', + deps=deps, + ), + is_idle_tool_call=False, + ) + + # Yield so spawned tool tasks, the listener, and the sender can drain. + await asyncio.sleep(5) + + # ---- Tear down ---- + + await event_queue.put(None) # sentinel stops event iteration + + await handler.shutdown() + + + # ---- Assertions ---- + + # Serialization: every response.create() must have been called only when + # no response was in-flight (_response_done_event was set). Any violation + # means the sender fired a new request before the previous one finished. + assert fake_response_api._serialization_violations == [], ( + f"response.create() was called while a response was still active on " + f"call(s) {fake_response_api._serialization_violations}" + ) + + # Total response.create() calls = tool results + retries for rejected ones + assert fake_response_api._call_count == EXPECTED_TOTAL_CALLS, ( + f"Expected {EXPECTED_TOTAL_CALLS} response.create calls " + f"({N_TOOL_RESULTS} results + {len(REJECT_CALL_NUMBERS)} retries), " + f"got {fake_response_api._call_count}" + ) + + # The error event handler must have set _last_response_rejected for each + # rejection (the log message comes from the event handler code path). + rejection_logs = [ + r for r in caplog.records + if "worker will retry" in getattr(r, "msg", "") + ] + assert len(rejection_logs) == len(REJECT_CALL_NUMBERS), ( + f"Expected {len(REJECT_CALL_NUMBERS)} rejection entries from error handler, " + f"got {len(rejection_logs)}" + ) + + # The sender loop must have retried after each rejection. + retry_logs = [ + r for r in caplog.records + if "response.create was rejected; retrying" in getattr(r, "msg", "") + ] + assert len(retry_logs) == len(REJECT_CALL_NUMBERS), ( + f"Expected {len(REJECT_CALL_NUMBERS)} retry entries from sender loop, " + f"got {len(retry_logs)}" + ) + + +# ---- Response creation timeout guard tests ---- + + +@pytest.mark.asyncio +async def test_response_sender_loop_times_out_waiting_for_response_done( + monkeypatch: Any, caplog: Any, +) -> None: + """If response.done is never received the sender loop should time out. + + Rather than hang forever, it force-sets the event and moves on. + """ + caplog.set_level(logging.DEBUG) + + monkeypatch.setattr(rt_mod, "_RESPONSE_DONE_TIMEOUT", 0.3) + + deps = ToolDependencies(reachy_mini=MagicMock(), movement_manager=MagicMock()) + handler = rt_mod.OpenaiRealtimeHandler(deps) + + create_count = 0 + + class FakeResponse: + async def create(self, **_kw: Any) -> None: + nonlocal create_count + create_count += 1 + # Simulate response.created clearing the event, but never + # send response.done (so the event stays cleared forever). + handler._response_done_event.clear() + + async def cancel(self, **_kw: Any) -> None: + pass + + fake_conn = MagicMock() + fake_conn.response = FakeResponse() + handler.connection = fake_conn + + # Queue two requests + await handler._safe_response_create(instructions="req1") + await handler._safe_response_create(instructions="req2") + + sender_task = asyncio.create_task(handler._response_sender_loop()) + + # Give enough time for both requests to time out (0.3s each + margin) + await asyncio.sleep(1.5) + + handler.connection = None # signal the loop to exit + handler._response_done_event.set() + await asyncio.wait_for(sender_task, timeout=2.0) + + assert create_count == 2, f"Expected 2 response.create calls, got {create_count}" + + timeout_logs = [ + r for r in caplog.records + if "Timed out waiting for response.done" in r.getMessage() + ] + assert len(timeout_logs) == 2, ( + f"Expected 2 timeout warnings, got {len(timeout_logs)}" + ) + + +@pytest.mark.asyncio +async def test_response_sender_loop_times_out_waiting_for_previous_response( + monkeypatch: Any, caplog: Any, +) -> None: + """If a previous response never completes, the pre-condition wait times out. + + It should force-set the event and proceed to send. + """ + caplog.set_level(logging.DEBUG) + + monkeypatch.setattr(rt_mod, "_RESPONSE_DONE_TIMEOUT", 0.3) + + deps = ToolDependencies(reachy_mini=MagicMock(), movement_manager=MagicMock()) + handler = rt_mod.OpenaiRealtimeHandler(deps) + + # Pretend a response is already in-flight (event cleared) + handler._response_done_event.clear() + + created = asyncio.Event() + + class FakeResponse: + async def create(self, **_kw: Any) -> None: + # Immediately complete the response cycle so the loop can finish + handler._response_done_event.set() + created.set() + + async def cancel(self, **_kw: Any) -> None: + pass + + fake_conn = MagicMock() + fake_conn.response = FakeResponse() + handler.connection = fake_conn + + await handler._safe_response_create(instructions="waiting_req") + + sender_task = asyncio.create_task(handler._response_sender_loop()) + + # Wait for the request to be sent (after timing out on the pre-condition) + await asyncio.wait_for(created.wait(), timeout=2.0) + + handler.connection = None + handler._response_done_event.set() + await asyncio.wait_for(sender_task, timeout=2.0) + + timeout_logs = [ + r for r in caplog.records + if "Timed out waiting for previous response" in r.getMessage() + ] + assert len(timeout_logs) == 1, ( + f"Expected 1 pre-condition timeout warning, got {len(timeout_logs)}" + ) diff --git a/projects/reachy-mini-openshell/tests/test_reachy_constructors.py b/projects/reachy-mini-openshell/tests/test_reachy_constructors.py deleted file mode 100644 index 59547309..00000000 --- a/projects/reachy-mini-openshell/tests/test_reachy_constructors.py +++ /dev/null @@ -1,85 +0,0 @@ -from __future__ import annotations - -import os -import sys -import types -import unittest -from contextlib import contextmanager, redirect_stdout -from io import StringIO -from unittest.mock import patch - -from reachy_openshell import backend, smoke - - -class FakeReachyMini: - calls: list[dict[str, object]] = [] - - def __init__(self, **kwargs: object) -> None: - self.calls.append(kwargs) - - def __enter__(self) -> "FakeReachyMini": - return self - - def __exit__(self, *_args: object) -> None: - return None - - def goto_target(self, **_kwargs: object) -> None: - return None - - -@contextmanager -def fake_reachy_modules(): - original = { - name: sys.modules.get(name) - for name in ("reachy_mini", "reachy_mini.utils") - } - - reachy_module = types.ModuleType("reachy_mini") - reachy_module.ReachyMini = FakeReachyMini - utils_module = types.ModuleType("reachy_mini.utils") - utils_module.create_head_pose = lambda **kwargs: {"head_pose": kwargs} - - sys.modules["reachy_mini"] = reachy_module - sys.modules["reachy_mini.utils"] = utils_module - FakeReachyMini.calls = [] - - try: - yield - finally: - for name, module in original.items(): - if module is None: - sys.modules.pop(name, None) - else: - sys.modules[name] = module - - -class ReachyConstructorTests(unittest.TestCase): - def test_backend_smoke_motion_disables_media_by_default(self) -> None: - with patch.dict(os.environ, {}, clear=True): - settings = backend.Settings.from_env() - - with fake_reachy_modules(): - backend.run_smoke_motion(settings) - - self.assertEqual(FakeReachyMini.calls[0]["media_backend"], "no_media") - - def test_smoke_cli_disables_media_by_default(self) -> None: - with patch.dict(os.environ, {}, clear=True): - target = smoke.target_from_args(smoke.build_parser().parse_args([])) - - with fake_reachy_modules(), redirect_stdout(StringIO()): - smoke.run_motion(target) - - self.assertEqual(FakeReachyMini.calls[0]["media_backend"], "no_media") - - def test_smoke_cli_uses_network_mode_for_non_local_cli_host(self) -> None: - with patch.dict(os.environ, {}, clear=True): - target = smoke.target_from_args( - smoke.build_parser().parse_args(["--host", "host.openshell.internal"]) - ) - - self.assertEqual(target.connection_mode, "network") - - -if __name__ == "__main__": - unittest.main() diff --git a/projects/reachy-mini-openshell/tests/tools/test_background_tool_manager.py b/projects/reachy-mini-openshell/tests/tools/test_background_tool_manager.py new file mode 100644 index 00000000..90b7a7f1 --- /dev/null +++ b/projects/reachy-mini-openshell/tests/tools/test_background_tool_manager.py @@ -0,0 +1,545 @@ +"""Tests for BackgroundToolManager.""" + +from __future__ import annotations +import asyncio +from typing import Any +from unittest.mock import AsyncMock, MagicMock + +import pytest + +from reachy_mini_conversation_app.tools.tool_constants import ToolState +from reachy_mini_conversation_app.tools.background_tool_manager import ( + ToolProgress, + BackgroundTool, + ToolCallRoutine, + ToolNotification, + BackgroundToolManager, +) + + +# --------------------------------------------------------------------------- +# Helpers +# --------------------------------------------------------------------------- + + +def _make_routine( + tool_name: str = "test_tool", + result: dict[str, Any] | None = None, + error: Exception | None = None, + delay: float = 0.0, +) -> ToolCallRoutine: + """Create a mock ToolCallRoutine that returns *result* or raises *error*. + + If *delay* > 0, the routine will sleep for that many seconds before + returning / raising so we can test cancellation and progress. + + Mirrors the contract of ``_dispatch_tool_call`` in core_tools: exceptions + (including ``CancelledError``) are caught and returned as + ``{"error": "..."}`` dicts so that ``_run_tool`` never sees a raw raise. + """ + routine = MagicMock(spec=ToolCallRoutine) + routine.tool_name = tool_name + routine.args_json_str = "{}" + + async def _call(manager: BackgroundToolManager) -> dict[str, Any]: + try: + if delay: + await asyncio.sleep(delay) + if error is not None: + raise error + return result or {"ok": True} + except asyncio.CancelledError: + return {"error": "Tool cancelled"} + except Exception as e: + return {"error": f"{type(e).__name__}: {e}"} + + routine.__call__ = _call # type: ignore[method-assign] + routine.side_effect = _call + return routine + + +# --------------------------------------------------------------------------- +# Model / data-class sanity checks +# --------------------------------------------------------------------------- + + +class TestToolProgress: + """Validate ToolProgress construction and bounds.""" + + def test_valid_progress(self) -> None: + """Accept valid progress values and messages.""" + p = ToolProgress(progress=0.5, message="halfway") + assert p.progress == 0.5 + assert p.message == "halfway" + + def test_bounds(self) -> None: + """Allow 0.0 and 1.0 as boundary values.""" + assert ToolProgress(progress=0.0).progress == 0.0 + assert ToolProgress(progress=1.0).progress == 1.0 + + def test_out_of_bounds_raises(self) -> None: + """Reject progress values outside [0, 1].""" + with pytest.raises(Exception): + ToolProgress(progress=-0.1) + with pytest.raises(Exception): + ToolProgress(progress=1.1) + + +class TestToolNotification: + """Validate ToolNotification construction.""" + + def test_creation(self) -> None: + """Create a notification and verify its fields.""" + n = ToolNotification( + id="abc", + tool_name="my_tool", + is_idle_tool_call=False, + status=ToolState.COMPLETED, + result={"data": 1}, + ) + assert n.id == "abc" + assert n.status == ToolState.COMPLETED + assert n.result == {"data": 1} + assert n.error is None + + +class TestBackgroundTool: + """Validate BackgroundTool helpers.""" + + def test_tool_id(self) -> None: + """Verify the composite tool_id property includes started_at.""" + t = BackgroundTool( + id="123", + tool_name="weather", + is_idle_tool_call=False, + status=ToolState.RUNNING, + ) + assert t.tool_id == f"weather-123-{t.started_at}" + + def test_get_notification(self) -> None: + """Convert a BackgroundTool to a ToolNotification.""" + t = BackgroundTool( + id="1", + tool_name="t", + is_idle_tool_call=True, + status=ToolState.COMPLETED, + result={"x": 1}, + error=None, + ) + n = t.get_notification() + assert isinstance(n, ToolNotification) + assert n.id == "1" + assert n.tool_name == "t" + assert n.is_idle_tool_call is True + assert n.status == ToolState.COMPLETED + assert n.result == {"x": 1} + + +# --------------------------------------------------------------------------- +# BackgroundToolManager +# --------------------------------------------------------------------------- + + +@pytest.fixture +def manager() -> BackgroundToolManager: + """Return a fresh BackgroundToolManager for each test.""" + return BackgroundToolManager() + + +class TestSetLoop: + """Verify event-loop assignment via set_loop.""" + + @pytest.mark.asyncio + async def test_set_loop_uses_running_loop(self, manager: BackgroundToolManager) -> None: + """Default to the current running loop.""" + manager.set_loop() + assert manager._loop is asyncio.get_running_loop() + + def test_set_loop_explicit(self, manager: BackgroundToolManager) -> None: + """Accept an explicitly provided loop.""" + loop = asyncio.new_event_loop() + try: + manager.set_loop(loop) + assert manager._loop is loop + finally: + loop.close() + + def test_set_loop_creates_new_when_no_running(self, manager: BackgroundToolManager) -> None: + """When called outside an async context it falls back to a new loop.""" + manager.set_loop() + assert manager._loop is not None + + +class TestStartTool: + """Verify tool registration via start_tool.""" + + @pytest.mark.asyncio + async def test_start_registers_tool(self, manager: BackgroundToolManager) -> None: + """Register a tool and verify its initial state.""" + routine = _make_routine("greet") + bg = await manager.start_tool( + call_id="c1", + tool_call_routine=routine, + is_idle_tool_call=False, + ) + assert bg.tool_name == "greet" + assert bg.id == "c1" + assert bg.status == ToolState.RUNNING + assert manager.get_tool(bg.tool_id) is bg + + # Let the task finish + await asyncio.sleep(0.05) + + @pytest.mark.asyncio + async def test_start_with_progress(self, manager: BackgroundToolManager) -> None: + """Initialize progress tracking when requested.""" + routine = _make_routine("slow", delay=0.1) + bg = await manager.start_tool( + call_id="c2", + tool_call_routine=routine, + is_idle_tool_call=True, + with_progress=True, + ) + assert bg.progress is not None + assert bg.progress.progress == 0.0 + await asyncio.sleep(0.15) + + +class TestRunToolLifecycle: + """Test _run_tool via start_tool (the public entry point).""" + + @pytest.mark.asyncio + async def test_successful_completion(self, manager: BackgroundToolManager) -> None: + """Complete a tool and verify result, status, and notification.""" + routine = _make_routine("ok_tool", result={"answer": 42}) + bg = await manager.start_tool("c1", routine, is_idle_tool_call=False) + + # Wait for the task to finish + await asyncio.sleep(0.05) + + assert bg.status == ToolState.COMPLETED + assert bg.result == {"answer": 42} + assert bg.completed_at is not None + assert bg.error is None + + # Notification should be queued + notification = manager._notification_queue.get_nowait() + assert notification.status == ToolState.COMPLETED + + @pytest.mark.asyncio + async def test_tool_failure(self, manager: BackgroundToolManager) -> None: + """Mark a tool as FAILED when it raises an exception.""" + routine = _make_routine("bad_tool", error=ValueError("boom")) + bg = await manager.start_tool("c1", routine, is_idle_tool_call=False) + + await asyncio.sleep(0.05) + + assert bg.status == ToolState.FAILED + assert "ValueError: boom" in (bg.error or "") + assert bg.completed_at is not None + + notification = manager._notification_queue.get_nowait() + assert notification.status == ToolState.FAILED + + @pytest.mark.asyncio + async def test_tool_cancellation(self, manager: BackgroundToolManager) -> None: + """Cancel a running tool and verify CANCELLED status.""" + routine = _make_routine("long_tool", delay=10.0) + bg = await manager.start_tool("c1", routine, is_idle_tool_call=False) + + # Give the task a moment to start, then cancel + await asyncio.sleep(0.02) + cancelled = await manager.cancel_tool(bg.tool_id) + assert cancelled is True + + # Let cancellation propagate + await asyncio.sleep(0.05) + + assert bg.status == ToolState.CANCELLED + assert bg.error == "Tool cancelled" + assert bg.completed_at is not None + + +class TestUpdateProgress: + """Verify progress updates on running tools.""" + + @pytest.mark.asyncio + async def test_update_progress_success(self, manager: BackgroundToolManager) -> None: + """Update progress value and message on a tracked tool.""" + routine = _make_routine("prog", delay=0.5) + bg = await manager.start_tool("c1", routine, is_idle_tool_call=False, with_progress=True) + + ok = await manager.update_progress(bg.tool_id, 0.5, "half done") + assert ok is True + assert bg.progress is not None + assert bg.progress.progress == 0.5 + assert bg.progress.message == "half done" + + # Cancel to clean up + await manager.cancel_tool(bg.tool_id) + await asyncio.sleep(0.05) + + @pytest.mark.asyncio + async def test_update_progress_clamps(self, manager: BackgroundToolManager) -> None: + """Clamp out-of-range progress values to [0, 1].""" + routine = _make_routine("prog", delay=0.5) + bg = await manager.start_tool("c1", routine, is_idle_tool_call=False, with_progress=True) + + await manager.update_progress(bg.tool_id, 1.5) + assert bg.progress is not None + assert bg.progress.progress == 1.0 + + await manager.update_progress(bg.tool_id, -0.5) + assert bg.progress.progress == 0.0 + + await manager.cancel_tool(bg.tool_id) + await asyncio.sleep(0.05) + + @pytest.mark.asyncio + async def test_update_progress_unknown_tool(self, manager: BackgroundToolManager) -> None: + """Return False for an unknown tool_id.""" + ok = await manager.update_progress("nonexistent", 0.5) + assert ok is False + + @pytest.mark.asyncio + async def test_update_progress_no_tracking(self, manager: BackgroundToolManager) -> None: + """Return False when progress tracking is disabled.""" + routine = _make_routine("fast", delay=0.5) + bg = await manager.start_tool("c1", routine, is_idle_tool_call=False, with_progress=False) + + ok = await manager.update_progress(bg.tool_id, 0.5) + assert ok is False + + await manager.cancel_tool(bg.tool_id) + await asyncio.sleep(0.05) + + +class TestCancelTool: + """Verify tool cancellation behaviour.""" + + @pytest.mark.asyncio + async def test_cancel_nonexistent(self, manager: BackgroundToolManager) -> None: + """Return False when the tool_id does not exist.""" + result = await manager.cancel_tool("does-not-exist") + assert result is False + + @pytest.mark.asyncio + async def test_cancel_already_completed(self, manager: BackgroundToolManager) -> None: + """Return True when cancelling an already-completed tool.""" + routine = _make_routine("done") + bg = await manager.start_tool("c1", routine, is_idle_tool_call=False) + await asyncio.sleep(0.05) # let it finish + assert bg.status == ToolState.COMPLETED + + # Cancelling a completed tool should return True (not running, no-op) + result = await manager.cancel_tool(bg.tool_id) + assert result is True + + +class TestTimeoutTools: + """Verify automatic timeout of long-running tools.""" + + @pytest.mark.asyncio + async def test_timeout_cancels_old_tools(self, manager: BackgroundToolManager) -> None: + """Cancel tools exceeding max duration.""" + # Use a very short max duration + manager._max_tool_duration_seconds = 0.01 + + routine = _make_routine("slow", delay=10.0) + await manager.start_tool("c1", routine, is_idle_tool_call=False) + + # Wait longer than the timeout + await asyncio.sleep(0.05) + + count = await manager.timeout_tools() + assert count == 1 + + await asyncio.sleep(0.05) + + @pytest.mark.asyncio + async def test_timeout_ignores_recent_tools(self, manager: BackgroundToolManager) -> None: + """Leave recent tools untouched.""" + manager._max_tool_duration_seconds = 9999 + + routine = _make_routine("fast", delay=10.0) + bg = await manager.start_tool("c1", routine, is_idle_tool_call=False) + + count = await manager.timeout_tools() + assert count == 0 + + await manager.cancel_tool(bg.tool_id) + await asyncio.sleep(0.05) + + +class TestCleanupTools: + """Verify cleanup of completed tools from memory.""" + + @pytest.mark.asyncio + async def test_cleanup_removes_old_completed(self, manager: BackgroundToolManager) -> None: + """Remove completed tools past the retention window.""" + manager._max_tool_memory_seconds = 0.01 + + routine = _make_routine("old") + bg = await manager.start_tool("c1", routine, is_idle_tool_call=False) + await asyncio.sleep(0.05) + assert bg.status == ToolState.COMPLETED + + # Wait for the memory retention to expire + await asyncio.sleep(0.05) + + removed = await manager.cleanup_tools() + assert removed == 1 + assert manager.get_tool(bg.tool_id) is None + + @pytest.mark.asyncio + async def test_cleanup_keeps_recent_completed(self, manager: BackgroundToolManager) -> None: + """Keep recently completed tools.""" + manager._max_tool_memory_seconds = 9999 + + routine = _make_routine("recent") + bg = await manager.start_tool("c1", routine, is_idle_tool_call=False) + await asyncio.sleep(0.05) + + removed = await manager.cleanup_tools() + assert removed == 0 + assert manager.get_tool(bg.tool_id) is not None + + @pytest.mark.asyncio + async def test_cleanup_ignores_running(self, manager: BackgroundToolManager) -> None: + """Never remove still-running tools.""" + manager._max_tool_memory_seconds = 0.0 # immediate expiry + + routine = _make_routine("still_going", delay=10.0) + bg = await manager.start_tool("c1", routine, is_idle_tool_call=False) + + removed = await manager.cleanup_tools() + assert removed == 0 + + await manager.cancel_tool(bg.tool_id) + await asyncio.sleep(0.05) + + +class TestGetters: + """Verify tool retrieval helpers.""" + + @pytest.mark.asyncio + async def test_get_tool(self, manager: BackgroundToolManager) -> None: + """Return None for missing tools and the instance for known ones.""" + assert manager.get_tool("nope") is None + + routine = _make_routine("x") + bg = await manager.start_tool("1", routine, is_idle_tool_call=False) + assert manager.get_tool(bg.tool_id) is bg + await asyncio.sleep(0.05) + + @pytest.mark.asyncio + async def test_get_running_tools(self, manager: BackgroundToolManager) -> None: + """Return only tools that are still running.""" + r1 = _make_routine("a", delay=10.0) + r2 = _make_routine("b", delay=10.0) + r3 = _make_routine("c") # finishes immediately + + bg1 = await manager.start_tool("1", r1, is_idle_tool_call=False) + bg2 = await manager.start_tool("2", r2, is_idle_tool_call=False) + await manager.start_tool("3", r3, is_idle_tool_call=False) + await asyncio.sleep(0.05) # let r3 finish + + running = manager.get_running_tools() + assert len(running) == 2 + names = {t.tool_name for t in running} + assert names == {"a", "b"} + + # Clean up + await manager.cancel_tool(bg1.tool_id) + await manager.cancel_tool(bg2.tool_id) + await asyncio.sleep(0.05) + + @pytest.mark.asyncio + async def test_get_all_tools_sorted(self, manager: BackgroundToolManager) -> None: + """Tools are returned most-recent-first.""" + r1 = _make_routine("first") + r2 = _make_routine("second") + + await manager.start_tool("1", r1, is_idle_tool_call=False) + await asyncio.sleep(0.02) # ensure different started_at + await manager.start_tool("2", r2, is_idle_tool_call=False) + + await asyncio.sleep(0.05) + + all_tools = manager.get_all_tools() + assert len(all_tools) == 2 + assert all_tools[0].tool_name == "second" + assert all_tools[1].tool_name == "first" + + @pytest.mark.asyncio + async def test_get_all_tools_limit(self, manager: BackgroundToolManager) -> None: + """Respect the limit parameter on get_all_tools.""" + for i in range(5): + r = _make_routine(f"t{i}") + await manager.start_tool(str(i), r, is_idle_tool_call=False) + + await asyncio.sleep(0.05) + + limited = manager.get_all_tools(limit=3) + assert len(limited) == 3 + + +class TestStartUp: + """Verify start_up bootstraps background tasks.""" + + @pytest.mark.asyncio + async def test_startup_creates_tasks(self, manager: BackgroundToolManager) -> None: + """start_up should create the listener and cleanup background tasks.""" + callback = AsyncMock() + manager.start_up(tool_callbacks=[callback]) + + # Start a tool and let it complete — the listener should invoke the callback + routine = _make_routine("ping") + await manager.start_tool("c1", routine, is_idle_tool_call=False) + await asyncio.sleep(0.1) + + assert callback.call_count == 1 + notification = callback.call_args[0][0] + assert isinstance(notification, ToolNotification) + assert notification.status == ToolState.COMPLETED + + @pytest.mark.asyncio + async def test_startup_multiple_callbacks(self, manager: BackgroundToolManager) -> None: + """Invoke all registered callbacks on completion.""" + cb1 = AsyncMock() + cb2 = AsyncMock() + manager.start_up(tool_callbacks=[cb1, cb2]) + + routine = _make_routine("multi") + await manager.start_tool("c1", routine, is_idle_tool_call=False) + await asyncio.sleep(0.1) + + assert cb1.call_count == 1 + assert cb2.call_count == 1 + + +class TestNotificationQueue: + """Verify notifications are enqueued on tool completion or failure.""" + + @pytest.mark.asyncio + async def test_notifications_queued_on_completion(self, manager: BackgroundToolManager) -> None: + """Queue a COMPLETED notification with the tool result.""" + routine = _make_routine("notif", result={"v": 1}) + await manager.start_tool("c1", routine, is_idle_tool_call=False) + await asyncio.sleep(0.05) + + n = manager._notification_queue.get_nowait() + assert n.tool_name == "notif" + assert n.status == ToolState.COMPLETED + assert n.result == {"v": 1} + + @pytest.mark.asyncio + async def test_notifications_queued_on_failure(self, manager: BackgroundToolManager) -> None: + """Queue a FAILED notification with the error message.""" + routine = _make_routine("fail", error=RuntimeError("oops")) + await manager.start_tool("c1", routine, is_idle_tool_call=False) + await asyncio.sleep(0.05) + + n = manager._notification_queue.get_nowait() + assert n.status == ToolState.FAILED + assert "RuntimeError: oops" in (n.error or "") diff --git a/projects/reachy-mini-openshell/tests/vision/test_processors.py b/projects/reachy-mini-openshell/tests/vision/test_processors.py new file mode 100644 index 00000000..bfde6fad --- /dev/null +++ b/projects/reachy-mini-openshell/tests/vision/test_processors.py @@ -0,0 +1,498 @@ +"""Tests for the vision processing module.""" + +import time +from typing import Any +from unittest.mock import Mock, MagicMock, patch + +import numpy as np +import pytest + +from reachy_mini_conversation_app.vision.processors import ( + VisionConfig, + VisionManager, + VisionProcessor, + initialize_vision_manager, +) + + +def test_vision_config_defaults() -> None: + """Test VisionConfig has sensible defaults.""" + config = VisionConfig() + assert config.vision_interval == 5.0 + assert config.max_new_tokens == 64 + assert config.jpeg_quality == 85 + assert config.max_retries == 3 + assert config.retry_delay == 1.0 + assert config.device_preference == "auto" + + +def test_vision_config_custom_values() -> None: + """Test VisionConfig accepts custom values.""" + config = VisionConfig( + model_path="/custom/path", + vision_interval=10.0, + max_new_tokens=128, + jpeg_quality=95, + max_retries=5, + retry_delay=2.0, + device_preference="cpu", + ) + assert config.model_path == "/custom/path" + assert config.vision_interval == 10.0 + assert config.max_new_tokens == 128 + assert config.jpeg_quality == 95 + assert config.max_retries == 5 + assert config.retry_delay == 2.0 + assert config.device_preference == "cpu" + + + +@pytest.fixture +def mock_torch() -> Any: + """Mock torch module to avoid loading actual models.""" + with patch("reachy_mini_conversation_app.vision.processors.torch") as mock: + mock.cuda.is_available.return_value = False + mock.backends.mps.is_available.return_value = False + mock.float32 = "float32" + mock.bfloat16 = "bfloat16" + yield mock + + +@pytest.fixture +def mock_transformers() -> Any: + """Mock transformers module.""" + with patch("reachy_mini_conversation_app.vision.processors.AutoProcessor") as proc, \ + patch("reachy_mini_conversation_app.vision.processors.AutoModelForImageTextToText") as model: + + # Mock processor + mock_processor = MagicMock() + mock_processor.apply_chat_template.return_value = { + "input_ids": MagicMock(to=lambda x: MagicMock()), + "attention_mask": MagicMock(to=lambda x: MagicMock()), + "pixel_values": MagicMock(to=lambda x: MagicMock()), + } + mock_processor.batch_decode.return_value = ["assistant\nThis is a test description."] + mock_processor.tokenizer.eos_token_id = 2 + proc.from_pretrained.return_value = mock_processor + + # Mock model + mock_model_instance = MagicMock() + mock_model_instance.eval.return_value = None + mock_model_instance.generate.return_value = [[1, 2, 3]] + mock_model_instance.to.return_value = mock_model_instance + model.from_pretrained.return_value = mock_model_instance + + yield {"processor": proc, "model": model} + + +def test_vision_processor_device_selection_cpu(mock_torch: Any) -> None: + """Test VisionProcessor selects CPU when specified.""" + config = VisionConfig(device_preference="cpu") + processor = VisionProcessor(config) + assert processor.device == "cpu" + + +def test_vision_processor_device_selection_cuda_unavailable(mock_torch: Any) -> None: + """Test VisionProcessor falls back to CPU when CUDA unavailable.""" + mock_torch.cuda.is_available.return_value = False + config = VisionConfig(device_preference="cuda") + processor = VisionProcessor(config) + assert processor.device == "cpu" + + +def test_vision_processor_device_selection_cuda_available(mock_torch: Any) -> None: + """Test VisionProcessor selects CUDA when available.""" + mock_torch.cuda.is_available.return_value = True + config = VisionConfig(device_preference="cuda") + processor = VisionProcessor(config) + assert processor.device == "cuda" + + +def test_vision_processor_device_selection_mps_available(mock_torch: Any) -> None: + """Test VisionProcessor selects MPS when available on Apple Silicon.""" + mock_torch.backends.mps.is_available.return_value = True + config = VisionConfig(device_preference="mps") + processor = VisionProcessor(config) + assert processor.device == "mps" + + +def test_vision_processor_device_selection_auto_prefers_mps(mock_torch: Any) -> None: + """Test VisionProcessor auto mode prefers MPS on Apple Silicon.""" + mock_torch.backends.mps.is_available.return_value = True + mock_torch.cuda.is_available.return_value = False + config = VisionConfig(device_preference="auto") + processor = VisionProcessor(config) + assert processor.device == "mps" + + +def test_vision_processor_device_selection_auto_prefers_cuda_over_cpu(mock_torch: Any) -> None: + """Test VisionProcessor auto mode prefers CUDA over CPU.""" + mock_torch.backends.mps.is_available.return_value = False + mock_torch.cuda.is_available.return_value = True + config = VisionConfig(device_preference="auto") + processor = VisionProcessor(config) + assert processor.device == "cuda" + + +def test_vision_processor_initialization(mock_torch: Any, mock_transformers: Any) -> None: + """Test VisionProcessor initializes successfully.""" + config = VisionConfig(model_path="test/model") + processor = VisionProcessor(config) + + assert not processor._initialized + result = processor.initialize() + + assert result is True + assert processor._initialized + mock_transformers["processor"].from_pretrained.assert_called_once_with("test/model") + mock_transformers["model"].from_pretrained.assert_called_once() + + +def test_vision_processor_initialization_failure(mock_torch: Any) -> None: + """Test VisionProcessor handles initialization failure gracefully.""" + with patch("reachy_mini_conversation_app.vision.processors.AutoProcessor") as mock_proc: + mock_proc.from_pretrained.side_effect = Exception("Model not found") + + config = VisionConfig(model_path="invalid/model") + processor = VisionProcessor(config) + result = processor.initialize() + + assert result is False + assert not processor._initialized + + +def test_vision_processor_process_image_not_initialized(mock_torch: Any) -> None: + """Test process_image returns error when model not initialized.""" + processor = VisionProcessor() + test_image = np.zeros((480, 640, 3), dtype=np.uint8) + + result = processor.process_image(test_image) + assert result == "Vision model not initialized" + + +def test_vision_processor_process_image_success(mock_torch: Any, mock_transformers: Any) -> None: + """Test process_image processes an image successfully.""" + with patch("reachy_mini_conversation_app.vision.processors.cv2") as mock_cv2: + # Mock cv2.imencode to return success + mock_cv2.imencode.return_value = (True, np.array([1, 2, 3], dtype=np.uint8)) + mock_cv2.IMWRITE_JPEG_QUALITY = 1 + + processor = VisionProcessor() + processor.initialize() + + test_image = np.zeros((480, 640, 3), dtype=np.uint8) + result = processor.process_image(test_image, "Describe this image.") + + assert isinstance(result, str) + assert result == "This is a test description." + + +def test_vision_processor_process_image_encode_failure(mock_torch: Any, mock_transformers: Any) -> None: + """Test process_image handles image encoding failure.""" + with patch("reachy_mini_conversation_app.vision.processors.cv2") as mock_cv2: + mock_cv2.imencode.return_value = (False, None) + mock_cv2.IMWRITE_JPEG_QUALITY = 1 + + processor = VisionProcessor() + processor.initialize() + + test_image = np.zeros((480, 640, 3), dtype=np.uint8) + result = processor.process_image(test_image) + + assert result == "Failed to encode image" + + +def test_vision_processor_process_image_with_retry(mock_torch: Any, mock_transformers: Any) -> None: + """Test process_image retries on failure.""" + with patch("reachy_mini_conversation_app.vision.processors.cv2") as mock_cv2: + mock_cv2.imencode.return_value = (True, np.array([1, 2, 3], dtype=np.uint8)) + mock_cv2.IMWRITE_JPEG_QUALITY = 1 + + # Set up the OutOfMemoryError to be a proper exception + mock_torch.cuda.OutOfMemoryError = type("OutOfMemoryError", (Exception,), {}) + + processor = VisionProcessor(VisionConfig(max_retries=3, retry_delay=0.01)) + processor.initialize() + + # Make the model generate fail twice, then succeed + call_count = [0] + assert processor.model is not None + original_generate = processor.model.generate + + def failing_generate(*args: Any, **kwargs: Any) -> Any: + call_count[0] += 1 + if call_count[0] < 3: + raise Exception("Temporary failure") + return original_generate(*args, **kwargs) + + processor.model.generate = failing_generate + + test_image = np.zeros((480, 640, 3), dtype=np.uint8) + result = processor.process_image(test_image) + + assert isinstance(result, str) + assert call_count[0] == 3 + + +def test_vision_processor_extract_response_variants() -> None: + """Test _extract_response handles different response formats.""" + processor = VisionProcessor() + + # Test with "assistant\n" marker + result = processor._extract_response("user prompt\nassistant\nThe response text") + assert result == "The response text" + + # Test with "Assistant:" marker + result = processor._extract_response("User: prompt\nAssistant: Another response") + assert result == "Another response" + + # Test fallback to full text + result = processor._extract_response("Just some text without markers") + assert result == "Just some text without markers" + + +def test_vision_processor_get_model_info(mock_torch: Any, mock_transformers: Any) -> None: + """Test get_model_info returns correct information.""" + mock_torch.cuda.is_available.return_value = True + mock_torch.cuda.get_device_properties.return_value.total_memory = 8 * 1024**3 + + processor = VisionProcessor(VisionConfig(model_path="test/model", device_preference="cpu")) + processor.initialize() + + info = processor.get_model_info() + + assert info["initialized"] is True + assert info["device"] == "cpu" + assert info["model_path"] == "test/model" + assert "cuda_available" in info + + +@pytest.fixture +def mock_camera() -> Mock: + """Create a mock camera object.""" + camera = Mock() + camera.get_latest_frame.return_value = np.zeros((480, 640, 3), dtype=np.uint8) + return camera + + +def test_vision_manager_initialization(mock_torch: Any, mock_transformers: Any, mock_camera: Mock) -> None: + """Test VisionManager initializes successfully.""" + config = VisionConfig(vision_interval=2.0) + manager = VisionManager(mock_camera, config) + + assert manager.vision_interval == 2.0 + assert manager.processor._initialized + + +def test_vision_manager_initialization_failure(mock_torch: Any, mock_camera: Mock) -> None: + """Test VisionManager raises error when processor initialization fails.""" + with patch("reachy_mini_conversation_app.vision.processors.AutoProcessor") as mock_proc: + mock_proc.from_pretrained.side_effect = Exception("Model not found") + + with pytest.raises(RuntimeError, match="Vision processor initialization failed"): + VisionManager(mock_camera, VisionConfig()) + + +def test_vision_manager_start_stop(mock_torch: Any, mock_transformers: Any, mock_camera: Mock) -> None: + """Test VisionManager can start and stop.""" + manager = VisionManager(mock_camera, VisionConfig()) + + manager.start() + assert manager._thread is not None + assert manager._thread.is_alive() + assert not manager._stop_event.is_set() + + time.sleep(0.1) # Let thread run briefly + + manager.stop() + assert manager._stop_event.is_set() + assert not manager._thread.is_alive() + + +def test_vision_manager_processes_frames(mock_torch: Any, mock_transformers: Any, mock_camera: Mock) -> None: + """Test VisionManager processes frames at intervals.""" + with patch("reachy_mini_conversation_app.vision.processors.cv2") as mock_cv2: + mock_cv2.imencode.return_value = (True, np.array([1, 2, 3], dtype=np.uint8)) + mock_cv2.IMWRITE_JPEG_QUALITY = 1 + + config = VisionConfig(vision_interval=0.1) # Fast interval for testing + manager = VisionManager(mock_camera, config) + + manager.start() + time.sleep(0.3) # Wait for at least 2 processing cycles + manager.stop() + + # Camera should have been called at least once + assert mock_camera.get_latest_frame.call_count >= 1 + + +def test_vision_manager_handles_none_frame(mock_torch: Any, mock_transformers: Any, mock_camera: Mock) -> None: + """Test VisionManager handles None frame gracefully.""" + mock_camera.get_latest_frame.return_value = None + + config = VisionConfig(vision_interval=0.1) + manager = VisionManager(mock_camera, config) + + manager.start() + time.sleep(0.2) + manager.stop() + + # Verify camera was called but no crashes occurred + assert mock_camera.get_latest_frame.called + + +def test_vision_manager_handles_processing_error(mock_torch: Any, mock_transformers: Any, mock_camera: Mock) -> None: + """Test VisionManager handles processing errors gracefully.""" + with patch("reachy_mini_conversation_app.vision.processors.cv2") as mock_cv2: + mock_cv2.imencode.side_effect = Exception("Processing error") + mock_cv2.IMWRITE_JPEG_QUALITY = 1 + + config = VisionConfig(vision_interval=0.1) + manager = VisionManager(mock_camera, config) + + manager.start() + time.sleep(0.2) + manager.stop() + + # Verify thread stopped gracefully despite errors + assert manager._stop_event.is_set() + + +def test_vision_manager_get_status(mock_torch: Any, mock_transformers: Any, mock_camera: Mock) -> None: + """Test VisionManager get_status returns correct information.""" + manager = VisionManager(mock_camera, VisionConfig(vision_interval=5.0)) + + status = manager.get_status() + + assert "last_processed" in status + assert "processor_info" in status + assert "config" in status + assert status["config"]["interval"] == 5.0 + + +def test_vision_manager_skips_invalid_responses(mock_torch: Any, mock_transformers: Any, mock_camera: Mock) -> None: + """Test VisionManager doesn't update timestamp for invalid responses.""" + with patch("reachy_mini_conversation_app.vision.processors.cv2") as mock_cv2: + mock_cv2.imencode.return_value = (True, np.array([1, 2, 3], dtype=np.uint8)) + mock_cv2.IMWRITE_JPEG_QUALITY = 1 + + # Make processor return invalid response + config = VisionConfig(vision_interval=0.1) + manager = VisionManager(mock_camera, config) + + # Mock the processor's process_image method to return invalid response + with patch.object(manager.processor, 'process_image', return_value="Vision model not initialized"): + initial_time = manager._last_processed_time + + manager.start() + time.sleep(0.2) + manager.stop() + + # Last processed time should not have been updated + assert manager._last_processed_time == initial_time + + +def test_initialize_vision_manager_success(mock_torch: Any, mock_transformers: Any, mock_camera: Mock) -> None: + """Test initialize_vision_manager creates VisionManager successfully.""" + with patch("reachy_mini_conversation_app.vision.processors.snapshot_download") as mock_download, \ + patch("reachy_mini_conversation_app.vision.processors.os.makedirs"), \ + patch("reachy_mini_conversation_app.vision.processors.config") as mock_config: + + mock_config.LOCAL_VISION_MODEL = "test/model" + mock_config.HF_HOME = "/tmp/hf_cache" + + result = initialize_vision_manager(mock_camera) + + assert result is not None + assert isinstance(result, VisionManager) + mock_download.assert_called_once() + + +def test_initialize_vision_manager_download_failure(mock_torch: Any, mock_camera: Mock) -> None: + """Test initialize_vision_manager handles download failure.""" + with patch("reachy_mini_conversation_app.vision.processors.snapshot_download") as mock_download, \ + patch("reachy_mini_conversation_app.vision.processors.os.makedirs"), \ + patch("reachy_mini_conversation_app.vision.processors.config") as mock_config: + + mock_config.LOCAL_VISION_MODEL = "test/model" + mock_config.HF_HOME = "/tmp/hf_cache" + mock_download.side_effect = Exception("Network error") + + result = initialize_vision_manager(mock_camera) + + assert result is None + + +def test_initialize_vision_manager_processor_failure(mock_torch: Any, mock_camera: Mock) -> None: + """Test initialize_vision_manager handles processor initialization failure.""" + with patch("reachy_mini_conversation_app.vision.processors.snapshot_download"), \ + patch("reachy_mini_conversation_app.vision.processors.os.makedirs"), \ + patch("reachy_mini_conversation_app.vision.processors.config") as mock_config, \ + patch("reachy_mini_conversation_app.vision.processors.AutoProcessor") as mock_proc: + + mock_config.LOCAL_VISION_MODEL = "test/model" + mock_config.HF_HOME = "/tmp/hf_cache" + mock_proc.from_pretrained.side_effect = Exception("Model load error") + + result = initialize_vision_manager(mock_camera) + + assert result is None + + +def test_vision_processor_cuda_oom_recovery(mock_torch: Any, mock_transformers: Any) -> None: + """Test VisionProcessor recovers from CUDA OOM errors.""" + with patch("reachy_mini_conversation_app.vision.processors.cv2") as mock_cv2: + mock_cv2.imencode.return_value = (True, np.array([1, 2, 3], dtype=np.uint8)) + mock_cv2.IMWRITE_JPEG_QUALITY = 1 + + processor = VisionProcessor(VisionConfig(max_retries=2, retry_delay=0.01)) + processor.initialize() + processor.device = "cuda" # Force CUDA for this test + + # Make generate raise OOM error + mock_torch.cuda.OutOfMemoryError = type("OutOfMemoryError", (Exception,), {}) + assert processor.model is not None + processor.model.generate.side_effect = mock_torch.cuda.OutOfMemoryError("OOM") + + test_image = np.zeros((480, 640, 3), dtype=np.uint8) + result = processor.process_image(test_image) + + assert "GPU out of memory" in result + mock_torch.cuda.empty_cache.assert_called() + + +def test_vision_processor_cache_cleanup_mps(mock_torch: Any, mock_transformers: Any) -> None: + """Test VisionProcessor cleans up MPS cache after processing.""" + with patch("reachy_mini_conversation_app.vision.processors.cv2") as mock_cv2: + mock_cv2.imencode.return_value = (True, np.array([1, 2, 3], dtype=np.uint8)) + mock_cv2.IMWRITE_JPEG_QUALITY = 1 + + processor = VisionProcessor() + processor.initialize() + processor.device = "mps" # Force MPS for this test + + test_image = np.zeros((480, 640, 3), dtype=np.uint8) + processor.process_image(test_image) + + # Should call mps empty_cache + mock_torch.mps.empty_cache.assert_called() + + +def test_vision_manager_thread_safety(mock_torch: Any, mock_transformers: Any, mock_camera: Mock) -> None: + """Test VisionManager thread safety with multiple start/stop cycles.""" + with patch("reachy_mini_conversation_app.vision.processors.cv2") as mock_cv2: + mock_cv2.imencode.return_value = (True, np.array([1, 2, 3], dtype=np.uint8)) + mock_cv2.IMWRITE_JPEG_QUALITY = 1 + + config = VisionConfig(vision_interval=0.05) + manager = VisionManager(mock_camera, config) + + # Multiple start/stop cycles + for _ in range(3): + manager.start() + time.sleep(0.1) + manager.stop() + time.sleep(0.05) + + # Should not crash or leave dangling threads + assert manager._stop_event.is_set() From 03cc74d687893a36aff05561a53e10019893f259 Mon Sep 17 00:00:00 2001 From: Johnny Greco Date: Wed, 24 Jun 2026 17:50:36 -0400 Subject: [PATCH 05/45] Expand root gitignore --- .gitignore | 112 ++++++++++++++++++++++++++++++++++++++++++++++++++++- 1 file changed, 110 insertions(+), 2 deletions(-) diff --git a/.gitignore b/.gitignore index b7080d0e..f1304db4 100644 --- a/.gitignore +++ b/.gitignore @@ -1,7 +1,115 @@ +# OS and editor noise .DS_Store +Thumbs.db +*.swp +*.swo +*~ +.idea/ +.vscode/ +!.vscode/extensions.json +!.vscode/settings.json + +# Secrets and local environment +.env +.env.* +!.env.example +*.local +*.key +*.pem +*.crt +*.csr + +# Logs +*.log +logs/ +npm-debug.log* +yarn-debug.log* +yarn-error.log* +pnpm-debug.log* + +# Temporary and cache directories .cache/ -.venv/ -.venv-docs/ +.uv-cache/ +.tmp/ +tmp/ +temp/ + +# Python __pycache__/ +*.py[cod] +*$py.class +*.so +.Python +.venv/ +.venv-*/ +venv/ +ENV/ +env/ +pip-wheel-metadata/ +*.egg-info/ +.eggs/ +build/ +dist/ +htmlcov/ +.coverage +.coverage.* +coverage.xml +.pytest_cache/ +.mypy_cache/ +.ruff_cache/ +.pyre/ +.pytype/ +.hypothesis/ +.tox/ +.nox/ +.dmypy.json +dmypy.json +.ipynb_checkpoints/ + +# Rust +target/ +**/*.rs.bk + +# JavaScript and TypeScript +node_modules/ +.npm/ +.pnpm-store/ +.yarn/cache/ +.yarn/unplugged/ +.yarn/build-state.yml +.yarn/install-state.gz +dist/ +build/ +coverage/ +.nyc_output/ +*.tsbuildinfo +*.eslintcache +.vite/ +.turbo/ +.parcel-cache/ +.angular/cache/ +.next/ +.nuxt/ +.svelte-kit/ +.output/ +.vercel/ +.netlify/ +.serverless/ +out/ + +# Static site and docs output public/ site/ +.docusaurus/ +.vitepress/cache/ +.vitepress/dist/ + +# Runtime artifacts +*.pid +*.seed +*.pid.lock + +# Package artifacts +*.tgz +*.tar.gz +*.zip From c5cb9ae369e97f574588076ab54eff021113dd7c Mon Sep 17 00:00:00 2001 From: Johnny Greco Date: Wed, 24 Jun 2026 18:33:49 -0400 Subject: [PATCH 06/45] Fix Reachy Mini dependency sync --- README.md | 2 +- projects/README.md | 2 +- projects/reachy-mini-openshell/README.md | 236 +- projects/reachy-mini-openshell/pyproject.toml | 9 +- projects/reachy-mini-openshell/uv.lock | 2949 +++++++++++++++++ 5 files changed, 3179 insertions(+), 19 deletions(-) create mode 100644 projects/reachy-mini-openshell/uv.lock diff --git a/README.md b/README.md index f54acf22..314544dc 100644 --- a/README.md +++ b/README.md @@ -13,7 +13,7 @@ OpenShell as the runtime. build logs worth sharing. - `docs/dev-notes/authors.json` contains reusable Dev Notes author metadata. - `projects/` contains self-contained research project folders, including the - Reachy Mini OpenShell simulator/backend scaffold. + Reachy OpenShell fork of the Reachy Mini conversation app. - `scripts/render-dev-notes.py` renders Dev Notes cards, post bylines, and navigation entries from post front matter. - `zensical.toml` configures the documentation site. diff --git a/projects/README.md b/projects/README.md index 998778ed..21bd5190 100644 --- a/projects/README.md +++ b/projects/README.md @@ -4,4 +4,4 @@ This directory contains self-contained research projects. Each project should li Current projects: -- `reachy-mini-openshell`: Reachy Mini simulator/backend research for running the backend inside an OpenShell runtime. +- `reachy-mini-openshell`: OpenShell-oriented fork of the Reachy Mini conversation app. diff --git a/projects/reachy-mini-openshell/README.md b/projects/reachy-mini-openshell/README.md index de3e35db..ef70d72e 100644 --- a/projects/reachy-mini-openshell/README.md +++ b/projects/reachy-mini-openshell/README.md @@ -10,44 +10,250 @@ tags: - reachy_mini_python_app --- -# Reachy OpenShell +# 🤖 Reachy OpenShell -Reachy OpenShell is a locked-profile fork of the Reachy Mini conversation app -for OpenShell research. +Reachy OpenShell is an OpenShell-oriented fork of the Reachy Mini conversation +app. The repository now uses the default Reachy conversation-app package shape +generated by: -## Customize +```bash +reachy-mini-app-assistant create --template conversation +``` -The app is locked to: +The Python package and command names intentionally match that template: -```text -src/reachy_mini_conversation_app/profiles/_reachy_mini_conversation_app_locked_profile +- package: `reachy_mini_conversation_app` +- module entry point: `python -m reachy_mini_conversation_app` +- console script: `reachy-mini-conversation-app` +- Reachy Mini Apps entry point: `reachy_mini_conversation_app` + +The app is no longer the old `reachy_openshell` smoke/backend scaffold. There is +no standalone backend server on port `8080`, no `reachy_openshell.backend`, and +no `reachy_openshell.smoke` module. Runtime communication goes through the +Reachy Mini SDK and daemon, while the conversation UI is provided by Gradio or +the Reachy Mini app shell. + +## What Is Here + +This project contains: + +- a forked Reachy Mini voice conversation app +- OpenAI Realtime audio conversation support +- Reachy Mini movement, dance, emotion, and look-around tools +- a locked OpenShell profile for instructions and tool selection +- optional camera, local vision, YOLO head-tracking, and MediaPipe head-tracking + integrations + +## Requirements + +- Python 3.10, 3.11, or 3.12. The recommended local version is Python 3.12. +- `uv` for the recommended local workflow +- Reachy Mini SDK 1.8.0, installed through this project. This is pinned to the + version compatible with the forked conversation-app dependency stack. +- a running Reachy Mini daemon, either connected to hardware or started in + simulator mode +- an OpenAI API key for conversation + +## Install + +From the repository root: + +```bash +cd projects/reachy-mini-openshell +uv venv --python 3.12 +source .venv/bin/activate +uv sync +cp .env.example .env ``` -That folder is the customization surface: +Then edit `.env` and set: + +```bash +OPENAI_API_KEY=your_api_key_here +``` + +If you are not using `uv`, install the app in editable mode from the project +directory: + +```bash +python -m venv .venv +source .venv/bin/activate +python -m pip install -e . +``` -- `instructions.txt`: system prompt for the assistant -- `tools.txt`: explicit tool allow-list -- Python files in that folder: profile-local tools +For development tools and tests: + +```bash +uv sync --group dev +``` + +The checked-in uv resolution currently targets macOS/Darwin development. If the +app is later deployed from this repo on Linux, revisit `[tool.uv].environments` +and regenerate `uv.lock` for that platform. + +## Optional Dependencies + +The active optional dependency groups are vision-related only: + +```bash +uv sync --extra local_vision +uv sync --extra yolo_vision +uv sync --extra mediapipe_vision +uv sync --extra all_vision +``` + +With `pip`, use the equivalent editable installs: + +```bash +python -m pip install -e '.[local_vision]' +python -m pip install -e '.[yolo_vision]' +python -m pip install -e '.[mediapipe_vision]' +python -m pip install -e '.[all_vision]' +``` + +There are no `backend` or `sim` extras anymore. The previous backend extra +belonged to the deleted scaffold, and simulator support is provided by the +Reachy Mini daemon/runtime rather than a project extra. + +## Configuration + +The app loads `.env` from the current directory or a parent directory unless +`REACHY_MINI_SKIP_DOTENV=1` is set. + +Supported environment variables: + +- `OPENAI_API_KEY`: API key used by OpenAI Realtime. +- `MODEL_NAME`: Realtime model name. Defaults to `gpt-realtime`. +- `LOCAL_VISION_MODEL`: Hugging Face model used with `--local-vision`. +- `HF_HOME`: Hugging Face cache directory. Defaults to `./cache`. +- `HF_TOKEN`: optional Hugging Face token for gated models. + +When running with Gradio, the UI also includes an OpenAI API key field. The +bundled Reachy Mini settings UI can store and validate the key when the app is +run through the Reachy Mini app shell. ## Run Locally -Start the Reachy Mini daemon first. For the simulator baseline: +Start the Reachy Mini daemon first. For the local simulator baseline: ```bash reachy-mini-daemon --sim --scene minimal --headless --no-media --fastapi-host 127.0.0.1 --fastapi-port 8000 --dataset-update-interval 0 ``` +You can verify the daemon separately at: + +```text +http://127.0.0.1:8000/api/daemon/status +``` + Then run the conversation app: ```bash python -m reachy_mini_conversation_app --gradio --no-camera ``` -The app also installs a console script: +The installed console script is equivalent: ```bash reachy-mini-conversation-app --gradio --no-camera ``` -Simulation mode auto-enables Gradio; `--gradio` is included here so the expected -browser interface is explicit. +In simulator mode, the app auto-enables Gradio. The examples still pass +`--gradio` so the expected browser interface is explicit. Gradio usually opens +at: + +```text +http://127.0.0.1:7860/ +``` + +If port `7860` is busy, Gradio may choose another available local port and print +that URL in the terminal. + +## Runtime Flags + +Useful app flags: + +- `--gradio`: launch the browser conversation UI. +- `--no-camera`: disable camera usage. This is the recommended simulator + baseline. +- `--head-tracker yolo`: enable YOLO head tracking. Requires the `yolo_vision` + extra. +- `--head-tracker mediapipe`: enable MediaPipe head tracking. Requires the + `mediapipe_vision` extra. +- `--local-vision`: use a local vision model instead of Realtime vision. + Requires the `local_vision` extra. +- `--robot-name `: connect to a daemon started with the same + `--robot-name`. +- `--debug`: enable debug logging. + +Examples: + +```bash +python -m reachy_mini_conversation_app --gradio --no-camera +python -m reachy_mini_conversation_app --gradio --head-tracker yolo +python -m reachy_mini_conversation_app --gradio --local-vision +python -m reachy_mini_conversation_app --gradio --robot-name reachy-mini-a +``` + +## Locked Profile + +OpenShell customization lives in the locked profile: + +```text +src/reachy_mini_conversation_app/profiles/_reachy_mini_conversation_app_locked_profile +``` + +That folder is the customization surface: + +- `instructions.txt`: the system prompt for the assistant +- `tools.txt`: the explicit allow-list of profile tools +- Python files in the folder: profile-local tool implementations + +The current profile allows: + +```text +dance +stop_dance +play_emotion +stop_emotion +sweep_look +``` + +`sweep_look` is implemented in the locked profile. The other allowed tools come +from the app's built-in tool set. The tool loader also includes required system +tools automatically. + +## Validate Changes + +Useful local checks: + +```bash +python -m compileall src tests +python -m reachy_mini_conversation_app --help +reachy-mini-app-assistant check . +``` + +Tests require the development dependency group: + +```bash +uv sync --group dev +python -m pytest -q +``` + +## Troubleshooting + +If the app cannot connect, make sure the daemon is running before launching the +conversation app. If the daemon was started with `--robot-name`, pass the same +name to the app with `--robot-name`. + +If `--local-vision`, `--head-tracker yolo`, or `--head-tracker mediapipe` fails +with an import error, install the matching optional dependency group. + +If `uv sync` tries to build `pygobject` or `pycairo` on macOS, the resolver is +including a Linux media dependency path. This project scopes uv resolution to +Darwin for the current local workflow; rerun `uv sync`, and if uv is still using +old metadata, clear the package cache with `uv cache clean reachy-mini pygobject +pycairo`. + +If you are running the simulator with `--no-media`, keep `--no-camera` on the +conversation app. diff --git a/projects/reachy-mini-openshell/pyproject.toml b/projects/reachy-mini-openshell/pyproject.toml index 6ddc6313..800679d8 100644 --- a/projects/reachy-mini-openshell/pyproject.toml +++ b/projects/reachy-mini-openshell/pyproject.toml @@ -7,8 +7,8 @@ name = "reachy_mini_conversation_app" version = "0.3.0" description = "OpenShell-oriented fork of the Reachy Mini conversation app." readme = "README.md" -requires-python = ">=3.10" -dependencies = [ "aiortc>=1.13.0", "fastrtc>=0.0.34", "gradio==5.50.1.dev1", "huggingface-hub==1.3.0", "opencv-python>=4.12.0.88", "python-dotenv", "openai>=2.1", "reachy_mini_dances_library", "reachy_mini_toolbox", "reachy-mini>=1.5.0", "eclipse-zenoh~=1.7.0", "gradio_client>=1.13.3",] +requires-python = ">=3.10,<3.13" +dependencies = [ "aiortc>=1.13.0", "fastrtc>=0.0.34", "gradio==5.50.1.dev1", "huggingface-hub==1.3.0", "opencv-python>=4.12.0.88", "python-dotenv", "openai>=2.1", "reachy_mini_dances_library", "reachy_mini_toolbox", "reachy-mini==1.8.0", "eclipse-zenoh~=1.7.0", "gradio_client>=1.13.3",] [[project.authors]] name = "Pollen Robotics" email = "contact@pollen-robotics.com" @@ -16,6 +16,11 @@ email = "contact@pollen-robotics.com" [dependency-groups] dev = [ "pytest", "pytest-asyncio", "ruff==0.12.0", "mypy==1.18.2", "pre-commit", "types-requests", "python-semantic-release>=10.5.3",] +[tool.uv] +environments = [ + "sys_platform == 'darwin'", +] + [project.optional-dependencies] local_vision = [ "torch>=2.1", "transformers==5.0.0rc2", "num2words",] yolo_vision = [ "ultralytics", "supervision",] diff --git a/projects/reachy-mini-openshell/uv.lock b/projects/reachy-mini-openshell/uv.lock new file mode 100644 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-42,16 +42,17 @@ This project contains: - Reachy Mini movement, dance, emotion, and look-around tools - a locked OpenShell profile for instructions and tool selection - optional camera, local vision, YOLO head-tracking, and MediaPipe head-tracking - integrations +integrations ## Requirements - Python 3.10, 3.11, or 3.12. The recommended local version is Python 3.12. - `uv` for the recommended local workflow -- Reachy Mini SDK 1.8.0, installed through this project. This is pinned to the - version compatible with the forked conversation-app dependency stack. +- Reachy Mini SDK 1.8.0 with the MuJoCo simulator backend, installed through +this project. The SDK is pinned to the version compatible with the forked +conversation-app dependency stack. - a running Reachy Mini daemon, either connected to hardware or started in - simulator mode +simulator mode - an OpenAI API key for conversation ## Install @@ -111,9 +112,10 @@ python -m pip install -e '.[mediapipe_vision]' python -m pip install -e '.[all_vision]' ``` -There are no `backend` or `sim` extras anymore. The previous backend extra -belonged to the deleted scaffold, and simulator support is provided by the -Reachy Mini daemon/runtime rather than a project extra. +There are no project-level `backend` or `sim` extras anymore. The previous +backend extra belonged to the deleted scaffold. The default dependency set +includes Reachy Mini's MuJoCo simulator backend because the local development +workflow starts `reachy-mini-daemon --sim` from this environment. ## Configuration @@ -163,7 +165,7 @@ In simulator mode, the app auto-enables Gradio. The examples still pass at: ```text -http://127.0.0.1:7860/ +c ``` If port `7860` is busy, Gradio may choose another available local port and print @@ -175,15 +177,15 @@ Useful app flags: - `--gradio`: launch the browser conversation UI. - `--no-camera`: disable camera usage. This is the recommended simulator - baseline. +baseline. - `--head-tracker yolo`: enable YOLO head tracking. Requires the `yolo_vision` - extra. +extra. - `--head-tracker mediapipe`: enable MediaPipe head tracking. Requires the - `mediapipe_vision` extra. +`mediapipe_vision` extra. - `--local-vision`: use a local vision model instead of Realtime vision. - Requires the `local_vision` extra. +Requires the `local_vision` extra. - `--robot-name `: connect to a daemon started with the same - `--robot-name`. +`--robot-name`. - `--debug`: enable debug logging. Examples: @@ -252,8 +254,7 @@ with an import error, install the matching optional dependency group. If `uv sync` tries to build `pygobject` or `pycairo` on macOS, the resolver is including a Linux media dependency path. This project scopes uv resolution to Darwin for the current local workflow; rerun `uv sync`, and if uv is still using -old metadata, clear the package cache with `uv cache clean reachy-mini pygobject -pycairo`. +old metadata, clear the package cache with `uv cache clean reachy-mini pygobject pycairo`. If you are running the simulator with `--no-media`, keep `--no-camera` on the -conversation app. +conversation app. \ No newline at end of file diff --git a/projects/reachy-mini-openshell/pyproject.toml b/projects/reachy-mini-openshell/pyproject.toml index 800679d8..ffce601d 100644 --- a/projects/reachy-mini-openshell/pyproject.toml +++ b/projects/reachy-mini-openshell/pyproject.toml @@ -8,7 +8,7 @@ version = "0.3.0" description = "OpenShell-oriented fork of the Reachy Mini conversation app." readme = "README.md" requires-python = ">=3.10,<3.13" -dependencies = [ "aiortc>=1.13.0", "fastrtc>=0.0.34", "gradio==5.50.1.dev1", "huggingface-hub==1.3.0", "opencv-python>=4.12.0.88", "python-dotenv", "openai>=2.1", "reachy_mini_dances_library", "reachy_mini_toolbox", "reachy-mini==1.8.0", "eclipse-zenoh~=1.7.0", "gradio_client>=1.13.3",] +dependencies = [ "aiortc>=1.13.0", "fastrtc>=0.0.34", "gradio==5.50.1.dev1", "huggingface-hub==1.3.0", "opencv-python>=4.12.0.88", "python-dotenv", 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'darwin'" }, { name = "python-dotenv", marker = "sys_platform == 'darwin'" }, - { name = "reachy-mini", marker = "sys_platform == 'darwin'" }, + { name = "reachy-mini", extra = ["mujoco"], marker = "sys_platform == 'darwin'" }, { name = "reachy-mini-dances-library", marker = "sys_platform == 'darwin'" }, { name = "reachy-mini-toolbox", marker = "sys_platform == 'darwin'" }, ] @@ -2102,7 +2193,7 @@ requires-dist = [ { name = "openai", specifier = ">=2.1" }, { name = "opencv-python", specifier = ">=4.12.0.88" }, { name = "python-dotenv" }, - { name = "reachy-mini", specifier = "==1.8.0" }, + { name = "reachy-mini", extras = ["mujoco"], specifier = "==1.8.0" }, { name = "reachy-mini-dances-library" }, { name = "reachy-mini-toolbox" }, { name = "supervision", marker = "extra == 'all-vision'" }, @@ -2947,3 +3038,12 @@ wheels = [ { url = 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+wheels = [ + { url = "https://files.pythonhosted.org/packages/3a/13/547360d81e6d88d58492968ffda9f9542854f11310ee556fef14260cc886/zipp-4.1.0-py3-none-any.whl", hash = "sha256:25ad4e16390cd314347dd8f1de67a2ac538ae658ed4ab9db16029c07c188e97f", size = 10238, upload-time = "2026-05-18T20:08:57.045Z" }, +] From 03f4e30ddeab3441797890ab98d39a31a1768aa2 Mon Sep 17 00:00:00 2001 From: Johnny Greco Date: Wed, 24 Jun 2026 23:17:09 -0400 Subject: [PATCH 08/45] Support provider-routed text input --- projects/reachy-mini-openshell/.env.example | 5 +- .../reachy_mini_conversation_app/config.py | 29 +- .../reachy_mini_conversation_app/console.py | 261 +---------- .../src/reachy_mini_conversation_app/main.py | 60 ++- .../openai_realtime.py | 442 ++++++++++++++---- .../static/index.html | 54 --- .../static/main.js | 136 ------ .../static/style.css | 210 --------- .../tests/test_openai_realtime.py | 332 +++++++++++++ 9 files changed, 771 insertions(+), 758 deletions(-) delete mode 100644 projects/reachy-mini-openshell/src/reachy_mini_conversation_app/static/index.html delete mode 100644 projects/reachy-mini-openshell/src/reachy_mini_conversation_app/static/main.js delete mode 100644 projects/reachy-mini-openshell/src/reachy_mini_conversation_app/static/style.css diff --git a/projects/reachy-mini-openshell/.env.example b/projects/reachy-mini-openshell/.env.example index 12cf25b2..42515c10 100644 --- a/projects/reachy-mini-openshell/.env.example +++ b/projects/reachy-mini-openshell/.env.example @@ -1,5 +1,6 @@ -OPENAI_API_KEY= -MODEL_NAME="gpt-realtime" +OPENAI_API_KEY=${NVIDIA_API_KEY} +OPENAI_BASE_URL=https://inference-api.nvidia.com/v1 +MODEL_NAME=azure/anthropic/claude-opus-4-8 # Used only with --local-vision. LOCAL_VISION_MODEL=HuggingFaceTB/SmolVLM2-2.2B-Instruct diff --git a/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/config.py b/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/config.py index fe10c9fd..6cf01c4f 100644 --- a/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/config.py +++ b/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/config.py @@ -3,7 +3,7 @@ import logging from pathlib import Path -from dotenv import find_dotenv, load_dotenv +from dotenv import find_dotenv, load_dotenv, dotenv_values LOCKED_PROFILE = "_reachy_mini_conversation_app_locked_profile" @@ -38,6 +38,8 @@ def _env_flag(name: str, default: bool = False) -> bool: sys.exit(1) _skip_dotenv = _env_flag("REACHY_MINI_SKIP_DOTENV", default=False) +_dotenv_path = "" +_dotenv_values: dict[str, str | None] = {} if _skip_dotenv: logger.info("Skipping .env loading because REACHY_MINI_SKIP_DOTENV is set") @@ -46,24 +48,43 @@ def _env_flag(name: str, default: bool = False) -> bool: dotenv_path = find_dotenv(usecwd=True) if dotenv_path: + _dotenv_path = dotenv_path + _dotenv_values = dict(dotenv_values(dotenv_path)) # Load .env and override environment variables load_dotenv(dotenv_path=dotenv_path, override=True) logger.info(f"Configuration loaded from {dotenv_path}") else: - logger.warning("No .env file found, using environment variables") + logger.warning("No .env file found") + + +def _dotenv_value(name: str, default: str | None = None) -> str | None: + """Return a value from the loaded .env file only.""" + value = _dotenv_values.get(name) + if value is None: + return default + value = value.strip() + return value if value else default class Config: """Configuration class for the conversation app.""" - OPENAI_API_KEY = os.getenv("OPENAI_API_KEY") + OPENAI_API_KEY = _dotenv_value("OPENAI_API_KEY") + OPENAI_BASE_URL = _dotenv_value("OPENAI_BASE_URL", "https://api.openai.com/v1") MODEL_NAME = os.getenv("MODEL_NAME", "gpt-realtime") HF_HOME = os.getenv("HF_HOME", "./cache") LOCAL_VISION_MODEL = os.getenv("LOCAL_VISION_MODEL", "HuggingFaceTB/SmolVLM2-2.2B-Instruct") HF_TOKEN = os.getenv("HF_TOKEN") - logger.debug(f"Model: {MODEL_NAME}, HF_HOME: {HF_HOME}, Vision Model: {LOCAL_VISION_MODEL}") + logger.debug( + "Model: %s, Base URL: %s, HF_HOME: %s, Vision Model: %s", + MODEL_NAME, + OPENAI_BASE_URL, + HF_HOME, + LOCAL_VISION_MODEL, + ) logger.debug(f"Locked profile: {LOCKED_PROFILE}") + logger.debug("Dotenv path: %s", _dotenv_path or "") def __init__(self) -> None: """Initialize the configuration.""" diff --git a/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/console.py b/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/console.py index 57103578..ff284fca 100644 --- a/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/console.py +++ b/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/console.py @@ -1,20 +1,9 @@ -"""Bidirectional local audio stream with optional settings UI. +"""Bidirectional local audio stream for Reachy Mini audio.""" -In headless mode, there is no Gradio UI. If the OpenAI API key is not -available via environment/.env, we expose a minimal settings page via the -Reachy Mini Apps settings server to let non-technical users enter it. - -The settings UI is served from this package's ``static/`` folder and offers a -single password field to set ``OPENAI_API_KEY``. Once set, we persist it to the -app instance's ``.env`` file (if available) and proceed to start streaming. -""" - -import os -import sys import time import asyncio import logging -from typing import List, Optional +from typing import Any, List, Optional from pathlib import Path from fastrtc import AdditionalOutputs, audio_to_float32 @@ -26,20 +15,6 @@ from reachy_mini_conversation_app.openai_realtime import OpenaiRealtimeHandler -try: - # FastAPI is provided by the Reachy Mini Apps runtime - from fastapi import FastAPI, Response - from pydantic import BaseModel - from fastapi.responses import FileResponse, JSONResponse - from starlette.staticfiles import StaticFiles -except Exception: # pragma: no cover - only loaded when settings_app is used - FastAPI = object # type: ignore - FileResponse = object # type: ignore - JSONResponse = object # type: ignore - StaticFiles = object # type: ignore - BaseModel = object # type: ignore - - logger = logging.getLogger(__name__) @@ -51,12 +26,12 @@ def __init__( handler: OpenaiRealtimeHandler, robot: ReachyMini, *, - settings_app: Optional[FastAPI] = None, + settings_app: Optional[Any] = None, instance_path: Optional[str] = None, ): """Initialize the stream with an OpenAI realtime handler and pipelines. - - ``settings_app``: the Reachy Mini Apps FastAPI to attach settings endpoints. + - ``settings_app``: reserved for the Reachy Mini Apps runtime. - ``instance_path``: directory where per-instance ``.env`` should be stored. """ self.handler = handler @@ -65,240 +40,38 @@ def __init__( self._tasks: List[asyncio.Task[None]] = [] # Allow the handler to flush the player queue when appropriate. self.handler._clear_queue = self.clear_audio_queue - self._settings_app: Optional[FastAPI] = settings_app + self._settings_app: Optional[Any] = settings_app self._instance_path: Optional[str] = instance_path - self._settings_initialized = False self._asyncio_loop = None - # ---- Settings UI (only when API key is missing) ---- - def _read_env_lines(self, env_path: Path) -> list[str]: - """Load env file contents or a template as a list of lines.""" - inst = env_path.parent - try: - if env_path.exists(): - try: - return env_path.read_text(encoding="utf-8").splitlines() - except Exception: - return [] - template_text = None - ex = inst / ".env.example" - if ex.exists(): - try: - template_text = ex.read_text(encoding="utf-8") - except Exception: - template_text = None - if template_text is None: - try: - cwd_example = Path.cwd() / ".env.example" - if cwd_example.exists(): - template_text = cwd_example.read_text(encoding="utf-8") - except Exception: - template_text = None - if template_text is None: - packaged = Path(__file__).parent / ".env.example" - if packaged.exists(): - try: - template_text = packaged.read_text(encoding="utf-8") - except Exception: - template_text = None - return template_text.splitlines() if template_text else [] - except Exception: - return [] - - def _persist_api_key(self, key: str) -> None: - """Persist API key to environment and instance ``.env`` if possible. - - Behavior: - - Always sets ``OPENAI_API_KEY`` in process env and in-memory config. - - Writes/updates ``/.env``: - * If ``.env`` exists, replaces/append OPENAI_API_KEY line. - * Else, copies template from ``/.env.example`` when present, - otherwise falls back to the packaged template - ``reachy_mini_conversation_app/.env.example``. - * Ensures the resulting file contains the full template plus the key. - - Loads the written ``.env`` into the current process environment. - """ - k = (key or "").strip() - if not k: - return - # Update live process env and config so consumers see it immediately - try: - os.environ["OPENAI_API_KEY"] = k - except Exception: # best-effort - pass - try: - config.OPENAI_API_KEY = k - except Exception: - pass - - if not self._instance_path: - return - try: - inst = Path(self._instance_path) - env_path = inst / ".env" - lines = self._read_env_lines(env_path) - replaced = False - for i, ln in enumerate(lines): - if ln.strip().startswith("OPENAI_API_KEY="): - lines[i] = f"OPENAI_API_KEY={k}" - replaced = True - break - if not replaced: - lines.append(f"OPENAI_API_KEY={k}") - final_text = "\n".join(lines) + "\n" - env_path.write_text(final_text, encoding="utf-8") - logger.info("Persisted OPENAI_API_KEY to %s", env_path) - - # Load the newly written .env into this process to ensure downstream imports see it - try: - from dotenv import load_dotenv - - load_dotenv(dotenv_path=str(env_path), override=True) - except Exception: - pass - except Exception as e: - logger.warning("Failed to persist OPENAI_API_KEY: %s", e) - - def _init_settings_ui_if_needed(self) -> None: - """Attach minimal settings UI to the settings app. - - Always mounts the UI when a settings_app is provided so that users - see a confirmation message even if the API key is already configured. - """ - if self._settings_initialized: - return - if self._settings_app is None: - return - - static_dir = Path(__file__).parent / "static" - index_file = static_dir / "index.html" - - if hasattr(self._settings_app, "mount"): - try: - # Serve /static/* assets - self._settings_app.mount("/static", StaticFiles(directory=str(static_dir)), name="static") - except Exception: - pass - - class ApiKeyPayload(BaseModel): - openai_api_key: str - - # GET / -> index.html - @self._settings_app.get("/") - def _root() -> FileResponse: - return FileResponse(str(index_file)) - - # GET /favicon.ico -> optional, avoid noisy 404s on some browsers - @self._settings_app.get("/favicon.ico") - def _favicon() -> Response: - return Response(status_code=204) - - # GET /status -> whether key is set - @self._settings_app.get("/status") - def _status() -> JSONResponse: - has_key = bool(config.OPENAI_API_KEY and str(config.OPENAI_API_KEY).strip()) - return JSONResponse({"has_key": has_key}) - - # GET /ready -> whether backend finished loading tools - @self._settings_app.get("/ready") - def _ready() -> JSONResponse: - try: - mod = sys.modules.get("reachy_mini_conversation_app.tools.core_tools") - ready = bool(getattr(mod, "_TOOLS_INITIALIZED", False)) if mod else False - except Exception: - ready = False - return JSONResponse({"ready": ready}) - - # POST /openai_api_key -> set/persist key - @self._settings_app.post("/openai_api_key") - def _set_key(payload: ApiKeyPayload) -> JSONResponse: - key = (payload.openai_api_key or "").strip() - if not key: - return JSONResponse({"ok": False, "error": "empty_key"}, status_code=400) - self._persist_api_key(key) - return JSONResponse({"ok": True}) - - # POST /validate_api_key -> validate key without persisting it - @self._settings_app.post("/validate_api_key") - async def _validate_key(payload: ApiKeyPayload) -> JSONResponse: - key = (payload.openai_api_key or "").strip() - if not key: - return JSONResponse({"valid": False, "error": "empty_key"}, status_code=400) - - # Try to validate by checking if we can fetch the models - try: - import httpx - - headers = {"Authorization": f"Bearer {key}", "Content-Type": "application/json"} - async with httpx.AsyncClient(timeout=10.0) as client: - response = await client.get("https://api.openai.com/v1/models", headers=headers) - if response.status_code == 200: - return JSONResponse({"valid": True}) - elif response.status_code == 401: - return JSONResponse({"valid": False, "error": "invalid_api_key"}, status_code=401) - else: - return JSONResponse( - {"valid": False, "error": "validation_failed"}, status_code=response.status_code - ) - except Exception as e: - logger.warning(f"API key validation failed: {e}") - return JSONResponse({"valid": False, "error": "validation_error"}, status_code=500) - - self._settings_initialized = True - def launch(self) -> None: """Start the recorder/player and run the async processing loops. - If the OpenAI key is missing, expose a tiny settings UI via the - Reachy Mini settings server to collect it before starting streams. + Provider credentials are loaded from `.env` only. If `OPENAI_API_KEY` is + missing, startup stops before media is opened. """ self._stop_event.clear() - # Try to load an existing instance .env first (covers subsequent runs) + # Try to load an existing instance .env first for Reachy Mini app-shell runs. if self._instance_path: try: - from dotenv import load_dotenv + from dotenv import load_dotenv, dotenv_values env_path = Path(self._instance_path) / ".env" if env_path.exists(): load_dotenv(dotenv_path=str(env_path), override=True) - new_key = os.getenv("OPENAI_API_KEY", "").strip() - if new_key: - try: - config.OPENAI_API_KEY = new_key - except Exception: - pass + values = dotenv_values(env_path) + config.OPENAI_API_KEY = (values.get("OPENAI_API_KEY") or "").strip() or None + config.OPENAI_BASE_URL = ( + (values.get("OPENAI_BASE_URL") or "").strip() + or "https://api.openai.com/v1" + ) except Exception: pass # Instance .env loading is optional; continue with defaults - # If key is still missing, try to download one from HuggingFace if not (config.OPENAI_API_KEY and str(config.OPENAI_API_KEY).strip()): - logger.info("OPENAI_API_KEY not set, attempting to download from HuggingFace...") - try: - from gradio_client import Client - client = Client("HuggingFaceM4/gradium_setup", verbose=False) - key, status = client.predict(api_name="/claim_b_key") - if key and key.strip(): - logger.info("Successfully downloaded API key from HuggingFace") - # Persist it immediately - self._persist_api_key(key) - except Exception as e: - logger.warning(f"Failed to download API key from HuggingFace: {e}") - - # Always expose settings UI if a settings app is available - # (do this AFTER loading/downloading the key so status endpoint sees the right value) - self._init_settings_ui_if_needed() - - # If key is still missing -> wait until provided via the settings UI - if not (config.OPENAI_API_KEY and str(config.OPENAI_API_KEY).strip()): - logger.warning("OPENAI_API_KEY not found. Open the app settings page to enter it.") - # Poll until the key becomes available (set via the settings UI) - try: - while not (config.OPENAI_API_KEY and str(config.OPENAI_API_KEY).strip()): - time.sleep(0.2) - except KeyboardInterrupt: - logger.info("Interrupted while waiting for API key.") - return + logger.error("OPENAI_API_KEY is missing. Add it to .env and restart the conversation app.") + return # Start media after key is set/available self._robot.media.start_recording() diff --git a/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/main.py b/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/main.py index 6b809e8a..f618aef4 100644 --- a/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/main.py +++ b/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/main.py @@ -31,7 +31,7 @@ def main() -> None: def run( args: argparse.Namespace, - robot: ReachyMini = None, + robot: ReachyMini | None = None, app_stop_event: Optional[threading.Event] = None, settings_app: Optional[Any] = None, instance_path: Optional[str] = None, @@ -41,7 +41,6 @@ def run( import gradio as gr from fastapi import FastAPI from fastrtc import Stream - from gradio.utils import get_space except ImportError as exc: raise RuntimeError( "Reachy OpenShell conversation dependencies are not installed. " @@ -144,25 +143,66 @@ def run( stream_manager: gr.Blocks | LocalStream | None = None if args.gradio: - api_key_textbox = gr.Textbox( - label="OPENAI API Key", - type="password", - value=os.getenv("OPENAI_API_KEY") if not get_space() else "", - ) - stream = Stream( handler=handler, mode="send-receive", modality="audio", additional_inputs=[ chatbot, - api_key_textbox, ], additional_outputs=[chatbot], additional_outputs_handler=update_chatbot, ui_args={"title": "Talk with Reachy Mini"}, ) stream_manager = stream.ui + + with stream_manager: + input_mode = gr.Radio( + choices=["Microphone", "Text"], + value="Microphone", + label="Input", + ) + with gr.Row(): + text_input = gr.Textbox( + label="Message", + lines=2, + max_lines=5, + visible=False, + ) + send_button = gr.Button("Send", variant="primary", visible=False) + + def switch_input_mode(mode: str) -> tuple[dict[str, Any], dict[str, Any], dict[str, Any]]: + text_mode = mode == "Text" + return ( + gr.update(visible=not text_mode), + gr.update(visible=text_mode), + gr.update(visible=text_mode), + ) + + async def send_text_message( + message: str, + chatbot_messages: List[Dict[str, Any]] | None, + ) -> tuple[List[Dict[str, Any]], str]: + updated_chatbot = list(chatbot_messages or []) + updated_chatbot.extend(await handler.send_text_message(message)) + return updated_chatbot, "" + + input_mode.change( + fn=switch_input_mode, + inputs=input_mode, + outputs=[stream.webrtc_component, text_input, send_button], + ) + text_input.submit( + fn=send_text_message, + inputs=[text_input, chatbot], + outputs=[chatbot, text_input], + ) + send_button.click( + fn=send_text_message, + inputs=[text_input, chatbot], + outputs=[chatbot, text_input], + ) + if not settings_app: app = FastAPI() else: @@ -243,7 +283,7 @@ def run(self, reachy_mini: ReachyMini, stop_event: threading.Event) -> None: robot=reachy_mini, app_stop_event=stop_event, settings_app=self.settings_app, - instance_path=instance_path, + instance_path=str(instance_path), ) diff --git a/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/openai_realtime.py b/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/openai_realtime.py index c43d6172..7e993157 100644 --- a/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/openai_realtime.py +++ b/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/openai_realtime.py @@ -4,8 +4,7 @@ import random import asyncio import logging -from typing import Any, Final, Tuple, Literal, Optional -from pathlib import Path +from typing import Any, Final, Tuple, Literal, Optional, cast from datetime import datetime import cv2 @@ -22,6 +21,7 @@ from reachy_mini_conversation_app.tools.core_tools import ( ToolDependencies, get_tool_specs, + dispatch_tool_call_with_manager, ) from reachy_mini_conversation_app.tools.background_tool_manager import ( ToolCallRoutine, @@ -89,9 +89,6 @@ def __init__(self, deps: ToolDependencies, gradio_mode: bool = False, instance_p self.is_idle_tool_call = False self.gradio_mode = gradio_mode self.instance_path = instance_path - # Track how the API key was provided (env vs textbox) and its value - self._key_source: Literal["env", "textbox"] = "env" - self._provided_api_key: str | None = None # Debouncing for partial transcripts self.partial_transcript_task: asyncio.Task[None] | None = None @@ -101,6 +98,8 @@ def __init__(self, deps: ToolDependencies, gradio_mode: bool = False, instance_p # Internal lifecycle flags self._shutdown_requested: bool = False self._connected_event: asyncio.Event = asyncio.Event() + self._text_startup_task: asyncio.Task[None] | None = None + self._startup_error: str | None = None # Background tool manager self.tool_manager = BackgroundToolManager() @@ -120,6 +119,314 @@ def copy(self) -> "OpenaiRealtimeHandler": """Create a copy of the handler.""" return OpenaiRealtimeHandler(self.deps, self.gradio_mode, self.instance_path) + def _record_startup_error(self, message: str) -> None: + """Store a startup failure so the UI can show a useful error.""" + self._startup_error = message + try: + self._connected_event.set() + except Exception: + pass + + def _realtime_context(self) -> str: + """Return non-secret Realtime configuration for diagnostics.""" + return f"model={config.MODEL_NAME!r}, base_url={config.OPENAI_BASE_URL!r}" + + def _provider_realtime_hint(self) -> str: + """Return a provider-specific hint for common compatibility failures.""" + base_url = str(config.OPENAI_BASE_URL) + if "integrate.api.nvidia.com" in base_url or "inference-api.nvidia.com" in base_url: + return ( + " NVIDIA OpenAI-compatible chat endpoints use Chat Completions; " + "microphone mode requires an OpenAI-compatible Realtime API endpoint." + ) + return "" + + def _not_connected_message(self) -> str: + """Return the user-facing reason the Realtime session is unavailable.""" + if self._startup_error: + return f"[error] {self._startup_error}" + return ( + "[error] Realtime session is not connected. Check OPENAI_API_KEY, " + "OPENAI_BASE_URL, and MODEL_NAME in .env." + ) + + @staticmethod + def _text_model_uses_realtime() -> bool: + """Return whether typed messages should use the Realtime transport.""" + return "realtime" in str(config.MODEL_NAME).lower() + + @staticmethod + def _chat_completion_tool_specs() -> list[dict[str, Any]]: + """Convert Realtime-style tool specs to Chat Completions tool specs.""" + chat_tools: list[dict[str, Any]] = [] + for tool in get_tool_specs(): + if tool.get("type") != "function": + continue + chat_tools.append( + { + "type": "function", + "function": { + "name": tool.get("name"), + "description": tool.get("description", ""), + "parameters": tool.get("parameters", {}), + }, + } + ) + return chat_tools + + @staticmethod + def _tool_call_value(tool_call: Any, name: str) -> Any: + """Read a value from either an SDK model object or a dict.""" + if isinstance(tool_call, dict): + return tool_call.get(name) + return getattr(tool_call, name, None) + + @classmethod + def _tool_call_function_value(cls, tool_call: Any, name: str) -> Any: + """Read a function value from either an SDK tool-call object or a dict.""" + function = cls._tool_call_value(tool_call, "function") + if isinstance(function, dict): + return function.get(name) + return getattr(function, name, None) + + @staticmethod + def _serialize_tool_call(tool_call: Any) -> dict[str, Any]: + """Convert a tool call into the dict shape Chat Completions expects.""" + if hasattr(tool_call, "model_dump"): + return tool_call.model_dump() + if isinstance(tool_call, dict): + return tool_call + return { + "id": getattr(tool_call, "id", None), + "type": getattr(tool_call, "type", "function"), + "function": { + "name": getattr(getattr(tool_call, "function", None), "name", None), + "arguments": getattr(getattr(tool_call, "function", None), "arguments", "{}"), + }, + } + + def _openai_api_key_or_error(self) -> str | None: + """Return the configured API key or record a useful startup error.""" + openai_api_key = (config.OPENAI_API_KEY or "").strip() + if openai_api_key: + return openai_api_key + + message = ( + "OPENAI_API_KEY is missing or empty after reading .env. Add it to .env and restart the " + "conversation app. If .env uses OPENAI_API_KEY=${NVIDIA_API_KEY}, make sure " + "NVIDIA_API_KEY is exported in the shell that starts the app." + ) + self._record_startup_error(message) + logger.error(message) + return None + + async def _ensure_text_session(self) -> bool: + """Start a Realtime session for text-only Gradio input if needed.""" + if self.connection is not None: + return True + + if self._text_startup_task is None or self._text_startup_task.done(): + self._startup_error = None + try: + self._connected_event.clear() + except Exception: + pass + self._text_startup_task = asyncio.create_task(self.start_up(), name="openai-realtime-text") + + try: + await asyncio.wait_for(self._connected_event.wait(), timeout=10.0) + except asyncio.TimeoutError: + logger.warning("Timed out waiting for text Realtime session startup") + + return self.connection is not None + + @staticmethod + def _chat_message_from_output(output: AdditionalOutputs) -> dict[str, Any] | None: + """Convert a FastRTC AdditionalOutputs payload into a chatbot message.""" + if not output.args: + return None + candidate = output.args[0] + if not isinstance(candidate, dict): + return None + role = candidate.get("role") + content = candidate.get("content") + if role == "user_partial" or not isinstance(role, str) or content is None: + return None + return candidate + + async def send_text_message(self, message: str, timeout: float = 30.0) -> list[dict[str, Any]]: + """Send a typed user message and collect chat updates.""" + text = message.strip() + if not text: + return [] + + if not self._text_model_uses_realtime(): + return await self._send_chat_completion_text_message(text) + + if not await self._ensure_text_session(): + return [ + { + "role": "assistant", + "content": self._not_connected_message(), + }, + ] + + await self.connection.conversation.item.create( + item={ + "type": "message", + "role": "user", + "content": [{"type": "input_text", "text": text}], + }, + ) + await self._safe_response_create() + + messages: list[dict[str, Any]] = [{"role": "user", "content": text}] + saw_assistant_message = False + deadline = asyncio.get_event_loop().time() + timeout + + while asyncio.get_event_loop().time() < deadline: + try: + output = await asyncio.wait_for(self.output_queue.get(), timeout=0.5) + except asyncio.TimeoutError: + if saw_assistant_message and self._response_done_event.is_set(): + break + continue + + if not isinstance(output, AdditionalOutputs): + continue + + chat_message = self._chat_message_from_output(output) + if chat_message is None: + continue + + messages.append(chat_message) + if chat_message.get("role") == "assistant": + saw_assistant_message = True + + if saw_assistant_message and self._response_done_event.is_set(): + break + + if not saw_assistant_message: + messages.append({"role": "assistant", "content": "[error] Timed out waiting for a response."}) + + return messages + + async def _send_chat_completion_text_message(self, text: str) -> list[dict[str, Any]]: + """Send a typed message through Chat Completions for non-Realtime models.""" + openai_api_key = self._openai_api_key_or_error() + if openai_api_key is None: + return [{"role": "assistant", "content": self._not_connected_message()}] + + if getattr(self, "client", None) is None: + self.client = AsyncOpenAI( + api_key=openai_api_key, + base_url=config.OPENAI_BASE_URL, + ) + + chatbot_messages: list[dict[str, Any]] = [{"role": "user", "content": text}] + chat_messages: list[dict[str, Any]] = [ + {"role": "system", "content": get_session_instructions()}, + {"role": "user", "content": text}, + ] + chat_tools = self._chat_completion_tool_specs() + + try: + completion = await self.client.chat.completions.create( + model=config.MODEL_NAME, + messages=cast(Any, chat_messages), + tools=cast(Any, chat_tools), + tool_choice="auto", + ) + except Exception as e: + logger.exception("Chat Completions request failed") + return [ + *chatbot_messages, + { + "role": "assistant", + "content": ( + f"[error] Chat Completions request failed " + f"(model={config.MODEL_NAME!r}, base_url={config.OPENAI_BASE_URL!r}): " + f"{type(e).__name__}: {e}" + ), + }, + ] + + choice = completion.choices[0] if completion.choices else None + assistant_message = getattr(choice, "message", None) if choice else None + assistant_content = getattr(assistant_message, "content", None) or "" + tool_calls = getattr(assistant_message, "tool_calls", None) or [] + + if not tool_calls: + chatbot_messages.append({"role": "assistant", "content": assistant_content or "[no response]"}) + return chatbot_messages + + chat_messages.append( + { + "role": "assistant", + "content": assistant_content, + "tool_calls": [self._serialize_tool_call(tool_call) for tool_call in tool_calls], + } + ) + + for tool_call in tool_calls: + tool_call_id = self._tool_call_value(tool_call, "id") or str(uuid.uuid4()) + tool_name = self._tool_call_function_value(tool_call, "name") + args_json = self._tool_call_function_value(tool_call, "arguments") or "{}" + if not isinstance(tool_name, str): + tool_result = {"error": "tool call did not include a valid function name"} + else: + tool_result = await dispatch_tool_call_with_manager( + tool_name, + args_json, + self.deps, + self.tool_manager, + ) + + tool_result_json = json.dumps(tool_result) + chat_messages.append( + { + "role": "tool", + "tool_call_id": tool_call_id, + "content": tool_result_json, + } + ) + chatbot_messages.append( + { + "role": "assistant", + "content": tool_result_json, + "metadata": { + "title": f"Used tool {tool_name or 'unknown'}", + "status": "done", + }, + } + ) + + try: + follow_up = await self.client.chat.completions.create( + model=config.MODEL_NAME, + messages=cast(Any, chat_messages), + tools=cast(Any, chat_tools), + ) + except Exception as e: + logger.exception("Chat Completions tool follow-up failed") + chatbot_messages.append( + { + "role": "assistant", + "content": ( + f"[error] Chat Completions tool follow-up failed " + f"(model={config.MODEL_NAME!r}, base_url={config.OPENAI_BASE_URL!r}): " + f"{type(e).__name__}: {e}" + ), + } + ) + return chatbot_messages + + follow_up_choice = follow_up.choices[0] if follow_up.choices else None + follow_up_message = getattr(follow_up_choice, "message", None) if follow_up_choice else None + follow_up_content = getattr(follow_up_message, "content", None) or "Done." + chatbot_messages.append({"role": "assistant", "content": follow_up_content}) + return chatbot_messages + async def _emit_debounced_partial(self, transcript: str, sequence: int) -> None: """Emit partial transcript after debounce delay.""" try: @@ -134,27 +441,14 @@ async def _emit_debounced_partial(self, transcript: str, sequence: int) -> None: async def start_up(self) -> None: """Start the handler with minimal retries on unexpected websocket closure.""" - openai_api_key = config.OPENAI_API_KEY - if self.gradio_mode and not openai_api_key: - # api key was not found in .env or in the environment variables - await self.wait_for_args() # type: ignore[no-untyped-call] - args = list(self.latest_args) - textbox_api_key = args[3] if len(args[3]) > 0 else None - if textbox_api_key is not None: - openai_api_key = textbox_api_key - self._key_source = "textbox" - self._provided_api_key = textbox_api_key - else: - openai_api_key = config.OPENAI_API_KEY - else: - if not openai_api_key or not openai_api_key.strip(): - # In headless console mode, LocalStream now blocks startup until the key is provided. - # However, unit tests may invoke this handler directly with a stubbed client. - # To keep tests hermetic without requiring a real key, fall back to a placeholder. - logger.warning("OPENAI_API_KEY missing. Proceeding with a placeholder (tests/offline).") - openai_api_key = "DUMMY" + openai_api_key = self._openai_api_key_or_error() + if openai_api_key is None: + return - self.client = AsyncOpenAI(api_key=openai_api_key) + self.client = AsyncOpenAI( + api_key=openai_api_key, + base_url=config.OPENAI_BASE_URL, + ) max_attempts = 3 for attempt in range(1, max_attempts + 1): @@ -173,12 +467,29 @@ async def start_up(self) -> None: logger.info("Retrying in %.1f seconds...", delay) await asyncio.sleep(delay) continue - raise + message = ( + f"Realtime websocket closed before startup completed ({self._realtime_context()}): " + f"{type(e).__name__}: {e}.{self._provider_realtime_hint()}" + ) + self._record_startup_error(message) + logger.error(message) + return + except Exception as e: + message = ( + f"Realtime startup failed ({self._realtime_context()}): " + f"{type(e).__name__}: {e}.{self._provider_realtime_hint()}" + ) + self._record_startup_error(message) + logger.exception(message) + return finally: # never keep a stale reference self.connection = None try: - self._connected_event.clear() + if self._startup_error is None: + self._connected_event.clear() + else: + self._connected_event.set() except Exception: pass @@ -418,10 +729,12 @@ async def _run_realtime_session(self) -> None: LOCKED_PROFILE, get_session_voice(), ) - # If we reached here, the session update succeeded which implies the API key worked. - # Persist the key to a newly created .env (copied from .env.example) if needed. - self._persist_api_key_if_needed() - except Exception: + except Exception as e: + message = ( + f"Realtime session.update failed ({self._realtime_context()}): " + f"{type(e).__name__}: {e}.{self._provider_realtime_hint()}" + ) + self._record_startup_error(message) logger.exception("Realtime session.update failed; aborting startup") return @@ -742,70 +1055,3 @@ async def send_idle_signal(self, idle_duration: float) -> None: "tool_choice": "required", }, ) - - def _persist_api_key_if_needed(self) -> None: - """Persist the API key into `.env` inside `instance_path/` when appropriate. - - - Only runs in Gradio mode when key came from the textbox and is non-empty. - - Only saves if `self.instance_path` is not None. - - Writes `.env` to `instance_path/.env` (does not overwrite if it already exists). - - If `instance_path/.env.example` exists, copies its contents while overriding OPENAI_API_KEY. - """ - try: - if not self.gradio_mode: - logger.warning("Not in Gradio mode; skipping API key persistence.") - return - - if self._key_source != "textbox": - logger.info("API key not provided via textbox; skipping persistence.") - return - - key = (self._provided_api_key or "").strip() - if not key: - logger.warning("No API key provided via textbox; skipping persistence.") - return - if self.instance_path is None: - logger.warning("Instance path is None; cannot persist API key.") - return - - # Update the current process environment for downstream consumers - try: - import os - - os.environ["OPENAI_API_KEY"] = key - except Exception: # best-effort - pass - - target_dir = Path(self.instance_path) - env_path = target_dir / ".env" - if env_path.exists(): - # Respect existing user configuration - logger.info(".env already exists at %s; not overwriting.", env_path) - return - - example_path = target_dir / ".env.example" - content_lines: list[str] = [] - if example_path.exists(): - try: - content = example_path.read_text(encoding="utf-8") - content_lines = content.splitlines() - except Exception as e: - logger.warning("Failed to read .env.example at %s: %s", example_path, e) - - # Replace or append the OPENAI_API_KEY line - replaced = False - for i, line in enumerate(content_lines): - if line.strip().startswith("OPENAI_API_KEY="): - content_lines[i] = f"OPENAI_API_KEY={key}" - replaced = True - break - if not replaced: - content_lines.append(f"OPENAI_API_KEY={key}") - - # Ensure file ends with newline - final_text = "\n".join(content_lines) + "\n" - env_path.write_text(final_text, encoding="utf-8") - logger.info("Created %s and stored OPENAI_API_KEY for future runs.", env_path) - except Exception as e: - # Never crash the app for QoL persistence; just log. - logger.warning("Could not persist OPENAI_API_KEY to .env: %s", e) diff --git a/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/static/index.html b/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/static/index.html deleted file mode 100644 index 058cff29..00000000 --- a/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/static/index.html +++ /dev/null @@ -1,54 +0,0 @@ - - - - - - Reachy OpenShell - Settings - - - -
    -
    - -

    Loading…

    -
    -
    -
    -
    Headless control
    -

    Reachy OpenShell

    -

    Configure your OpenAI API key for the conversation app.

    -
    - - - - -
    - - - - diff --git a/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/static/main.js b/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/static/main.js deleted file mode 100644 index 4932fc8d..00000000 --- a/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/static/main.js +++ /dev/null @@ -1,136 +0,0 @@ -const sleep = (ms) => new Promise((resolve) => setTimeout(resolve, ms)); - -async function fetchWithTimeout(url, options = {}, timeoutMs = 2000) { - const controller = new AbortController(); - const id = setTimeout(() => controller.abort(), timeoutMs); - try { - return await fetch(url, { ...options, signal: controller.signal }); - } finally { - clearTimeout(id); - } -} - -async function waitForStatus(timeoutMs = 15000) { - const loadingText = document.querySelector("#loading p"); - let attempts = 0; - const deadline = Date.now() + timeoutMs; - while (true) { - attempts += 1; - try { - const url = new URL("/status", window.location.origin); - url.searchParams.set("_", Date.now().toString()); - const resp = await fetchWithTimeout(url, {}, 2000); - if (resp.ok) return await resp.json(); - } catch (e) {} - if (loadingText) { - loadingText.textContent = attempts > 8 ? "Starting backend…" : "Loading…"; - } - if (Date.now() >= deadline) return null; - await sleep(500); - } -} - -async function validateKey(key) { - const body = { openai_api_key: key }; - const resp = await fetch("/validate_api_key", { - method: "POST", - headers: { "Content-Type": "application/json" }, - body: JSON.stringify(body), - }); - const data = await resp.json().catch(() => ({})); - if (!resp.ok) { - throw new Error(data.error || "validation_failed"); - } - return data; -} - -async function saveKey(key) { - const body = { openai_api_key: key }; - const resp = await fetch("/openai_api_key", { - method: "POST", - headers: { "Content-Type": "application/json" }, - body: JSON.stringify(body), - }); - if (!resp.ok) { - const data = await resp.json().catch(() => ({})); - throw new Error(data.error || "save_failed"); - } - return await resp.json(); -} - -function show(el, flag) { - el.classList.toggle("hidden", !flag); -} - -async function init() { - const loading = document.getElementById("loading"); - const statusEl = document.getElementById("status"); - const formPanel = document.getElementById("form-panel"); - const configuredPanel = document.getElementById("configured"); - const saveBtn = document.getElementById("save-btn"); - const changeKeyBtn = document.getElementById("change-key-btn"); - const input = document.getElementById("api-key"); - - show(loading, true); - show(formPanel, false); - show(configuredPanel, false); - - const st = (await waitForStatus()) || { has_key: false }; - - if (st.has_key) { - show(configuredPanel, true); - } else { - show(formPanel, true); - } - show(loading, false); - - changeKeyBtn.addEventListener("click", () => { - show(configuredPanel, false); - show(formPanel, true); - input.value = ""; - statusEl.textContent = ""; - statusEl.className = "status"; - }); - - input.addEventListener("input", () => { - input.classList.remove("error"); - }); - - saveBtn.addEventListener("click", async () => { - const key = input.value.trim(); - if (!key) { - statusEl.textContent = "Please enter a valid key."; - statusEl.className = "status warn"; - input.classList.add("error"); - return; - } - statusEl.textContent = "Validating API key..."; - statusEl.className = "status"; - input.classList.remove("error"); - try { - const validation = await validateKey(key); - if (!validation.valid) { - statusEl.textContent = "Invalid API key. Please check your key and try again."; - statusEl.className = "status error"; - input.classList.add("error"); - return; - } - statusEl.textContent = "Key valid! Saving..."; - statusEl.className = "status ok"; - await saveKey(key); - statusEl.textContent = "Saved. Reloading…"; - statusEl.className = "status ok"; - window.location.reload(); - } catch (e) { - input.classList.add("error"); - if (e.message === "invalid_api_key") { - statusEl.textContent = "Invalid API key. Please check your key and try again."; - } else { - statusEl.textContent = "Failed to validate/save key. Please try again."; - } - statusEl.className = "status error"; - } - }); -} - -window.addEventListener("DOMContentLoaded", init); \ No newline at end of file diff --git a/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/static/style.css b/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/static/style.css deleted file mode 100644 index 1f8f0c8f..00000000 --- a/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/static/style.css +++ /dev/null @@ -1,210 +0,0 @@ -:root { - --bg: #060b1a; - --bg-2: #071023; - --panel: rgba(11, 18, 36, 0.8); - --border: rgba(255, 255, 255, 0.08); - --text: #eaf2ff; - --muted: #9fb6d7; - --ok: #4ce0b3; - --warn: #ffb547; - --error: #ff5c70; - --accent: #45c4ff; - --accent-2: #5ef0c1; - --shadow: 0 20px 70px rgba(0, 0, 0, 0.45); -} - -* { box-sizing: border-box; } -body { - margin: 0; - min-height: 100vh; - font-family: "Space Grotesk", "Inter", "Segoe UI", sans-serif; - background: radial-gradient(circle at 20% 20%, rgba(69, 196, 255, 0.16), transparent 35%), - radial-gradient(circle at 80% 0%, rgba(94, 240, 193, 0.16), transparent 32%), - linear-gradient(135deg, var(--bg), var(--bg-2)); - color: var(--text); -} - -.ambient { - position: fixed; - inset: 0; - background: radial-gradient(circle at 30% 60%, rgba(255, 255, 255, 0.05), transparent 35%), - radial-gradient(circle at 75% 30%, rgba(69, 196, 255, 0.08), transparent 32%); - filter: blur(60px); - z-index: 0; - pointer-events: none; -} - -.loading { - position: fixed; - inset: 0; - background: rgba(5, 10, 24, 0.92); - backdrop-filter: blur(4px); - display: flex; - flex-direction: column; - align-items: center; - justify-content: center; - z-index: 9999; -} -.loading .spinner { - width: 46px; - height: 46px; - border: 4px solid rgba(255,255,255,0.15); - border-top-color: var(--accent); - border-radius: 50%; - animation: spin 1s linear infinite; - margin-bottom: 12px; -} -.loading p { color: var(--muted); margin: 0; letter-spacing: 0.4px; } -@keyframes spin { to { transform: rotate(360deg); } } - -.container { - position: relative; - max-width: 600px; - margin: 10vh auto; - padding: 0 24px 40px; - z-index: 1; -} - -.hero { - margin-bottom: 24px; -} -.hero h1 { - margin: 6px 0 6px; - font-size: 32px; - letter-spacing: -0.4px; -} -.subtitle { - margin: 0; - color: var(--muted); - line-height: 1.5; -} -.pill { - display: inline-flex; - align-items: center; - gap: 6px; - padding: 6px 12px; - border-radius: 999px; - background: rgba(94, 240, 193, 0.1); - color: var(--accent-2); - font-size: 12px; - letter-spacing: 0.3px; - border: 1px solid rgba(94, 240, 193, 0.25); -} - -.panel { - background: var(--panel); - border: 1px solid var(--border); - border-radius: 14px; - padding: 18px 18px 16px; - box-shadow: var(--shadow); - backdrop-filter: blur(10px); - margin-top: 16px; -} -.panel-heading { - display: flex; - align-items: center; - justify-content: space-between; - gap: 12px; - margin-bottom: 8px; -} -.panel-heading h2 { - margin: 2px 0; - font-size: 22px; -} -.eyebrow { - margin: 0; - text-transform: uppercase; - font-size: 11px; - letter-spacing: 0.5px; - color: var(--muted); -} -.muted { color: var(--muted); } -.chip { - display: inline-flex; - align-items: center; - padding: 6px 10px; - border-radius: 999px; - font-size: 12px; - color: var(--text); - background: rgba(255, 255, 255, 0.08); - border: 1px solid var(--border); -} -.chip-ok { - background: rgba(76, 224, 179, 0.15); - color: var(--ok); - border-color: rgba(76, 224, 179, 0.4); -} - -.hidden { display: none; } -label { - display: block; - margin: 8px 0 6px; - font-size: 13px; - color: var(--muted); - letter-spacing: 0.2px; -} -input[type="password"], -input[type="text"] { - width: 100%; - padding: 12px 14px; - border: 1px solid var(--border); - border-radius: 10px; - background: rgba(255, 255, 255, 0.04); - color: var(--text); - transition: border 0.15s ease, box-shadow 0.15s ease; -} -input:focus { - border-color: rgba(94, 240, 193, 0.7); - outline: none; - box-shadow: 0 0 0 3px rgba(94, 240, 193, 0.15); -} -input.error { - border-color: var(--error); - box-shadow: 0 0 0 3px rgba(255, 92, 112, 0.15); -} - -button { - display: inline-flex; - align-items: center; - justify-content: center; - margin-top: 12px; - padding: 11px 16px; - border: none; - border-radius: 10px; - background: linear-gradient(120deg, var(--accent), var(--accent-2)); - color: #031022; - cursor: pointer; - font-weight: 600; - letter-spacing: 0.2px; - box-shadow: 0 14px 40px rgba(69, 196, 255, 0.25); - transition: transform 0.12s ease, filter 0.12s ease, box-shadow 0.12s ease; -} -button:hover { filter: brightness(1.06); transform: translateY(-1px); } -button:active { transform: translateY(0); } -button.ghost { - background: rgba(255, 255, 255, 0.05); - color: var(--text); - box-shadow: none; - border: 1px solid var(--border); -} -button.ghost:hover { border-color: rgba(94, 240, 193, 0.4); } -.actions { - display: flex; - align-items: center; - gap: 12px; - flex-wrap: wrap; -} -.status { - margin: 0; - color: var(--muted); - font-size: 13px; -} -.status.ok { color: var(--ok); } -.status.warn { color: var(--warn); } -.status.error { color: var(--error); } - -@media (max-width: 760px) { - .hero h1 { font-size: 26px; } - button { width: 100%; justify-content: center; } - .actions { flex-direction: column; align-items: flex-start; } -} \ No newline at end of file diff --git a/projects/reachy-mini-openshell/tests/test_openai_realtime.py b/projects/reachy-mini-openshell/tests/test_openai_realtime.py index 39a82e3e..4a014ab4 100644 --- a/projects/reachy-mini-openshell/tests/test_openai_realtime.py +++ b/projects/reachy-mini-openshell/tests/test_openai_realtime.py @@ -20,6 +20,12 @@ def _build_handler(loop: asyncio.AbstractEventLoop) -> OpenaiRealtimeHandler: return OpenaiRealtimeHandler(deps) +def _set_openai_test_config(monkeypatch: Any) -> None: + monkeypatch.setattr(rt_mod.config, "OPENAI_API_KEY", "test-key") + monkeypatch.setattr(rt_mod.config, "OPENAI_BASE_URL", "https://example.test/v1") + monkeypatch.setattr(rt_mod.config, "MODEL_NAME", "test-realtime-model") + + def test_format_timestamp_uses_wall_clock() -> None: """Test that format_timestamp uses wall clock time.""" loop = asyncio.new_event_loop() @@ -44,6 +50,7 @@ async def test_start_up_retries_on_abrupt_close(monkeypatch: Any, caplog: Any) - Ensures handler clears self.connection at the end. """ caplog.set_level(logging.WARNING) + _set_openai_test_config(monkeypatch) # Use a local Exception as the module's ConnectionClosedError to avoid ws dependency FakeCCE = type("FakeCCE", (Exception,), {}) @@ -120,6 +127,330 @@ def __init__(self, **_kw: Any) -> None: self.realtime = FakeRealtime() warnings = [r for r in caplog.records if r.levelname == "WARNING" and "closed unexpectedly" in r.msg] assert len(warnings) == 1 + +@pytest.mark.asyncio +async def test_start_up_passes_env_base_url_to_openai_client(monkeypatch: Any) -> None: + """OPENAI_API_KEY and OPENAI_BASE_URL come from config and are passed to the SDK.""" + _set_openai_test_config(monkeypatch) + client_kwargs: dict[str, Any] = {} + + class FakeConn: + async def __aenter__(self) -> "FakeConn": return self + async def __aexit__(self, exc_type: Any, exc: Any, tb: Any) -> bool: return False + def __aiter__(self) -> "FakeConn": return self + async def __anext__(self) -> None: raise StopAsyncIteration + + class _Session: + async def update(self, **_kw: Any) -> None: return None + session = _Session() + + class FakeRealtime: + def connect(self, **_kw: Any) -> FakeConn: + return FakeConn() + + class FakeClient: + def __init__(self, **kwargs: Any) -> None: + client_kwargs.update(kwargs) + self.realtime = FakeRealtime() + + monkeypatch.setattr(rt_mod, "AsyncOpenAI", FakeClient) + + deps = ToolDependencies(reachy_mini=MagicMock(), movement_manager=MagicMock()) + handler = rt_mod.OpenaiRealtimeHandler(deps) + + await handler.start_up() + + assert client_kwargs == { + "api_key": "test-key", + "base_url": "https://example.test/v1", + } + + +@pytest.mark.asyncio +async def test_send_text_message_creates_input_text_and_collects_response(monkeypatch: Any) -> None: + """Text mode sends a user input_text item and returns chatbot updates.""" + _set_openai_test_config(monkeypatch) + event_queue: asyncio.Queue[Any] = asyncio.Queue() + created_items: list[dict[str, Any]] = [] + + class FakeEvent: + def __init__(self, etype: str, **kwargs: Any) -> None: + self.type = etype + for key, value in kwargs.items(): + setattr(self, key, value) + + class FakeSession: + async def update(self, **_kw: Any) -> None: + return None + + class FakeConversationItem: + async def create(self, **kwargs: Any) -> None: + created_items.append(kwargs["item"]) + + class FakeConversation: + item = FakeConversationItem() + + class FakeResponse: + async def create(self, **_kw: Any) -> None: + await event_queue.put(FakeEvent("response.created")) + await event_queue.put(FakeEvent("response.output_audio_transcript.done", transcript="Hello from text mode.")) + await event_queue.put(FakeEvent("response.done", response=MagicMock(usage=None))) + + async def cancel(self, **_kw: Any) -> None: + return None + + class FakeInputAudioBuffer: + async def append(self, **_kw: Any) -> None: + return None + + class FakeConn: + session = FakeSession() + conversation = FakeConversation() + response = FakeResponse() + input_audio_buffer = FakeInputAudioBuffer() + + async def __aenter__(self) -> "FakeConn": + return self + + async def __aexit__(self, exc_type: Any, exc: Any, tb: Any) -> bool: + return False + + def __aiter__(self) -> "FakeConn": + return self + + async def __anext__(self) -> Any: + event = await event_queue.get() + if event is None: + raise StopAsyncIteration + return event + + async def close(self) -> None: + await event_queue.put(None) + + class FakeRealtime: + def connect(self, **_kw: Any) -> FakeConn: + return FakeConn() + + class FakeClient: + def __init__(self, **_kw: Any) -> None: + self.realtime = FakeRealtime() + + monkeypatch.setattr(rt_mod, "AsyncOpenAI", FakeClient) + + deps = ToolDependencies(reachy_mini=MagicMock(), movement_manager=MagicMock()) + handler = rt_mod.OpenaiRealtimeHandler(deps) + + messages = await handler.send_text_message("Hello typed Reachy") + await handler.shutdown() + if handler._text_startup_task is not None: + await asyncio.wait_for(handler._text_startup_task, timeout=1) + + assert created_items == [ + { + "type": "message", + "role": "user", + "content": [{"type": "input_text", "text": "Hello typed Reachy"}], + } + ] + assert messages == [ + {"role": "user", "content": "Hello typed Reachy"}, + {"role": "assistant", "content": "Hello from text mode."}, + ] + + +@pytest.mark.asyncio +async def test_send_text_message_reports_missing_dotenv_key(monkeypatch: Any) -> None: + """Text mode reports the actual missing-key problem instead of a generic connection error.""" + monkeypatch.setattr(rt_mod.config, "OPENAI_API_KEY", "") + monkeypatch.setattr(rt_mod.config, "OPENAI_BASE_URL", "https://inference-api.nvidia.com/v1") + monkeypatch.setattr(rt_mod.config, "MODEL_NAME", "nvidia/nemotron-3-super-120b-a12b") + + deps = ToolDependencies(reachy_mini=MagicMock(), movement_manager=MagicMock()) + handler = rt_mod.OpenaiRealtimeHandler(deps) + + messages = await handler.send_text_message("Hello") + + assert len(messages) == 1 + assert "OPENAI_API_KEY is missing or empty" in messages[0]["content"] + assert "NVIDIA_API_KEY" in messages[0]["content"] + + +@pytest.mark.asyncio +async def test_send_text_message_reports_realtime_startup_failure(monkeypatch: Any) -> None: + """Text mode includes model/base URL context when the Realtime provider rejects startup.""" + monkeypatch.setattr(rt_mod.config, "OPENAI_API_KEY", "test-key") + monkeypatch.setattr(rt_mod.config, "OPENAI_BASE_URL", "https://inference-api.nvidia.com/v1") + monkeypatch.setattr(rt_mod.config, "MODEL_NAME", "gpt-realtime") + + class FakeSession: + async def update(self, **_kw: Any) -> None: + raise RuntimeError("404 not found") + + class FakeConn: + session = FakeSession() + + async def __aenter__(self) -> "FakeConn": + return self + + async def __aexit__(self, exc_type: Any, exc: Any, tb: Any) -> bool: + return False + + class FakeRealtime: + def connect(self, **_kw: Any) -> FakeConn: + return FakeConn() + + class FakeClient: + def __init__(self, **_kw: Any) -> None: + self.realtime = FakeRealtime() + + monkeypatch.setattr(rt_mod, "AsyncOpenAI", FakeClient) + + deps = ToolDependencies(reachy_mini=MagicMock(), movement_manager=MagicMock()) + handler = rt_mod.OpenaiRealtimeHandler(deps) + + messages = await handler.send_text_message("Hello") + + assert len(messages) == 1 + content = messages[0]["content"] + assert "Realtime session.update failed" in content + assert "gpt-realtime" in content + assert "https://inference-api.nvidia.com/v1" in content + assert "Chat Completions" in content + + +@pytest.mark.asyncio +async def test_send_text_message_uses_chat_completions_for_non_realtime_model(monkeypatch: Any) -> None: + """Non-Realtime model IDs use Chat Completions instead of the Realtime websocket.""" + monkeypatch.setattr(rt_mod.config, "OPENAI_API_KEY", "test-key") + monkeypatch.setattr(rt_mod.config, "OPENAI_BASE_URL", "https://inference-api.nvidia.com/v1") + monkeypatch.setattr(rt_mod.config, "MODEL_NAME", "nvidia/nemotron-3-super-120b-a12b") + create_calls: list[dict[str, Any]] = [] + + class FakeMessage: + content = "Hello from Nemotron." + tool_calls: list[Any] = [] + + class FakeChoice: + message = FakeMessage() + + class FakeCompletion: + choices = [FakeChoice()] + + class FakeCompletions: + async def create(self, **kwargs: Any) -> FakeCompletion: + create_calls.append(kwargs) + return FakeCompletion() + + class FakeChat: + completions = FakeCompletions() + + class FakeClient: + def __init__(self, **_kw: Any) -> None: + self.chat = FakeChat() + + monkeypatch.setattr(rt_mod, "AsyncOpenAI", FakeClient) + + deps = ToolDependencies(reachy_mini=MagicMock(), movement_manager=MagicMock()) + handler = rt_mod.OpenaiRealtimeHandler(deps) + + messages = await handler.send_text_message("Hello") + + assert messages == [ + {"role": "user", "content": "Hello"}, + {"role": "assistant", "content": "Hello from Nemotron."}, + ] + assert len(create_calls) == 1 + assert create_calls[0]["model"] == "nvidia/nemotron-3-super-120b-a12b" + assert create_calls[0]["messages"][-1] == {"role": "user", "content": "Hello"} + + +@pytest.mark.asyncio +async def test_chat_completion_tool_follow_up_keeps_tools_param(monkeypatch: Any) -> None: + """Anthropic-compatible backends require tools= on the follow-up after a tool result.""" + monkeypatch.setattr(rt_mod.config, "OPENAI_API_KEY", "test-key") + monkeypatch.setattr(rt_mod.config, "OPENAI_BASE_URL", "https://inference-api.nvidia.com/v1") + monkeypatch.setattr(rt_mod.config, "MODEL_NAME", "azure/anthropic/claude-opus-4-8") + monkeypatch.setattr( + rt_mod, + "get_tool_specs", + lambda: [ + { + "type": "function", + "name": "dance", + "description": "Dance once.", + "parameters": {"type": "object", "properties": {}}, + } + ], + ) + + async def fake_dispatch_tool_call_with_manager(*_args: Any, **_kwargs: Any) -> dict[str, Any]: + return {"ok": True} + + monkeypatch.setattr(rt_mod, "dispatch_tool_call_with_manager", fake_dispatch_tool_call_with_manager) + create_calls: list[dict[str, Any]] = [] + + class FakeFunction: + name = "dance" + arguments = "{}" + + class FakeToolCall: + id = "call_1" + type = "function" + function = FakeFunction() + + def model_dump(self) -> dict[str, Any]: + return { + "id": self.id, + "type": self.type, + "function": { + "name": self.function.name, + "arguments": self.function.arguments, + }, + } + + class FakeToolMessage: + content = "" + tool_calls = [FakeToolCall()] + + class FakeFinalMessage: + content = "I danced." + tool_calls: list[Any] = [] + + class FakeChoice: + def __init__(self, message: Any) -> None: + self.message = message + + class FakeCompletion: + def __init__(self, message: Any) -> None: + self.choices = [FakeChoice(message)] + + class FakeCompletions: + async def create(self, **kwargs: Any) -> FakeCompletion: + create_calls.append(kwargs) + if len(create_calls) == 1: + return FakeCompletion(FakeToolMessage()) + return FakeCompletion(FakeFinalMessage()) + + class FakeChat: + completions = FakeCompletions() + + class FakeClient: + def __init__(self, **_kw: Any) -> None: + self.chat = FakeChat() + + monkeypatch.setattr(rt_mod, "AsyncOpenAI", FakeClient) + + deps = ToolDependencies(reachy_mini=MagicMock(), movement_manager=MagicMock()) + handler = rt_mod.OpenaiRealtimeHandler(deps) + + messages = await handler.send_text_message("Dance") + + assert messages[-1] == {"role": "assistant", "content": "I danced."} + assert len(create_calls) == 2 + assert create_calls[0]["tools"] + assert create_calls[1]["tools"] == create_calls[0]["tools"] + assert any(message["role"] == "tool" for message in create_calls[1]["messages"]) + # ---- Cost calculation tests ---- @@ -193,6 +524,7 @@ async def test_response_sender_retries_on_active_response_rejection(monkeypatch: processing, not mocked out. """ caplog.set_level(logging.DEBUG) + _set_openai_test_config(monkeypatch) FakeCCE = type("FakeCCE", (Exception,), {}) monkeypatch.setattr(rt_mod, "ConnectionClosedError", FakeCCE) From 51ab456572fb49f0c0ac18d99529608b078e874f Mon Sep 17 00:00:00 2001 From: Johnny Greco Date: Wed, 24 Jun 2026 23:17:53 -0400 Subject: [PATCH 09/45] Switch Reachy project type checks to ty --- projects/reachy-mini-openshell/pyproject.toml | 22 ++++---- projects/reachy-mini-openshell/uv.lock | 53 +++++-------------- 2 files changed, 23 insertions(+), 52 deletions(-) diff --git a/projects/reachy-mini-openshell/pyproject.toml b/projects/reachy-mini-openshell/pyproject.toml index ffce601d..be842755 100644 --- a/projects/reachy-mini-openshell/pyproject.toml +++ b/projects/reachy-mini-openshell/pyproject.toml @@ -14,7 +14,15 @@ name = "Pollen Robotics" email = "contact@pollen-robotics.com" [dependency-groups] -dev = [ "pytest", "pytest-asyncio", "ruff==0.12.0", "mypy==1.18.2", "pre-commit", "types-requests", "python-semantic-release>=10.5.3",] +dev = [ + "pytest", + "pytest-asyncio", + "ruff==0.12.0", + "pre-commit", + "types-requests", + "python-semantic-release>=10.5.3", + "ty>=0.0.53", +] [tool.uv] environments = [ @@ -35,15 +43,7 @@ include-package-data = true [tool.ruff] line-length = 119 -exclude = [ ".venv", "dist", "build", "**/__pycache__", "*.egg-info", ".mypy_cache", ".pytest_cache",] - -[tool.mypy] -python_version = "3.12" -files = [ "src/",] -ignore_missing_imports = true -strict = true -show_error_codes = true -warn_unused_ignores = true +exclude = [ ".venv", "dist", "build", "**/__pycache__", "*.egg-info", ".pytest_cache",] [project.entry-points.reachy_mini_apps] reachy_mini_conversation_app = "reachy_mini_conversation_app.main:ReachyMiniConversationApp" @@ -52,7 +52,7 @@ reachy_mini_conversation_app = "reachy_mini_conversation_app.main:ReachyMiniConv "" = "src" [tool.setuptools.package-data] -reachy_mini_conversation_app = [ "images/*", "static/*", "profiles/**/*.py", "profiles/**/*.txt",] +reachy_mini_conversation_app = [ "images/*", "profiles/**/*.py", "profiles/**/*.txt",] [tool.ruff.lint] select = [ "E", "F", "W", "I", "C4", "D",] diff --git a/projects/reachy-mini-openshell/uv.lock b/projects/reachy-mini-openshell/uv.lock index 4438d67d..a3dcec23 100644 --- a/projects/reachy-mini-openshell/uv.lock +++ b/projects/reachy-mini-openshell/uv.lock @@ -1371,36 +1371,6 @@ wheels = [ { url = "https://files.pythonhosted.org/packages/81/08/7036c080d7117f28a4af526d794aab6a84463126db031b007717c1a6676e/multidict-6.7.1-py3-none-any.whl", hash = "sha256:55d97cc6dae627efa6a6e548885712d4864b81110ac76fa4e534c03819fa4a56", size = 12319, upload-time = "2026-01-26T02:46:44.004Z" }, ] -[[package]] -name = "mypy" -version = "1.18.2" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "mypy-extensions", marker = "sys_platform == 'darwin'" }, - { name = "pathspec", marker = "sys_platform == 'darwin'" }, - { name = "tomli", marker = 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notes](research/runtime.md) - [Application skeletons](research/applications.md) +- [Reachy Mini simulator tutorial](research/reachy-mini-conversation-simulator.md) - [Dev Notes](dev-notes/index.md) ## What belongs here diff --git a/docs/research/applications.md b/docs/research/applications.md index d761fb70..2fc8b8e6 100644 --- a/docs/research/applications.md +++ b/docs/research/applications.md @@ -5,6 +5,7 @@ OpenShell applications. ## Candidate skeletons +- [Reachy Mini conversation app simulator tutorial](reachy-mini-conversation-simulator.md) - Agent workflow demo - Research paper companion - Evaluation harness diff --git a/docs/research/reachy-mini-conversation-simulator.md b/docs/research/reachy-mini-conversation-simulator.md new file mode 100644 index 00000000..6a03c44f --- /dev/null +++ b/docs/research/reachy-mini-conversation-simulator.md @@ -0,0 +1,234 @@ +# Reachy Mini Conversation App Simulator Tutorial + +This tutorial walks through the local simulator workflow for the Reachy +OpenShell conversation app. It starts the Reachy Mini daemon in MuJoCo +simulation mode, verifies that the daemon is healthy, launches the Gradio +conversation UI, and shows what to expect in the browser. + +The app in this repository is an OpenShell-oriented fork of the Reachy Mini +conversation app template. The upstream Hugging Face Space is a useful reference +for the broader app family: [pollen-robotics/reachy_mini_conversation_app](https://huggingface.co/spaces/pollen-robotics/reachy_mini_conversation_app/tree/main). + +## What You Need + +- macOS with Python 3.10, 3.11, or 3.12. Python 3.12 is the recommended local + version. +- `uv`. +- An API key for conversation. Microphone mode requires an OpenAI-compatible + Realtime model; text mode can also use OpenAI-compatible Chat Completions + providers such as NVIDIA NIM. +- This repository checked out locally. + +The local dependency set includes `reachy-mini[mujoco]==1.8.0`, so the MuJoCo +simulator backend is installed by the default project sync. + +## 1. Install The Project + +From the repository root: + +```sh +cd projects/reachy-mini-openshell +uv venv --python 3.12 +source .venv/bin/activate +uv sync +cp .env.example .env +``` + +Edit `.env`. For OpenAI Realtime microphone and text input, use: + +```sh +OPENAI_API_KEY=your_api_key_here +OPENAI_BASE_URL=https://api.openai.com/v1 +MODEL_NAME=gpt-realtime +``` + +For NVIDIA-hosted text input through an OpenAI-compatible Chat Completions +endpoint, reference your existing NVIDIA API key environment variable: + +```sh +OPENAI_API_KEY=${NVIDIA_API_KEY} +OPENAI_BASE_URL=https://inference-api.nvidia.com/v1 +MODEL_NAME=azure/anthropic/claude-opus-4-8 +``` + +Use the exact model ID exposed by your provider. For example, NVIDIA model IDs +can look like `nvidia/nemotron-3-super-120b-a12b` or +`azure/anthropic/claude-opus-4-8`, depending on the endpoint and account. + +Those provider values are loaded from `.env` only. The browser UI does not +include fields for credentials, endpoint routing, or model selection. + +Run a quick import check: + +```sh +python - <<'PY' +import mujoco +import reachy_mini + +print("mujoco", mujoco.__version__) +print("reachy_mini", reachy_mini.__version__) +PY +``` + +You should see MuJoCo and Reachy Mini versions printed. If MuJoCo is missing, +rerun `uv sync` from `projects/reachy-mini-openshell`. + +## 2. Start The Simulator Daemon + +Start the Reachy Mini daemon in one terminal: + +```sh +reachy-mini-daemon \ + --sim \ + --scene minimal \ + --headless \ + --no-media \ + --fastapi-host 127.0.0.1 \ + --fastapi-port 8000 \ + --dataset-update-interval 0 +``` + +The important log line is: + +```text +Daemon started successfully. +``` + +The daemon should keep running in that terminal. Leave it open while you use the +conversation app. + +## 3. Verify The Daemon + +Open this URL in your browser: + +```text +http://127.0.0.1:8000/api/daemon/status +``` + +You should see syntax-highlighted JSON in the browser. The exact `version` can +vary, but a healthy simulator daemon should look like this: + +```json +{ + "type": "daemon_status", + "robot_name": "reachy_mini", + "state": "running", + "wireless_version": false, + "desktop_app_daemon": false, + "simulation_enabled": true, + "mockup_sim_enabled": false, + "no_media": true, + "media_released": false, + "camera_specs_name": "", + "backend_status": { + "motor_control_mode": "enabled", + "error": null + }, + "error": null, + "wlan_ip": null, + "version": "1.8.0", + "hardware_id": null +} +``` + +If `state` is `error` and the message mentions MuJoCo, the simulator dependency +is missing from the environment that started the daemon. Stop the daemon, run +`uv sync`, and start it again from the activated project environment. + +## 4. Start The Conversation App + +Open a second terminal, activate the same environment, and start the app: + +```sh +cd projects/reachy-mini-openshell +source .venv/bin/activate +python -m reachy_mini_conversation_app --gradio --no-camera +``` + +The console script is equivalent: + +```sh +reachy-mini-conversation-app --gradio --no-camera +``` + +The app connects to the daemon through the Reachy Mini SDK. In simulator mode it +uses the browser-based Gradio UI. The expected launch line is: + +```text +Running on local URL: http://127.0.0.1:7860 +``` + +If port `7860` is busy, Gradio may choose another local port. Use the URL printed +by the terminal. + +## 5. Open The Gradio UI + +Open the Gradio URL, usually: + +```text +http://127.0.0.1:7860/ +``` + +You should see the `Talk with Reachy Mini` page with an empty chat transcript, +an audio stream panel, and an `Input` selector. + +![Gradio conversation UI for Talk with Reachy Mini](../assets/reachy-mini-openshell/screenshots/gradio-home.png) + +If the app logs that `OPENAI_API_KEY` is missing, stop the app, update `.env`, +and restart it. Credentials are intentionally not entered in the browser. If +`.env` references `${NVIDIA_API_KEY}`, make sure that variable is +exported in the shell that starts the app. + +## 6. Talk To Reachy + +Use `Microphone` mode to speak when `MODEL_NAME` points to a Realtime-capable +model. Click `Click to Access Microphone` in the `Stream` panel and allow +microphone access in the browser. Once the stream starts, speak naturally. + +Use `Text` mode to type instead. Switch `Input` to `Text`, enter a message, and +send it from the text composer. For non-Realtime model IDs such as NVIDIA NIM +models, text mode uses Chat Completions. Tool calls are supported in text mode, +including providers that require the tool schema to remain attached after a tool +result is returned. + +Useful first prompts are: + +```text +Hello Reachy, introduce yourself. +Can you dance? +Look around the room. +Show me a happy emotion. +Stop moving. +``` + +Because this tutorial runs with `--no-camera`, camera and head-tracking features +are disabled. Voice conversation and motion tools are still available through the +simulated daemon. + +## 7. Stop The Demo + +Stop the conversation app with `Ctrl+C` in the app terminal. Then stop the +daemon with `Ctrl+C` in the daemon terminal. + +## Troubleshooting + +If the app cannot connect to the daemon, make sure the daemon terminal is still +running and that its status page reports `state: "running"`. + +If the app starts but the browser does not open automatically, copy the `Running +on local URL` value from the terminal into your browser. + +If the browser cannot access the microphone, check the browser permission prompt +and macOS microphone privacy settings. + +If text mode returns `404 page not found`, check that `OPENAI_BASE_URL` matches +the provider's OpenAI-compatible endpoint and that `MODEL_NAME` is an exact +model ID from that provider. + +If text mode returns `401 Unauthorized` with NVIDIA endpoints, make sure +`OPENAI_API_KEY=${NVIDIA_API_KEY}` resolves to a key that is authorized for +generation, not only model listing. + +If the daemon reports `MuJoCo is not installed`, make sure you started the +daemon from this project environment after running `uv sync`. The dependency is +provided by `reachy-mini[mujoco]==1.8.0`. diff --git a/projects/reachy-mini-openshell/README.md b/projects/reachy-mini-openshell/README.md index 97c1c189..14661352 100644 --- a/projects/reachy-mini-openshell/README.md +++ b/projects/reachy-mini-openshell/README.md @@ -39,6 +39,7 @@ This project contains: - a forked Reachy Mini voice conversation app - OpenAI Realtime audio conversation support +- text conversation support through OpenAI-compatible Chat Completions - Reachy Mini movement, dance, emotion, and look-around tools - a locked OpenShell profile for instructions and tool selection - optional camera, local vision, YOLO head-tracking, and MediaPipe head-tracking @@ -53,7 +54,9 @@ this project. The SDK is pinned to the version compatible with the forked conversation-app dependency stack. - a running Reachy Mini daemon, either connected to hardware or started in simulator mode -- an OpenAI API key for conversation +- an API key for conversation. Microphone mode requires an OpenAI-compatible +Realtime model; text mode can also use OpenAI-compatible Chat Completions +providers such as NVIDIA NIM. ## Install @@ -67,12 +70,27 @@ uv sync cp .env.example .env ``` -Then edit `.env` and set: +Then edit `.env`. For OpenAI Realtime microphone and text input, use: ```bash OPENAI_API_KEY=your_api_key_here +OPENAI_BASE_URL=https://api.openai.com/v1 +MODEL_NAME=gpt-realtime ``` +For NVIDIA-hosted text input through an OpenAI-compatible Chat Completions +endpoint, reference your existing NVIDIA API key environment variable: + +```bash +OPENAI_API_KEY=${NVIDIA_API_KEY} +OPENAI_BASE_URL=https://inference-api.nvidia.com/v1 +MODEL_NAME=azure/anthropic/claude-opus-4-8 +``` + +Use the exact model ID exposed by your provider. For example, NVIDIA model IDs +can look like `nvidia/nemotron-3-super-120b-a12b` or +`azure/anthropic/claude-opus-4-8`, depending on the endpoint and account. + If you are not using `uv`, install the app in editable mode from the project directory: @@ -119,21 +137,22 @@ workflow starts `reachy-mini-daemon --sim` from this environment. ## Configuration -The app loads `.env` from the current directory or a parent directory unless -`REACHY_MINI_SKIP_DOTENV=1` is set. +The app loads `.env` from the current directory or a parent directory. Provider +credentials and routing must be configured in `.env`; they are not accepted from +the browser UI or the Reachy Mini settings UI. -Supported environment variables: +Supported `.env` values: -- `OPENAI_API_KEY`: API key used by OpenAI Realtime. -- `MODEL_NAME`: Realtime model name. Defaults to `gpt-realtime`. +- `OPENAI_API_KEY`: API key used by the configured model provider. This can +reference another exported environment variable, such as +`${NVIDIA_API_KEY}`. +- `OPENAI_BASE_URL`: OpenAI-compatible API base URL. +- `MODEL_NAME`: provider model ID. Model names containing `realtime` use the +Realtime path; other model IDs use Chat Completions for text input. - `LOCAL_VISION_MODEL`: Hugging Face model used with `--local-vision`. - `HF_HOME`: Hugging Face cache directory. Defaults to `./cache`. - `HF_TOKEN`: optional Hugging Face token for gated models. -When running with Gradio, the UI also includes an OpenAI API key field. The -bundled Reachy Mini settings UI can store and validate the key when the app is -run through the Reachy Mini app shell. - ## Run Locally Start the Reachy Mini daemon first. For the local simulator baseline: @@ -165,12 +184,18 @@ In simulator mode, the app auto-enables Gradio. The examples still pass at: ```text -c +http://127.0.0.1:7860/ ``` If port `7860` is busy, Gradio may choose another available local port and print that URL in the terminal. +The Gradio UI includes an `Input` selector. Use `Microphone` for the WebRTC +audio stream with a Realtime-capable model, or switch to `Text` for typed +messages. Text mode uses Chat Completions when `MODEL_NAME` is a non-Realtime +model ID. Tool calls are supported in text mode; the app keeps the tool schema +attached on the post-tool follow-up request for providers that require it. + ## Runtime Flags Useful app flags: @@ -233,8 +258,14 @@ Useful local checks: python -m compileall src tests python -m reachy_mini_conversation_app --help reachy-mini-app-assistant check . +uv run ty check ``` +`ty` is the selected Python type checker for this project. The current copied +conversation-app baseline still reports diagnostics in motion, vision, optional +dependency, and SDK event typing, so use `uv run ty check` as the active audit +while that baseline is tightened. + Tests require the development dependency group: ```bash @@ -251,10 +282,19 @@ name to the app with `--robot-name`. If `--local-vision`, `--head-tracker yolo`, or `--head-tracker mediapipe` fails with an import error, install the matching optional dependency group. +If text mode returns `404 page not found`, check that `OPENAI_BASE_URL` matches +the provider's OpenAI-compatible endpoint and that `MODEL_NAME` is an exact +model ID from that provider. A catalog name, marketing page slug, or doubled +namespace may not be accepted by `/chat/completions`. + +If text mode returns `401 Unauthorized` with NVIDIA endpoints, make sure +`OPENAI_API_KEY=${NVIDIA_API_KEY}` resolves to a key that is authorized for +generation, not only model listing. + If `uv sync` tries to build `pygobject` or `pycairo` on macOS, the resolver is including a Linux media dependency path. This project scopes uv resolution to Darwin for the current local workflow; rerun `uv sync`, and if uv is still using old metadata, clear the package cache with `uv cache clean reachy-mini pygobject pycairo`. If you are running the simulator with `--no-media`, keep `--no-camera` on the -conversation app. \ No newline at end of file +conversation app. diff --git a/zensical.toml b/zensical.toml index 4f4429a5..4a97977d 100644 --- a/zensical.toml +++ b/zensical.toml @@ -10,7 +10,8 @@ nav = [ {"Research Engineering" = [ "research/index.md", "research/runtime.md", - "research/applications.md" + "research/applications.md", + "research/reachy-mini-conversation-simulator.md" ]}, {"Dev Notes" = [ "dev-notes/index.md", From 83ca461821a244ea28b4d1c6cd16ef982cc82e15 Mon Sep 17 00:00:00 2001 From: Johnny Greco Date: Thu, 25 Jun 2026 19:10:16 +0000 Subject: [PATCH 11/45] Fix microphone realtime startup --- projects/reachy-mini-openshell/README.md | 5 ++ .../openai_realtime.py | 39 ++++++-- .../tests/test_openai_realtime.py | 88 ++++++++++++++++++- 3 files changed, 123 insertions(+), 9 deletions(-) diff --git a/projects/reachy-mini-openshell/README.md b/projects/reachy-mini-openshell/README.md index 14661352..5df8a444 100644 --- a/projects/reachy-mini-openshell/README.md +++ b/projects/reachy-mini-openshell/README.md @@ -196,6 +196,11 @@ messages. Text mode uses Chat Completions when `MODEL_NAME` is a non-Realtime model ID. Tool calls are supported in text mode; the app keeps the tool schema attached on the post-tool follow-up request for providers that require it. +If the microphone appears to connect but no transcript or model response +arrives, check the visible chat error and your `.env` values. Microphone mode +requires an OpenAI-compatible Realtime model and endpoint; Chat Completions +providers are supported through the `Text` input mode only. + ## Runtime Flags Useful app flags: diff --git a/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/openai_realtime.py b/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/openai_realtime.py index 7e993157..9d7db348 100644 --- a/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/openai_realtime.py +++ b/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/openai_realtime.py @@ -98,8 +98,9 @@ def __init__(self, deps: ToolDependencies, gradio_mode: bool = False, instance_p # Internal lifecycle flags self._shutdown_requested: bool = False self._connected_event: asyncio.Event = asyncio.Event() - self._text_startup_task: asyncio.Task[None] | None = None + self._realtime_startup_task: asyncio.Task[None] | None = None self._startup_error: str | None = None + self._microphone_error_reported: bool = False # Background tool manager self.tool_manager = BackgroundToolManager() @@ -220,26 +221,37 @@ def _openai_api_key_or_error(self) -> str | None: logger.error(message) return None - async def _ensure_text_session(self) -> bool: - """Start a Realtime session for text-only Gradio input if needed.""" + async def _ensure_realtime_session(self, task_name: str) -> bool: + """Start a Realtime session for Gradio text or microphone input if needed.""" if self.connection is not None: return True - if self._text_startup_task is None or self._text_startup_task.done(): + if self._realtime_startup_task is None or self._realtime_startup_task.done(): self._startup_error = None try: self._connected_event.clear() except Exception: pass - self._text_startup_task = asyncio.create_task(self.start_up(), name="openai-realtime-text") + self._realtime_startup_task = asyncio.create_task(self.start_up(), name=task_name) try: await asyncio.wait_for(self._connected_event.wait(), timeout=10.0) except asyncio.TimeoutError: - logger.warning("Timed out waiting for text Realtime session startup") + logger.warning("Timed out waiting for Realtime session startup") return self.connection is not None + async def _ensure_text_session(self) -> bool: + """Start a Realtime session for text-only Gradio input if needed.""" + return await self._ensure_realtime_session("openai-realtime-text") + + async def _report_microphone_error_once(self, message: str) -> None: + """Show one visible microphone error instead of silently dropping every frame.""" + if self._microphone_error_reported: + return + self._microphone_error_reported = True + await self.output_queue.put(AdditionalOutputs({"role": "assistant", "content": message})) + @staticmethod def _chat_message_from_output(output: AdditionalOutputs) -> dict[str, Any] | None: """Convert a FastRTC AdditionalOutputs payload into a chatbot message.""" @@ -946,7 +958,20 @@ async def receive(self, frame: Tuple[int, NDArray[np.int16]]) -> None: """ if not self.connection: - return + if not self._text_model_uses_realtime(): + self._record_startup_error( + "Microphone mode requires an OpenAI-compatible Realtime model. " + f"Current MODEL_NAME={config.MODEL_NAME!r} uses the text path only; " + "switch Input to Text or configure a Realtime model for microphone input." + ) + await self._report_microphone_error_once(self._not_connected_message()) + return + + if not await self._ensure_realtime_session("openai-realtime-microphone"): + await self._report_microphone_error_once(self._not_connected_message()) + return + + self._microphone_error_reported = False input_sample_rate, audio_frame = frame diff --git a/projects/reachy-mini-openshell/tests/test_openai_realtime.py b/projects/reachy-mini-openshell/tests/test_openai_realtime.py index 4a014ab4..93182722 100644 --- a/projects/reachy-mini-openshell/tests/test_openai_realtime.py +++ b/projects/reachy-mini-openshell/tests/test_openai_realtime.py @@ -1,3 +1,4 @@ +import base64 import random import asyncio import logging @@ -5,6 +6,7 @@ from datetime import datetime, timezone from unittest.mock import MagicMock +import numpy as np import pytest import reachy_mini_conversation_app.openai_realtime as rt_mod @@ -242,8 +244,8 @@ def __init__(self, **_kw: Any) -> None: messages = await handler.send_text_message("Hello typed Reachy") await handler.shutdown() - if handler._text_startup_task is not None: - await asyncio.wait_for(handler._text_startup_task, timeout=1) + if handler._realtime_startup_task is not None: + await asyncio.wait_for(handler._realtime_startup_task, timeout=1) assert created_items == [ { @@ -258,6 +260,88 @@ def __init__(self, **_kw: Any) -> None: ] +@pytest.mark.asyncio +async def test_receive_lazily_starts_realtime_and_appends_microphone_audio(monkeypatch: Any) -> None: + """Mic frames should start the Realtime session before appending audio.""" + _set_openai_test_config(monkeypatch) + event_queue: asyncio.Queue[Any] = asyncio.Queue() + appended_audio: list[str] = [] + + class FakeSession: + async def update(self, **_kw: Any) -> None: + return None + + class FakeInputAudioBuffer: + async def append(self, **kwargs: Any) -> None: + appended_audio.append(kwargs["audio"]) + + class FakeConn: + session = FakeSession() + input_audio_buffer = FakeInputAudioBuffer() + + async def __aenter__(self) -> "FakeConn": + return self + + async def __aexit__(self, exc_type: Any, exc: Any, tb: Any) -> bool: + return False + + def __aiter__(self) -> "FakeConn": + return self + + async def __anext__(self) -> Any: + event = await event_queue.get() + if event is None: + raise StopAsyncIteration + return event + + async def close(self) -> None: + await event_queue.put(None) + + class FakeRealtime: + def connect(self, **_kw: Any) -> FakeConn: + return FakeConn() + + class FakeClient: + def __init__(self, **_kw: Any) -> None: + self.realtime = FakeRealtime() + + monkeypatch.setattr(rt_mod, "AsyncOpenAI", FakeClient) + + deps = ToolDependencies(reachy_mini=MagicMock(), movement_manager=MagicMock()) + handler = rt_mod.OpenaiRealtimeHandler(deps) + audio_frame = np.array([0, 1000, -1000, 0], dtype=np.int16) + + await handler.receive((24000, audio_frame)) + await handler.shutdown() + if handler._realtime_startup_task is not None: + await asyncio.wait_for(handler._realtime_startup_task, timeout=1) + + assert appended_audio == [base64.b64encode(audio_frame.tobytes()).decode("utf-8")] + + +@pytest.mark.asyncio +async def test_receive_reports_non_realtime_model_without_opening_realtime(monkeypatch: Any) -> None: + """Mic mode should visibly fail when MODEL_NAME can only use text completions.""" + monkeypatch.setattr(rt_mod.config, "OPENAI_API_KEY", "test-key") + monkeypatch.setattr(rt_mod.config, "OPENAI_BASE_URL", "https://inference-api.nvidia.com/v1") + monkeypatch.setattr(rt_mod.config, "MODEL_NAME", "nvidia/nemotron-3-super-120b-a12b") + + def fail_openai_client(**_kw: Any) -> None: + raise AssertionError("microphone mode should not open Realtime for a non-Realtime model") + + monkeypatch.setattr(rt_mod, "AsyncOpenAI", fail_openai_client) + + deps = ToolDependencies(reachy_mini=MagicMock(), movement_manager=MagicMock()) + handler = rt_mod.OpenaiRealtimeHandler(deps) + + await handler.receive((24000, np.array([0, 0], dtype=np.int16))) + + output = await asyncio.wait_for(handler.output_queue.get(), timeout=1) + assert isinstance(output, rt_mod.AdditionalOutputs) + assert "Microphone mode requires an OpenAI-compatible Realtime model" in output.args[0]["content"] + assert handler.connection is None + + @pytest.mark.asyncio async def test_send_text_message_reports_missing_dotenv_key(monkeypatch: Any) -> None: """Text mode reports the actual missing-key problem instead of a generic connection error.""" From ab10adbc7c43e902a4b133c9d5baff35a52088c0 Mon Sep 17 00:00:00 2001 From: Johnny Greco Date: Thu, 25 Jun 2026 19:14:52 +0000 Subject: [PATCH 12/45] Add one-step Reachy app launcher --- projects/reachy-mini-openshell/README.md | 38 +++-- .../scripts/start-local.sh | 153 ++++++++++++++++++ 2 files changed, 175 insertions(+), 16 deletions(-) create mode 100755 projects/reachy-mini-openshell/scripts/start-local.sh diff --git a/projects/reachy-mini-openshell/README.md b/projects/reachy-mini-openshell/README.md index 5df8a444..c771d959 100644 --- a/projects/reachy-mini-openshell/README.md +++ b/projects/reachy-mini-openshell/README.md @@ -155,40 +155,46 @@ Realtime path; other model IDs use Chat Completions for text input. ## Run Locally -Start the Reachy Mini daemon first. For the local simulator baseline: +Use the local launcher for the simulator baseline: ```bash -reachy-mini-daemon --sim --scene minimal --headless --no-media --fastapi-host 127.0.0.1 --fastapi-port 8000 --dataset-update-interval 0 +projects/reachy-mini-openshell/scripts/start-local.sh ``` -You can verify the daemon separately at: +The script creates `.venv` when needed, runs `uv sync`, creates `.env` from +`.env.example` if missing, starts `reachy-mini-daemon --sim`, launches the +Gradio app, and prints the browser URL: ```text -http://127.0.0.1:8000/api/daemon/status +http://127.0.0.1:7860/ ``` -Then run the conversation app: +If port `7860` is busy, the launcher chooses the next free port through `7899` +and prints that URL instead. Pass app flags after the script name: ```bash -python -m reachy_mini_conversation_app --gradio --no-camera +projects/reachy-mini-openshell/scripts/start-local.sh --debug +projects/reachy-mini-openshell/scripts/start-local.sh --head-tracker yolo ``` -The installed console script is equivalent: +From inside `projects/reachy-mini-openshell`, the shorter form is: ```bash -reachy-mini-conversation-app --gradio --no-camera +./scripts/start-local.sh --debug ``` -In simulator mode, the app auto-enables Gradio. The examples still pass -`--gradio` so the expected browser interface is explicit. Gradio usually opens -at: +Useful launcher environment variables: -```text -http://127.0.0.1:7860/ -``` +- `APP_PORT=7861`: request a specific Gradio port. +- `DAEMON_PORT=8001`: use a different Reachy daemon port. +- `REACHY_SKIP_SYNC=1`: skip `uv sync` after dependencies are already installed. -If port `7860` is busy, Gradio may choose another available local port and print -that URL in the terminal. +The manual equivalent, useful for debugging, is: + +```bash +reachy-mini-daemon --sim --scene minimal --headless --no-media --fastapi-host 127.0.0.1 --fastapi-port 8000 --dataset-update-interval 0 +python -m reachy_mini_conversation_app --gradio --no-camera +``` The Gradio UI includes an `Input` selector. Use `Microphone` for the WebRTC audio stream with a Realtime-capable model, or switch to `Text` for typed diff --git a/projects/reachy-mini-openshell/scripts/start-local.sh b/projects/reachy-mini-openshell/scripts/start-local.sh new file mode 100755 index 00000000..88f43b48 --- /dev/null +++ b/projects/reachy-mini-openshell/scripts/start-local.sh @@ -0,0 +1,153 @@ +#!/usr/bin/env bash +set -euo pipefail + +SCRIPT_DIR="$(cd -- "$(dirname -- "${BASH_SOURCE[0]}")" && pwd)" +PROJECT_DIR="$(cd -- "${SCRIPT_DIR}/.." && pwd)" +LAUNCHER_PATH="${BASH_SOURCE[0]}" + +cd "${PROJECT_DIR}" + +APP_HOST="${APP_HOST:-127.0.0.1}" +APP_PORT="${APP_PORT:-}" +APP_PORT_START="${APP_PORT_START:-7860}" +APP_PORT_END="${APP_PORT_END:-7899}" +DAEMON_HOST="${DAEMON_HOST:-127.0.0.1}" +DAEMON_PORT="${DAEMON_PORT:-8000}" +PYTHON_VERSION="${PYTHON_VERSION:-3.12}" +REACHY_SKIP_SYNC="${REACHY_SKIP_SYNC:-0}" +REACHY_DAEMON_TIMEOUT="${REACHY_DAEMON_TIMEOUT:-45}" + +DAEMON_PID="" + +log() { + printf '[reachy-start] %s\n' "$*" +} + +finish() { + if [[ -n "${DAEMON_PID}" ]]; then + log "Stopping simulator daemon pid=${DAEMON_PID}" + kill "${DAEMON_PID}" >/dev/null 2>&1 || true + wait "${DAEMON_PID}" >/dev/null 2>&1 || true + fi +} +trap finish EXIT INT TERM + +require_command() { + if ! command -v "$1" >/dev/null 2>&1; then + printf 'Missing required command: %s\n' "$1" >&2 + exit 1 + fi +} + +daemon_status_ok() { + "${PROJECT_DIR}/.venv/bin/python" - "$DAEMON_HOST" "$DAEMON_PORT" <<'PY' >/dev/null 2>&1 +import sys +import urllib.request + +host, port = sys.argv[1], sys.argv[2] +try: + with urllib.request.urlopen(f"http://{host}:{port}/api/daemon/status", timeout=1.5) as response: + raise SystemExit(0 if 200 <= response.status < 500 else 1) +except Exception: + raise SystemExit(1) +PY +} + +pick_app_port() { + if [[ -n "${APP_PORT}" ]]; then + "${PROJECT_DIR}/.venv/bin/python" - "$APP_HOST" "$APP_PORT" <<'PY' +import socket +import sys + +host = sys.argv[1] +port = int(sys.argv[2]) + +with socket.socket(socket.AF_INET, socket.SOCK_STREAM) as sock: + sock.settimeout(0.2) + if sock.connect_ex((host, port)) == 0: + raise SystemExit(f"Requested APP_PORT={port} is already in use") +PY + printf '%s\n' "${APP_PORT}" + return + fi + + "${PROJECT_DIR}/.venv/bin/python" - "$APP_HOST" "$APP_PORT_START" "$APP_PORT_END" <<'PY' +import socket +import sys + +host = sys.argv[1] +start = int(sys.argv[2]) +end = int(sys.argv[3]) + +for port in range(start, end + 1): + with socket.socket(socket.AF_INET, socket.SOCK_STREAM) as sock: + sock.settimeout(0.2) + if sock.connect_ex((host, port)) != 0: + print(port) + raise SystemExit(0) + +raise SystemExit(f"No free app port found in {start}-{end}") +PY +} + +require_command uv + +if [[ ! -x "${PROJECT_DIR}/.venv/bin/python" ]]; then + log "Creating virtual environment with Python ${PYTHON_VERSION}" + uv venv --python "${PYTHON_VERSION}" +fi + +if [[ "${REACHY_SKIP_SYNC}" != "1" ]]; then + log "Installing project dependencies with uv sync" + if ! uv sync; then + cat >&2 <<'EOF' + +uv sync failed. This project currently has a platform-specific uv.lock. +After installing dependencies another way, rerun with: + + REACHY_SKIP_SYNC=1 ${LAUNCHER_PATH} + +EOF + exit 1 + fi +fi + +if [[ ! -f ".env" ]]; then + cp .env.example .env + log "Created .env from .env.example. Edit it if you need different provider credentials." +fi + +export PATH="${PROJECT_DIR}/.venv/bin:${PATH}" + +if daemon_status_ok; then + log "Using existing Reachy daemon at http://${DAEMON_HOST}:${DAEMON_PORT}" +else + log "Starting Reachy simulator daemon at http://${DAEMON_HOST}:${DAEMON_PORT}" + reachy-mini-daemon \ + --sim \ + --scene minimal \ + --headless \ + --no-media \ + --fastapi-host "${DAEMON_HOST}" \ + --fastapi-port "${DAEMON_PORT}" \ + --dataset-update-interval 0 & + DAEMON_PID="$!" + + log "Waiting for simulator daemon" + deadline=$((SECONDS + REACHY_DAEMON_TIMEOUT)) + until daemon_status_ok; do + if (( SECONDS >= deadline )); then + printf 'Reachy simulator daemon did not become ready within %s seconds.\n' "${REACHY_DAEMON_TIMEOUT}" >&2 + exit 1 + fi + sleep 1 + done +fi + +SELECTED_APP_PORT="$(pick_app_port)" +export GRADIO_SERVER_NAME="${APP_HOST}" +export GRADIO_SERVER_PORT="${SELECTED_APP_PORT}" + +log "Starting Reachy conversation app" +log "Open: http://${APP_HOST}:${SELECTED_APP_PORT}/" +"${PROJECT_DIR}/.venv/bin/python" -m reachy_mini_conversation_app --gradio --no-camera "$@" From 8baa4de67a55926cca89bf51124cc8ad0c81ba2e Mon Sep 17 00:00:00 2001 From: Johnny Greco Date: Thu, 25 Jun 2026 22:41:57 +0000 Subject: [PATCH 13/45] Add Riva STT microphone mode --- projects/reachy-mini-openshell/.env.example | 15 + projects/reachy-mini-openshell/README.md | 49 +- projects/reachy-mini-openshell/pyproject.toml | 11 + .../reachy_mini_conversation_app/config.py | 1 + .../src/reachy_mini_conversation_app/main.py | 20 +- .../openai_realtime.py | 125 ++- .../reachy_mini_conversation_app/riva_asr.py | 202 ++++ .../tests/test_openai_realtime.py | 72 +- projects/reachy-mini-openshell/uv.lock | 919 ++++++++++-------- 9 files changed, 951 insertions(+), 463 deletions(-) create mode 100644 projects/reachy-mini-openshell/src/reachy_mini_conversation_app/riva_asr.py diff --git a/projects/reachy-mini-openshell/.env.example b/projects/reachy-mini-openshell/.env.example index 42515c10..2a82e724 100644 --- a/projects/reachy-mini-openshell/.env.example +++ b/projects/reachy-mini-openshell/.env.example @@ -2,6 +2,21 @@ OPENAI_API_KEY=${NVIDIA_API_KEY} OPENAI_BASE_URL=https://inference-api.nvidia.com/v1 MODEL_NAME=azure/anthropic/claude-opus-4-8 +# Audio input modes: +# - openai_realtime: microphone audio goes to an OpenAI-compatible Realtime endpoint. +# - riva_stt: microphone audio goes to Riva ASR; final transcripts go to the text LLM path. +AUDIO_INPUT_MODE=openai_realtime + +# Used only when AUDIO_INPUT_MODE=riva_stt. +RIVA_SERVER_URI=localhost:50051 +RIVA_USE_SSL=false +RIVA_LANGUAGE_CODE=en-US +RIVA_ASR_MODEL= +RIVA_AUTHORIZATION= +RIVA_METADATA= +RIVA_INTERIM_RESULTS=true +RIVA_AUTOMATIC_PUNCTUATION=true + # Used only with --local-vision. LOCAL_VISION_MODEL=HuggingFaceTB/SmolVLM2-2.2B-Instruct diff --git a/projects/reachy-mini-openshell/README.md b/projects/reachy-mini-openshell/README.md index c771d959..9470fe58 100644 --- a/projects/reachy-mini-openshell/README.md +++ b/projects/reachy-mini-openshell/README.md @@ -39,6 +39,7 @@ This project contains: - a forked Reachy Mini voice conversation app - OpenAI Realtime audio conversation support +- Riva streaming ASR support for microphone-to-text input - text conversation support through OpenAI-compatible Chat Completions - Reachy Mini movement, dance, emotion, and look-around tools - a locked OpenShell profile for instructions and tool selection @@ -54,9 +55,9 @@ this project. The SDK is pinned to the version compatible with the forked conversation-app dependency stack. - a running Reachy Mini daemon, either connected to hardware or started in simulator mode -- an API key for conversation. Microphone mode requires an OpenAI-compatible -Realtime model; text mode can also use OpenAI-compatible Chat Completions -providers such as NVIDIA NIM. +- an API key for conversation. OpenAI Realtime microphone mode requires an +OpenAI-compatible Realtime model; Riva STT and text mode can use +OpenAI-compatible Chat Completions providers such as NVIDIA NIM. ## Install @@ -112,9 +113,10 @@ and regenerate `uv.lock` for that platform. ## Optional Dependencies -The active optional dependency groups are vision-related only: +The active optional dependency groups cover Riva ASR and vision: ```bash +uv sync --extra riva uv sync --extra local_vision uv sync --extra yolo_vision uv sync --extra mediapipe_vision @@ -124,12 +126,17 @@ uv sync --extra all_vision With `pip`, use the equivalent editable installs: ```bash +python -m pip install -e '.[riva]' python -m pip install -e '.[local_vision]' python -m pip install -e '.[yolo_vision]' python -m pip install -e '.[mediapipe_vision]' python -m pip install -e '.[all_vision]' ``` +The `riva` extra is intentionally marked incompatible with `mediapipe_vision` +and `all_vision` because the current Riva and MediaPipe client stacks require +different protobuf ranges. + There are no project-level `backend` or `sim` extras anymore. The previous backend extra belonged to the deleted scaffold. The default dependency set includes Reachy Mini's MuJoCo simulator backend because the local development @@ -149,6 +156,19 @@ reference another exported environment variable, such as - `OPENAI_BASE_URL`: OpenAI-compatible API base URL. - `MODEL_NAME`: provider model ID. Model names containing `realtime` use the Realtime path; other model IDs use Chat Completions for text input. +- `AUDIO_INPUT_MODE`: microphone routing mode. Use `openai_realtime` for the +template default, where audio goes to an OpenAI-compatible Realtime endpoint. +Use `riva_stt` to stream microphone audio to Riva ASR and pass final +transcripts into the text LLM path. +- `RIVA_SERVER_URI`: Riva ASR server URI, for example `localhost:50051`. +- `RIVA_USE_SSL`: set to `true` for TLS-enabled Riva endpoints. +- `RIVA_LANGUAGE_CODE`: BCP-47 language code for Riva ASR, such as `en-US`. +- `RIVA_ASR_MODEL`: optional Riva ASR model name. Leave empty to let Riva +select a model from the language/configuration. +- `RIVA_AUTHORIZATION`: optional authorization metadata value, such as a bearer +token, for hosted Riva endpoints. +- `RIVA_METADATA`: optional comma-separated `key=value` metadata pairs passed +to the Riva client. - `LOCAL_VISION_MODEL`: Hugging Face model used with `--local-vision`. - `HF_HOME`: Hugging Face cache directory. Defaults to `./cache`. - `HF_TOKEN`: optional Hugging Face token for gated models. @@ -196,16 +216,19 @@ reachy-mini-daemon --sim --scene minimal --headless --no-media --fastapi-host 12 python -m reachy_mini_conversation_app --gradio --no-camera ``` -The Gradio UI includes an `Input` selector. Use `Microphone` for the WebRTC -audio stream with a Realtime-capable model, or switch to `Text` for typed -messages. Text mode uses Chat Completions when `MODEL_NAME` is a non-Realtime -model ID. Tool calls are supported in text mode; the app keeps the tool schema -attached on the post-tool follow-up request for providers that require it. +The Gradio UI includes an `Input` selector: + +- `OpenAI Realtime`: template-default microphone behavior. Audio streams to an +OpenAI-compatible Realtime endpoint, which handles transcription and response +generation in one session. +- `Riva STT`: microphone audio streams to Riva ASR. Final transcripts are sent +to the same text LLM path used by typed messages, so OpenAI-compatible Chat +Completions providers such as NVIDIA NIM can answer. +- `Text`: typed messages only. -If the microphone appears to connect but no transcript or model response -arrives, check the visible chat error and your `.env` values. Microphone mode -requires an OpenAI-compatible Realtime model and endpoint; Chat Completions -providers are supported through the `Text` input mode only. +Tool calls are supported in text mode and in the Riva STT path; the app keeps +the tool schema attached on the post-tool follow-up request for providers that +require it. ## Runtime Flags diff --git a/projects/reachy-mini-openshell/pyproject.toml b/projects/reachy-mini-openshell/pyproject.toml index be842755..a9a7a66e 100644 --- a/projects/reachy-mini-openshell/pyproject.toml +++ b/projects/reachy-mini-openshell/pyproject.toml @@ -28,8 +28,19 @@ dev = [ environments = [ "sys_platform == 'darwin'", ] +conflicts = [ + [ + { extra = "riva" }, + { extra = "mediapipe_vision" }, + ], + [ + { extra = "riva" }, + { extra = "all_vision" }, + ], +] [project.optional-dependencies] +riva = [ "nvidia-riva-client>=2.19,<3",] local_vision = [ "torch>=2.1", "transformers==5.0.0rc2", "num2words",] yolo_vision = [ "ultralytics", "supervision",] mediapipe_vision = [ "mediapipe==0.10.14",] diff --git a/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/config.py b/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/config.py index 6cf01c4f..bb04df19 100644 --- a/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/config.py +++ b/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/config.py @@ -72,6 +72,7 @@ class Config: OPENAI_API_KEY = _dotenv_value("OPENAI_API_KEY") OPENAI_BASE_URL = _dotenv_value("OPENAI_BASE_URL", "https://api.openai.com/v1") MODEL_NAME = os.getenv("MODEL_NAME", "gpt-realtime") + AUDIO_INPUT_MODE = os.getenv("AUDIO_INPUT_MODE", "openai_realtime") HF_HOME = os.getenv("HF_HOME", "./cache") LOCAL_VISION_MODEL = os.getenv("LOCAL_VISION_MODEL", "HuggingFaceTB/SmolVLM2-2.2B-Instruct") HF_TOKEN = os.getenv("HF_TOKEN") diff --git a/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/main.py b/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/main.py index f618aef4..3382e089 100644 --- a/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/main.py +++ b/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/main.py @@ -49,8 +49,13 @@ def run( # Putting these dependencies here makes the dashboard faster to load when the conversation app is installed from reachy_mini_conversation_app.moves import MovementManager + from reachy_mini_conversation_app.config import config from reachy_mini_conversation_app.console import LocalStream - from reachy_mini_conversation_app.openai_realtime import OpenaiRealtimeHandler + from reachy_mini_conversation_app.openai_realtime import ( + AUDIO_MODE_RIVA_STT, + AUDIO_MODE_OPENAI_REALTIME, + OpenaiRealtimeHandler, + ) from reachy_mini_conversation_app.tools.core_tools import ToolDependencies from reachy_mini_conversation_app.audio.head_wobbler import HeadWobbler @@ -157,9 +162,16 @@ def run( stream_manager = stream.ui with stream_manager: + input_mode_choices = { + "OpenAI Realtime": AUDIO_MODE_OPENAI_REALTIME, + "Riva STT": AUDIO_MODE_RIVA_STT, + "Text": "text", + } + initial_input_mode = "Riva STT" if handler.audio_input_mode == AUDIO_MODE_RIVA_STT else "OpenAI Realtime" + input_mode = gr.Radio( - choices=["Microphone", "Text"], - value="Microphone", + choices=list(input_mode_choices), + value=initial_input_mode, label="Input", ) with gr.Row(): @@ -173,6 +185,8 @@ def run( def switch_input_mode(mode: str) -> tuple[dict[str, Any], dict[str, Any], dict[str, Any]]: text_mode = mode == "Text" + if not text_mode: + handler.set_audio_input_mode(input_mode_choices.get(mode, config.AUDIO_INPUT_MODE)) return ( gr.update(visible=not text_mode), gr.update(visible=text_mode), diff --git a/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/openai_realtime.py b/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/openai_realtime.py index 9d7db348..ad173807 100644 --- a/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/openai_realtime.py +++ b/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/openai_realtime.py @@ -18,6 +18,7 @@ from reachy_mini_conversation_app.config import LOCKED_PROFILE, config from reachy_mini_conversation_app.prompts import get_session_voice, get_session_instructions +from reachy_mini_conversation_app.riva_asr import RivaAsrConfig, RivaStreamingTranscriber from reachy_mini_conversation_app.tools.core_tools import ( ToolDependencies, get_tool_specs, @@ -34,6 +35,9 @@ OPEN_AI_INPUT_SAMPLE_RATE: Final[Literal[24000]] = 24000 OPEN_AI_OUTPUT_SAMPLE_RATE: Final[Literal[24000]] = 24000 +AUDIO_MODE_OPENAI_REALTIME: Final = "openai_realtime" +AUDIO_MODE_RIVA_STT: Final = "riva_stt" +AUDIO_INPUT_MODES: Final = {AUDIO_MODE_OPENAI_REALTIME, AUDIO_MODE_RIVA_STT} # Cost tracking from usage data (pricing as of Feb 2026 https://openai.com/api/pricing/) AUDIO_INPUT_COST_PER_1M = 32.0 @@ -45,6 +49,19 @@ _RESPONSE_DONE_TIMEOUT: Final[float] = 30.0 +def _normalize_audio_input_mode(audio_input_mode: str) -> str: + """Normalize configured audio input mode.""" + normalized = audio_input_mode.strip().lower().replace("-", "_") + if normalized in {"openai", "realtime", "microphone"}: + return AUDIO_MODE_OPENAI_REALTIME + if normalized in {"riva", "riva_asr", "riva_stt"}: + return AUDIO_MODE_RIVA_STT + if normalized not in AUDIO_INPUT_MODES: + logger.warning("Unknown AUDIO_INPUT_MODE=%r; using %s", audio_input_mode, AUDIO_MODE_OPENAI_REALTIME) + return AUDIO_MODE_OPENAI_REALTIME + return normalized + + def _compute_response_cost(usage: Any) -> float: """Compute dollar cost from a response usage object.""" inp = getattr(usage, "input_token_details", None) @@ -63,7 +80,14 @@ def _compute_response_cost(usage: Any) -> float: class OpenaiRealtimeHandler(AsyncStreamHandler): """An OpenAI realtime handler for fastrtc Stream.""" - def __init__(self, deps: ToolDependencies, gradio_mode: bool = False, instance_path: Optional[str] = None): + def __init__( + self, + deps: ToolDependencies, + gradio_mode: bool = False, + instance_path: Optional[str] = None, + audio_input_mode: str | None = None, + audio_input_mode_state: dict[str, str] | None = None, + ): """Initialize the handler.""" super().__init__( expected_layout="mono", @@ -76,6 +100,9 @@ def __init__(self, deps: ToolDependencies, gradio_mode: bool = False, instance_p self.input_sample_rate: Literal[24000] = self.input_sample_rate self.deps = deps + self._audio_input_mode_state = audio_input_mode_state or { + "mode": _normalize_audio_input_mode(audio_input_mode or config.AUDIO_INPUT_MODE) + } # Override type annotations for OpenAI strict typing (only for values used in API) self.output_sample_rate = OPEN_AI_OUTPUT_SAMPLE_RATE @@ -89,6 +116,7 @@ def __init__(self, deps: ToolDependencies, gradio_mode: bool = False, instance_p self.is_idle_tool_call = False self.gradio_mode = gradio_mode self.instance_path = instance_path + self._riva_transcriber: RivaStreamingTranscriber | None = None # Debouncing for partial transcripts self.partial_transcript_task: asyncio.Task[None] | None = None @@ -118,7 +146,21 @@ def __init__(self, deps: ToolDependencies, gradio_mode: bool = False, instance_p def copy(self) -> "OpenaiRealtimeHandler": """Create a copy of the handler.""" - return OpenaiRealtimeHandler(self.deps, self.gradio_mode, self.instance_path) + return OpenaiRealtimeHandler( + self.deps, + self.gradio_mode, + self.instance_path, + audio_input_mode_state=self._audio_input_mode_state, + ) + + @property + def audio_input_mode(self) -> str: + """Return the current shared microphone audio mode.""" + return self._audio_input_mode_state["mode"] + + def set_audio_input_mode(self, audio_input_mode: str) -> None: + """Select how microphone audio should be processed.""" + self._audio_input_mode_state["mode"] = _normalize_audio_input_mode(audio_input_mode) def _record_startup_error(self, message: str) -> None: """Store a startup failure so the UI can show a useful error.""" @@ -947,22 +989,21 @@ async def _run_realtime_session(self) -> None: # Microphone receive async def receive(self, frame: Tuple[int, NDArray[np.int16]]) -> None: - """Receive audio frame from the microphone and send it to the OpenAI server. - - Handles both mono and stereo audio formats, converting to the expected - mono format for OpenAI's API. Resamples if the input sample rate differs - from the expected rate. + """Receive audio frame from the microphone and route it through the selected audio mode.""" + if self.audio_input_mode == AUDIO_MODE_RIVA_STT: + await self._receive_riva_stt(frame) + return - Args: - frame: A tuple containing (sample_rate, audio_data). + await self._receive_openai_realtime_audio(frame) - """ + async def _receive_openai_realtime_audio(self, frame: Tuple[int, NDArray[np.int16]]) -> None: + """Send a microphone frame to the OpenAI Realtime audio session.""" if not self.connection: if not self._text_model_uses_realtime(): self._record_startup_error( - "Microphone mode requires an OpenAI-compatible Realtime model. " + "OpenAI Realtime microphone mode requires an OpenAI-compatible Realtime model. " f"Current MODEL_NAME={config.MODEL_NAME!r} uses the text path only; " - "switch Input to Text or configure a Realtime model for microphone input." + "switch Input to Riva STT/Text or configure a Realtime model for OpenAI Realtime mode." ) await self._report_microphone_error_once(self._not_connected_message()) return @@ -974,8 +1015,39 @@ async def receive(self, frame: Tuple[int, NDArray[np.int16]]) -> None: self._microphone_error_reported = False input_sample_rate, audio_frame = frame + audio_frame = self._prepare_audio_frame(input_sample_rate, audio_frame, target_sample_rate=self.input_sample_rate) - # Reshape if needed + # Send to OpenAI (guard against races during reconnect) + try: + audio_message = base64.b64encode(audio_frame.tobytes()).decode("utf-8") + await self.connection.input_audio_buffer.append(audio=audio_message) + except Exception as e: + logger.debug("Dropping audio frame: connection not ready (%s)", e) + return + + async def _receive_riva_stt(self, frame: Tuple[int, NDArray[np.int16]]) -> None: + """Send a microphone frame to Riva ASR, then route transcripts into the text LLM path.""" + input_sample_rate, audio_frame = frame + audio_frame = self._prepare_audio_frame(input_sample_rate, audio_frame) + + if self._riva_transcriber is None: + self._riva_transcriber = RivaStreamingTranscriber( + config=RivaAsrConfig.from_env(), + on_final_transcript=self._handle_riva_final_transcript, + on_partial_transcript=self._handle_riva_partial_transcript, + ) + await self._riva_transcriber.start(input_sample_rate) + + await self._riva_transcriber.send_audio(audio_frame.tobytes()) + + def _prepare_audio_frame( + self, + input_sample_rate: int, + audio_frame: NDArray[np.int16], + *, + target_sample_rate: int | None = None, + ) -> NDArray[np.int16]: + """Convert incoming audio to mono PCM16, optionally resampling first.""" if audio_frame.ndim == 2: # Scipy channels last convention if audio_frame.shape[1] > audio_frame.shape[0]: @@ -984,21 +1056,22 @@ async def receive(self, frame: Tuple[int, NDArray[np.int16]]) -> None: if audio_frame.shape[1] > 1: audio_frame = audio_frame[:, 0] - # Resample if needed - if self.input_sample_rate != input_sample_rate: - audio_frame = resample(audio_frame, int(len(audio_frame) * self.input_sample_rate / input_sample_rate)) + if target_sample_rate is not None and target_sample_rate != input_sample_rate: + audio_frame = resample(audio_frame, int(len(audio_frame) * target_sample_rate / input_sample_rate)) - # Cast if needed - audio_frame = audio_to_int16(audio_frame) + return audio_to_int16(audio_frame) - # Send to OpenAI (guard against races during reconnect) - try: - audio_message = base64.b64encode(audio_frame.tobytes()).decode("utf-8") - await self.connection.input_audio_buffer.append(audio=audio_message) - except Exception as e: - logger.debug("Dropping audio frame: connection not ready (%s)", e) + async def _handle_riva_partial_transcript(self, transcript: str) -> None: + await self.output_queue.put(AdditionalOutputs({"role": "user_partial", "content": transcript})) + + async def _handle_riva_final_transcript(self, transcript: str) -> None: + if transcript.startswith("[error]"): + await self.output_queue.put(AdditionalOutputs({"role": "assistant", "content": transcript})) return + for message in await self.send_text_message(transcript): + await self.output_queue.put(AdditionalOutputs(message)) + async def emit(self) -> Tuple[int, NDArray[np.int16]] | AdditionalOutputs | None: """Emit audio frame to be played by the speaker.""" # sends to the stream the stuff put in the output queue by the openai event handler @@ -1027,6 +1100,10 @@ async def shutdown(self) -> None: # Stop background tool manager tasks (listener + cleanup) await self.tool_manager.shutdown() + if self._riva_transcriber is not None: + await self._riva_transcriber.stop() + self._riva_transcriber = None + # Cancel any pending debounce task if self.partial_transcript_task and not self.partial_transcript_task.done(): self.partial_transcript_task.cancel() diff --git a/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/riva_asr.py b/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/riva_asr.py new file mode 100644 index 00000000..efc7b814 --- /dev/null +++ b/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/riva_asr.py @@ -0,0 +1,202 @@ +"""Riva streaming ASR bridge used by microphone-to-text mode.""" + +from __future__ import annotations +import os +import queue +import asyncio +import logging +import threading +from dataclasses import dataclass +from collections.abc import Callable, Awaitable + + +logger = logging.getLogger(__name__) + + +@dataclass(frozen=True) +class RivaAsrConfig: + """Configuration for Riva streaming ASR.""" + + server_uri: str + language_code: str + model: str + use_ssl: bool + ssl_cert: str | None + authorization: str | None + metadata: tuple[tuple[str, str], ...] + interim_results: bool + automatic_punctuation: bool + + @classmethod + def from_env(cls) -> "RivaAsrConfig": + """Build Riva ASR configuration from environment variables.""" + return cls( + server_uri=os.getenv("RIVA_SERVER_URI", "localhost:50051"), + language_code=os.getenv("RIVA_LANGUAGE_CODE", "en-US"), + model=os.getenv("RIVA_ASR_MODEL", ""), + use_ssl=_env_flag("RIVA_USE_SSL", default=False), + ssl_cert=os.getenv("RIVA_SSL_CERT") or None, + authorization=os.getenv("RIVA_AUTHORIZATION") or None, + metadata=_parse_metadata(os.getenv("RIVA_METADATA", "")), + interim_results=_env_flag("RIVA_INTERIM_RESULTS", default=True), + automatic_punctuation=_env_flag("RIVA_AUTOMATIC_PUNCTUATION", default=True), + ) + + +class RivaStreamingTranscriber: + """Threaded wrapper around the blocking Riva streaming ASR client.""" + + def __init__( + self, + *, + config: RivaAsrConfig, + on_final_transcript: Callable[[str], Awaitable[None]], + on_partial_transcript: Callable[[str], Awaitable[None]] | None = None, + ) -> None: + """Initialize the streaming transcriber callbacks and audio queue.""" + self._config = config + self._on_final_transcript = on_final_transcript + self._on_partial_transcript = on_partial_transcript + self._audio_queue: queue.Queue[bytes | None] = queue.Queue(maxsize=128) + self._thread: threading.Thread | None = None + self._loop: asyncio.AbstractEventLoop | None = None + self._sample_rate_hertz: int | None = None + self._last_partial = "" + self._last_final = "" + + async def start(self, sample_rate_hertz: int) -> None: + """Start the background Riva stream.""" + if self._thread is not None and self._thread.is_alive(): + return + + self._loop = asyncio.get_running_loop() + self._sample_rate_hertz = sample_rate_hertz + self._thread = threading.Thread(target=self._run, name="riva-asr-stream", daemon=True) + self._thread.start() + + async def send_audio(self, audio_bytes: bytes) -> None: + """Send one PCM16 audio chunk to the Riva stream.""" + if self._thread is None or not self._thread.is_alive(): + raise RuntimeError("Riva ASR stream is not running") + + try: + self._audio_queue.put_nowait(audio_bytes) + except queue.Full: + try: + self._audio_queue.get_nowait() + except queue.Empty: + pass + self._audio_queue.put_nowait(audio_bytes) + + async def stop(self) -> None: + """Close the stream and wait briefly for the worker to exit.""" + if self._thread is None: + return + self._audio_queue.put(None) + thread = self._thread + await asyncio.to_thread(thread.join, 2.0) + + def _audio_chunks(self) -> object: + while True: + chunk = self._audio_queue.get() + if chunk is None: + return + yield chunk + + def _run(self) -> None: + try: + import riva.client + except ImportError: + self._schedule_final( + "[error] Riva STT mode requires the optional dependency " + "`nvidia-riva-client`. Install it with `uv sync --extra riva`." + ) + return + + if self._loop is None or self._sample_rate_hertz is None: + logger.error("Riva ASR stream started without an event loop or sample rate") + return + + try: + metadata_args = list(self._config.metadata) + if self._config.authorization: + metadata_args.append(("authorization", self._config.authorization)) + + auth = riva.client.Auth( + uri=self._config.server_uri, + use_ssl=self._config.use_ssl, + ssl_cert=self._config.ssl_cert, + metadata_args=metadata_args, + ) + asr_service = riva.client.ASRService(auth) + recognition_config = riva.client.RecognitionConfig( + encoding=riva.client.AudioEncoding.LINEAR_PCM, + sample_rate_hertz=self._sample_rate_hertz, + language_code=self._config.language_code, + max_alternatives=1, + enable_automatic_punctuation=self._config.automatic_punctuation, + audio_channel_count=1, + model=self._config.model, + ) + streaming_config = riva.client.StreamingRecognitionConfig( + config=recognition_config, + interim_results=self._config.interim_results, + ) + + responses = asr_service.streaming_response_generator(self._audio_chunks(), streaming_config) + for response in responses: + for result in getattr(response, "results", []): + transcript = self._result_transcript(result) + if not transcript: + continue + if getattr(result, "is_final", False): + self._schedule_final(transcript) + else: + self._schedule_partial(transcript) + except Exception as exc: + logger.exception("Riva streaming ASR failed") + self._schedule_final(f"[error] Riva streaming ASR failed: {type(exc).__name__}: {exc}") + + def _result_transcript(self, result: object) -> str: + alternatives = getattr(result, "alternatives", []) + if not alternatives: + return "" + transcript = getattr(alternatives[0], "transcript", "") + return transcript.strip() if isinstance(transcript, str) else "" + + def _schedule_partial(self, transcript: str) -> None: + if transcript == self._last_partial: + return + self._last_partial = transcript + if self._loop is None or self._on_partial_transcript is None: + return + asyncio.run_coroutine_threadsafe(self._on_partial_transcript(transcript), self._loop) + + def _schedule_final(self, transcript: str) -> None: + if transcript == self._last_final: + return + self._last_final = transcript + if self._loop is None: + return + asyncio.run_coroutine_threadsafe(self._on_final_transcript(transcript), self._loop) + + +def _env_flag(name: str, default: bool = False) -> bool: + raw = os.getenv(name) + if raw is None: + return default + return raw.strip().lower() in {"1", "true", "yes", "on"} + + +def _parse_metadata(raw: str) -> tuple[tuple[str, str], ...]: + pairs: list[tuple[str, str]] = [] + for item in raw.split(","): + item = item.strip() + if not item: + continue + key, separator, value = item.partition("=") + if not separator or not key.strip(): + logger.warning("Ignoring invalid RIVA_METADATA item %r; expected key=value", item) + continue + pairs.append((key.strip(), value.strip())) + return tuple(pairs) diff --git a/projects/reachy-mini-openshell/tests/test_openai_realtime.py b/projects/reachy-mini-openshell/tests/test_openai_realtime.py index 93182722..06a5e5e3 100644 --- a/projects/reachy-mini-openshell/tests/test_openai_realtime.py +++ b/projects/reachy-mini-openshell/tests/test_openai_realtime.py @@ -338,10 +338,80 @@ def fail_openai_client(**_kw: Any) -> None: output = await asyncio.wait_for(handler.output_queue.get(), timeout=1) assert isinstance(output, rt_mod.AdditionalOutputs) - assert "Microphone mode requires an OpenAI-compatible Realtime model" in output.args[0]["content"] + assert "OpenAI Realtime microphone mode requires an OpenAI-compatible Realtime model" in output.args[0]["content"] assert handler.connection is None +@pytest.mark.asyncio +async def test_receive_riva_mode_routes_final_transcript_to_text_llm(monkeypatch: Any) -> None: + """Riva STT mode should send final ASR transcripts through the text LLM path.""" + sent_text_messages: list[str] = [] + + class FakeRivaTranscriber: + instances: list["FakeRivaTranscriber"] = [] + + def __init__(self, **kwargs: Any) -> None: + self.on_final_transcript = kwargs["on_final_transcript"] + self.on_partial_transcript = kwargs["on_partial_transcript"] + self.started_sample_rate: int | None = None + self.audio_chunks: list[bytes] = [] + self.stopped = False + self.instances.append(self) + + async def start(self, sample_rate_hertz: int) -> None: + self.started_sample_rate = sample_rate_hertz + + async def send_audio(self, audio_bytes: bytes) -> None: + self.audio_chunks.append(audio_bytes) + await self.on_partial_transcript("hello") + await self.on_final_transcript("hello reachy") + + async def stop(self) -> None: + self.stopped = True + + monkeypatch.setattr(rt_mod, "RivaStreamingTranscriber", FakeRivaTranscriber) + + deps = ToolDependencies(reachy_mini=MagicMock(), movement_manager=MagicMock()) + handler = rt_mod.OpenaiRealtimeHandler(deps, audio_input_mode=rt_mod.AUDIO_MODE_RIVA_STT) + + async def fake_send_text_message(message: str) -> list[dict[str, Any]]: + sent_text_messages.append(message) + return [ + {"role": "user", "content": message}, + {"role": "assistant", "content": "Hi from the text model."}, + ] + + handler.send_text_message = fake_send_text_message # type: ignore[method-assign] + audio_frame = np.array([0, 1000, -1000, 0], dtype=np.int16) + + await handler.receive((16000, audio_frame)) + + partial = await asyncio.wait_for(handler.output_queue.get(), timeout=1) + user = await asyncio.wait_for(handler.output_queue.get(), timeout=1) + assistant = await asyncio.wait_for(handler.output_queue.get(), timeout=1) + await handler.shutdown() + + transcriber = FakeRivaTranscriber.instances[0] + assert transcriber.started_sample_rate == 16000 + assert transcriber.audio_chunks == [audio_frame.tobytes()] + assert transcriber.stopped + assert sent_text_messages == ["hello reachy"] + assert partial.args[0] == {"role": "user_partial", "content": "hello"} + assert user.args[0] == {"role": "user", "content": "hello reachy"} + assert assistant.args[0] == {"role": "assistant", "content": "Hi from the text model."} + + +def test_handler_copies_share_audio_input_mode() -> None: + """FastRTC handler copies should see the latest UI-selected audio mode.""" + deps = ToolDependencies(reachy_mini=MagicMock(), movement_manager=MagicMock()) + handler = rt_mod.OpenaiRealtimeHandler(deps, audio_input_mode=rt_mod.AUDIO_MODE_OPENAI_REALTIME) + copied_handler = handler.copy() + + handler.set_audio_input_mode(rt_mod.AUDIO_MODE_RIVA_STT) + + assert copied_handler.audio_input_mode == rt_mod.AUDIO_MODE_RIVA_STT + + @pytest.mark.asyncio async def test_send_text_message_reports_missing_dotenv_key(monkeypatch: Any) -> None: """Text mode reports the actual missing-key problem instead of a generic connection error.""" diff --git a/projects/reachy-mini-openshell/uv.lock b/projects/reachy-mini-openshell/uv.lock index a3dcec23..b4ec368f 100644 --- a/projects/reachy-mini-openshell/uv.lock +++ b/projects/reachy-mini-openshell/uv.lock @@ -9,6 +9,13 @@ resolution-markers = [ supported-markers = [ "sys_platform == 'darwin'", ] +conflicts = [[ + { package = "reachy-mini-conversation-app", extra = "mediapipe-vision" }, + { package = "reachy-mini-conversation-app", extra = "riva" }, +], [ + { package = "reachy-mini-conversation-app", extra = "all-vision" }, + { package = "reachy-mini-conversation-app", extra = "riva" }, +]] [[package]] name = "absl-py" @@ -42,15 +49,15 @@ name = "aiohttp" version = "3.14.1" source = { registry = "https://pypi.org/simple" } dependencies = [ - { name = "aiohappyeyeballs", marker = "sys_platform == 'darwin'" }, - { name = "aiosignal", marker = "sys_platform == 'darwin'" }, - { name = "async-timeout", marker = "python_full_version < '3.11' and sys_platform == 'darwin'" }, - { name = "attrs", marker = "sys_platform == 'darwin'" }, - { name = "frozenlist", marker = "sys_platform 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marker = "sys_platform == 'darwin'" }, - { name = "ifaddr", marker = "sys_platform == 'darwin'" }, + { name = "dnspython", marker = "sys_platform == 'darwin' or (extra == 'extra-28-reachy-mini-conversation-app-all-vision' and extra == 'extra-28-reachy-mini-conversation-app-riva') or (extra == 'extra-28-reachy-mini-conversation-app-mediapipe-vision' and extra == 'extra-28-reachy-mini-conversation-app-riva')" }, + { name = "ifaddr", marker = "sys_platform == 'darwin' or (extra == 'extra-28-reachy-mini-conversation-app-all-vision' and extra == 'extra-28-reachy-mini-conversation-app-riva') or (extra == 'extra-28-reachy-mini-conversation-app-mediapipe-vision' and extra == 'extra-28-reachy-mini-conversation-app-riva')" }, ] sdist = { url = "https://files.pythonhosted.org/packages/67/04/df7286233f468e19e9bedff023b6b246182f0b2ccb04ceeb69b2994021c6/aioice-0.10.2.tar.gz", hash = "sha256:bf236c6829ee33c8e540535d31cd5a066b531cb56de2be94c46be76d68b1a806", size = 44307, upload-time = 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or (sys_platform != 'darwin' and extra == 'extra-28-reachy-mini-conversation-app-mediapipe-vision' and extra == 'extra-28-reachy-mini-conversation-app-riva')" }, + { name = "scipy", version = "1.18.0", source = { registry = "https://pypi.org/simple" }, marker = "(python_full_version >= '3.12' and sys_platform == 'darwin') or (python_full_version < '3.12' and extra == 'extra-28-reachy-mini-conversation-app-all-vision' and extra == 'extra-28-reachy-mini-conversation-app-riva') or (python_full_version < '3.12' and extra == 'extra-28-reachy-mini-conversation-app-mediapipe-vision' and extra == 'extra-28-reachy-mini-conversation-app-riva') or (sys_platform != 'darwin' and extra == 'extra-28-reachy-mini-conversation-app-all-vision' and extra == 'extra-28-reachy-mini-conversation-app-riva') or (sys_platform != 'darwin' and extra == 'extra-28-reachy-mini-conversation-app-mediapipe-vision' and extra == 'extra-28-reachy-mini-conversation-app-riva')" }, + { name = "starlette", marker = 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"https://files.pythonhosted.org/packages/f9/20/a82cc900cef998cd8e9eff8bf6bf5a642e841b7daee12d74e184842a0d7d/reachy_mini-1.8.0.tar.gz", hash = "sha256:9c587f2386f1e11fe2f1fbfbcbffd191ee8dcf5cb1cd5fcd7621c2ab416a0dce", size = 24763681, upload-time = "2026-06-01T08:54:13.244Z" } wheels = [ @@ -2084,7 +2155,7 @@ wheels = [ [package.optional-dependencies] mujoco = [ - { name = "mujoco", marker = "sys_platform == 'darwin'" }, + { name = "mujoco", marker = "sys_platform == 'darwin' or (extra == 'extra-28-reachy-mini-conversation-app-all-vision' and extra == 'extra-28-reachy-mini-conversation-app-riva') or (extra == 'extra-28-reachy-mini-conversation-app-mediapipe-vision' and extra == 'extra-28-reachy-mini-conversation-app-riva')" }, ] [[package]] @@ -2092,18 +2163,18 @@ name = "reachy-mini-conversation-app" version = "0.3.0" source = { editable = "." } dependencies = [ - { name = "aiortc", marker = "sys_platform == 'darwin'" }, - { name = "eclipse-zenoh", marker = "sys_platform == 'darwin'" }, - { name = "fastrtc", marker = "sys_platform == 'darwin'" }, - { name = "gradio", marker = "sys_platform == 'darwin'" }, - { name = "gradio-client", marker = "sys_platform == 'darwin'" }, - { name = "huggingface-hub", marker = "sys_platform == 'darwin'" }, - { name = "openai", marker = "sys_platform == 'darwin'" }, - { name = "opencv-python", marker = "sys_platform == 'darwin'" }, - { name = "python-dotenv", marker = "sys_platform == 'darwin'" }, - { name = "reachy-mini", extra = ["mujoco"], marker = "sys_platform == 'darwin'" }, - { name = "reachy-mini-dances-library", marker = "sys_platform == 'darwin'" }, - { name = "reachy-mini-toolbox", marker = "sys_platform == 'darwin'" }, + { name = "aiortc", marker = "sys_platform == 'darwin' or (extra == 'extra-28-reachy-mini-conversation-app-all-vision' and extra == 'extra-28-reachy-mini-conversation-app-riva') or (extra == 'extra-28-reachy-mini-conversation-app-mediapipe-vision' and extra == 'extra-28-reachy-mini-conversation-app-riva')" }, + { name = "eclipse-zenoh", marker = "sys_platform == 'darwin' or (extra == 'extra-28-reachy-mini-conversation-app-all-vision' and extra == 'extra-28-reachy-mini-conversation-app-riva') or (extra == 'extra-28-reachy-mini-conversation-app-mediapipe-vision' and extra == 'extra-28-reachy-mini-conversation-app-riva')" }, + { name = "fastrtc", marker = "sys_platform == 'darwin' or (extra == 'extra-28-reachy-mini-conversation-app-all-vision' and extra == 'extra-28-reachy-mini-conversation-app-riva') or (extra == 'extra-28-reachy-mini-conversation-app-mediapipe-vision' and extra == 'extra-28-reachy-mini-conversation-app-riva')" }, + { name = "gradio", marker = "sys_platform == 'darwin' or (extra == 'extra-28-reachy-mini-conversation-app-all-vision' and extra == 'extra-28-reachy-mini-conversation-app-riva') or (extra == 'extra-28-reachy-mini-conversation-app-mediapipe-vision' and extra == 'extra-28-reachy-mini-conversation-app-riva')" }, + { name = "gradio-client", marker = "sys_platform == 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'extra-28-reachy-mini-conversation-app-all-vision' and extra == 'extra-28-reachy-mini-conversation-app-riva') or (extra == 'extra-28-reachy-mini-conversation-app-mediapipe-vision' and extra == 'extra-28-reachy-mini-conversation-app-riva')" }, + { name = "reachy-mini-toolbox", marker = "sys_platform == 'darwin' or (extra == 'extra-28-reachy-mini-conversation-app-all-vision' and extra == 'extra-28-reachy-mini-conversation-app-riva') or (extra == 'extra-28-reachy-mini-conversation-app-mediapipe-vision' and extra == 'extra-28-reachy-mini-conversation-app-riva')" }, ] [package.optional-dependencies] @@ -2116,27 +2187,30 @@ all-vision = [ { name = "ultralytics", marker = "sys_platform == 'darwin'" }, ] local-vision = [ - { name = "num2words", marker = "sys_platform == 'darwin'" }, - { name = "torch", marker = "sys_platform == 'darwin'" }, - { name = "transformers", marker = "sys_platform == 'darwin'" }, + { name = "num2words", marker = "sys_platform == 'darwin' or (extra == 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marker = "sys_platform == 'darwin'" }, +] yolo-vision = [ - { name = "supervision", marker = "sys_platform == 'darwin'" }, - { name = "ultralytics", marker = "sys_platform == 'darwin'" }, + { name = "supervision", marker = "sys_platform == 'darwin' or (extra == 'extra-28-reachy-mini-conversation-app-all-vision' and extra == 'extra-28-reachy-mini-conversation-app-riva') or (extra == 'extra-28-reachy-mini-conversation-app-mediapipe-vision' and extra == 'extra-28-reachy-mini-conversation-app-riva')" }, + { name = "ultralytics", marker = "sys_platform == 'darwin' or (extra == 'extra-28-reachy-mini-conversation-app-all-vision' and extra == 'extra-28-reachy-mini-conversation-app-riva') or (extra == 'extra-28-reachy-mini-conversation-app-mediapipe-vision' and extra == 'extra-28-reachy-mini-conversation-app-riva')" }, ] [package.dev-dependencies] dev = [ - { name = "pre-commit", marker = "sys_platform == 'darwin'" }, - { name = "pytest", marker = "sys_platform == 'darwin'" }, - { name = "pytest-asyncio", marker = "sys_platform == 'darwin'" }, - { name = "python-semantic-release", marker = "sys_platform == 'darwin'" }, - { name = "ruff", marker = "sys_platform == 'darwin'" }, - { name = "ty", marker = "sys_platform == 'darwin'" }, - { name = "types-requests", marker = "sys_platform == 'darwin'" }, + { name = "pre-commit", marker = "sys_platform == 'darwin' or (extra == 'extra-28-reachy-mini-conversation-app-all-vision' and extra == 'extra-28-reachy-mini-conversation-app-riva') or (extra == 'extra-28-reachy-mini-conversation-app-mediapipe-vision' and extra == 'extra-28-reachy-mini-conversation-app-riva')" }, + { name = "pytest", marker = "sys_platform == 'darwin' or (extra == 'extra-28-reachy-mini-conversation-app-all-vision' and extra == 'extra-28-reachy-mini-conversation-app-riva') or (extra == 'extra-28-reachy-mini-conversation-app-mediapipe-vision' and extra == 'extra-28-reachy-mini-conversation-app-riva')" }, + { name = "pytest-asyncio", marker = "sys_platform == 'darwin' or (extra == 'extra-28-reachy-mini-conversation-app-all-vision' and extra == 'extra-28-reachy-mini-conversation-app-riva') or (extra == 'extra-28-reachy-mini-conversation-app-mediapipe-vision' and extra == 'extra-28-reachy-mini-conversation-app-riva')" }, + { name = "python-semantic-release", marker = "sys_platform == 'darwin' or (extra == 'extra-28-reachy-mini-conversation-app-all-vision' and extra == 'extra-28-reachy-mini-conversation-app-riva') or (extra == 'extra-28-reachy-mini-conversation-app-mediapipe-vision' and extra == 'extra-28-reachy-mini-conversation-app-riva')" }, + { name = "ruff", marker = "sys_platform == 'darwin' or (extra == 'extra-28-reachy-mini-conversation-app-all-vision' and extra == 'extra-28-reachy-mini-conversation-app-riva') or (extra == 'extra-28-reachy-mini-conversation-app-mediapipe-vision' and extra == 'extra-28-reachy-mini-conversation-app-riva')" }, + { name = "ty", marker = "sys_platform == 'darwin' or (extra == 'extra-28-reachy-mini-conversation-app-all-vision' and extra == 'extra-28-reachy-mini-conversation-app-riva') or (extra == 'extra-28-reachy-mini-conversation-app-mediapipe-vision' and extra == 'extra-28-reachy-mini-conversation-app-riva')" }, + { name = "types-requests", marker = "sys_platform == 'darwin' or (extra == 'extra-28-reachy-mini-conversation-app-all-vision' and extra == 'extra-28-reachy-mini-conversation-app-riva') or (extra == 'extra-28-reachy-mini-conversation-app-mediapipe-vision' and extra == 'extra-28-reachy-mini-conversation-app-riva')" }, ] [package.metadata] @@ -2151,6 +2225,7 @@ requires-dist = [ { name = "mediapipe", marker = "extra == 'mediapipe-vision'", specifier = "==0.10.14" }, { name = "num2words", marker = "extra == 'all-vision'" }, { name = "num2words", marker = "extra == 'local-vision'" }, + { name = "nvidia-riva-client", marker = "extra == 'riva'", specifier = ">=2.19,<3" }, { name = "openai", specifier = ">=2.1" }, { name = "opencv-python", specifier = ">=4.12.0.88" }, { name = "python-dotenv" }, @@ -2166,7 +2241,7 @@ requires-dist = [ { name = "ultralytics", marker = "extra == 'all-vision'" }, { name = "ultralytics", marker = "extra == 'yolo-vision'" }, ] -provides-extras = ["local-vision", "yolo-vision", "mediapipe-vision", "all-vision"] +provides-extras = ["riva", "local-vision", "yolo-vision", "mediapipe-vision", "all-vision"] [package.metadata.requires-dev] dev = [ @@ -2184,7 +2259,7 @@ name = "reachy-mini-dances-library" version = "0.2.1" source = { registry = "https://pypi.org/simple" } dependencies = [ - { name = "reachy-mini", marker = "sys_platform == 'darwin'" }, + { name = "reachy-mini", marker = "sys_platform == 'darwin' or (extra == 'extra-28-reachy-mini-conversation-app-all-vision' and extra == 'extra-28-reachy-mini-conversation-app-riva') or (extra == 'extra-28-reachy-mini-conversation-app-mediapipe-vision' and extra == 'extra-28-reachy-mini-conversation-app-riva')" }, ] sdist = { url = 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projects/reachy-mini-openshell/.env.example | 1 + projects/reachy-mini-openshell/README.md | 7 ++-- .../reachy_mini_conversation_app/riva_asr.py | 22 ++++++++++-- .../tests/test_riva_asr.py | 34 +++++++++++++++++++ 4 files changed, 60 insertions(+), 4 deletions(-) create mode 100644 projects/reachy-mini-openshell/tests/test_riva_asr.py diff --git a/projects/reachy-mini-openshell/.env.example b/projects/reachy-mini-openshell/.env.example index 2a82e724..be0b39a3 100644 --- a/projects/reachy-mini-openshell/.env.example +++ b/projects/reachy-mini-openshell/.env.example @@ -8,6 +8,7 @@ MODEL_NAME=azure/anthropic/claude-opus-4-8 AUDIO_INPUT_MODE=openai_realtime # Used only when AUDIO_INPUT_MODE=riva_stt. +# Accepts either host:port or http(s)://host:port. RIVA_SERVER_URI=localhost:50051 RIVA_USE_SSL=false RIVA_LANGUAGE_CODE=en-US diff --git a/projects/reachy-mini-openshell/README.md b/projects/reachy-mini-openshell/README.md index 9470fe58..5102b8d3 100644 --- a/projects/reachy-mini-openshell/README.md +++ b/projects/reachy-mini-openshell/README.md @@ -160,8 +160,11 @@ Realtime path; other model IDs use Chat Completions for text input. template default, where audio goes to an OpenAI-compatible Realtime endpoint. Use `riva_stt` to stream microphone audio to Riva ASR and pass final transcripts into the text LLM path. -- `RIVA_SERVER_URI`: Riva ASR server URI, for example `localhost:50051`. -- `RIVA_USE_SSL`: set to `true` for TLS-enabled Riva endpoints. +- `RIVA_SERVER_URI`: Riva ASR server URI, for example `localhost:50051` or +`http://riva-host:9000`. URL schemes are normalized for the Riva client. +- `RIVA_USE_SSL`: set to `true` for TLS-enabled Riva endpoints. If +`RIVA_SERVER_URI` starts with `https://`, TLS is enabled unless this value is +explicitly set. - `RIVA_LANGUAGE_CODE`: BCP-47 language code for Riva ASR, such as `en-US`. - `RIVA_ASR_MODEL`: optional Riva ASR model name. Leave empty to let Riva select a model from the language/configuration. diff --git a/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/riva_asr.py b/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/riva_asr.py index efc7b814..134ed179 100644 --- a/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/riva_asr.py +++ b/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/riva_asr.py @@ -7,6 +7,7 @@ import logging import threading from dataclasses import dataclass +from urllib.parse import urlparse from collections.abc import Callable, Awaitable @@ -30,11 +31,12 @@ class RivaAsrConfig: @classmethod def from_env(cls) -> "RivaAsrConfig": """Build Riva ASR configuration from environment variables.""" + server_uri, inferred_use_ssl = _normalize_server_uri(os.getenv("RIVA_SERVER_URI", "localhost:50051")) return cls( - server_uri=os.getenv("RIVA_SERVER_URI", "localhost:50051"), + server_uri=server_uri, language_code=os.getenv("RIVA_LANGUAGE_CODE", "en-US"), model=os.getenv("RIVA_ASR_MODEL", ""), - use_ssl=_env_flag("RIVA_USE_SSL", default=False), + use_ssl=_env_flag("RIVA_USE_SSL", default=inferred_use_ssl), ssl_cert=os.getenv("RIVA_SSL_CERT") or None, authorization=os.getenv("RIVA_AUTHORIZATION") or None, metadata=_parse_metadata(os.getenv("RIVA_METADATA", "")), @@ -188,6 +190,22 @@ def _env_flag(name: str, default: bool = False) -> bool: return raw.strip().lower() in {"1", "true", "yes", "on"} +def _normalize_server_uri(raw: str) -> tuple[str, bool]: + value = raw.strip() + if "://" not in value: + return value, False + + parsed = urlparse(value) + if parsed.scheme not in {"http", "https"}: + logger.warning("RIVA_SERVER_URI=%r has an unexpected scheme; passing host/path through", raw) + + server_uri = parsed.netloc or parsed.path + if parsed.path not in {"", "/"} and parsed.netloc: + logger.warning("Ignoring path in RIVA_SERVER_URI=%r; Riva client expects host:port", raw) + + return server_uri, parsed.scheme == "https" + + def _parse_metadata(raw: str) -> tuple[tuple[str, str], ...]: pairs: list[tuple[str, str]] = [] for item in raw.split(","): diff --git a/projects/reachy-mini-openshell/tests/test_riva_asr.py b/projects/reachy-mini-openshell/tests/test_riva_asr.py new file mode 100644 index 00000000..9a28d01b --- /dev/null +++ b/projects/reachy-mini-openshell/tests/test_riva_asr.py @@ -0,0 +1,34 @@ +from reachy_mini_conversation_app.riva_asr import RivaAsrConfig + + +def test_riva_config_accepts_http_endpoint_url(monkeypatch): + """Riva endpoint URLs should be normalized to the host:port form expected by the client.""" + monkeypatch.setenv("RIVA_SERVER_URI", "http://192.168.1.57:9000") + monkeypatch.delenv("RIVA_USE_SSL", raising=False) + + config = RivaAsrConfig.from_env() + + assert config.server_uri == "192.168.1.57:9000" + assert config.use_ssl is False + + +def test_riva_config_infers_ssl_from_https_endpoint_url(monkeypatch): + """HTTPS Riva endpoint URLs should enable TLS unless explicitly overridden.""" + monkeypatch.setenv("RIVA_SERVER_URI", "https://riva.example.test:443") + monkeypatch.delenv("RIVA_USE_SSL", raising=False) + + config = RivaAsrConfig.from_env() + + assert config.server_uri == "riva.example.test:443" + assert config.use_ssl is True + + +def test_riva_use_ssl_env_overrides_endpoint_url_scheme(monkeypatch): + """RIVA_USE_SSL should keep explicit operator configuration authoritative.""" + monkeypatch.setenv("RIVA_SERVER_URI", "https://riva.example.test:443") + monkeypatch.setenv("RIVA_USE_SSL", "false") + + config = RivaAsrConfig.from_env() + + assert config.server_uri == "riva.example.test:443" + assert config.use_ssl is False From 565d15e280c001c31ee3e833a93dc00ffc4c6aa1 Mon Sep 17 00:00:00 2001 From: Johnny Greco Date: Thu, 25 Jun 2026 23:20:55 +0000 Subject: [PATCH 15/45] Address Reachy panel review findings --- .../reachy-mini-conversation-simulator.md | 27 +++-- projects/reachy-mini-openshell/.env.example | 6 +- projects/reachy-mini-openshell/README.md | 21 ++-- projects/reachy-mini-openshell/index.html | 4 +- projects/reachy-mini-openshell/pyproject.toml | 4 +- .../reachy_mini_conversation_app/config.py | 48 +++++++- .../reachy_mini_conversation_app/console.py | 27 ++--- .../src/reachy_mini_conversation_app/main.py | 22 +++- .../openai_realtime.py | 28 ++++- .../reachy_mini_conversation_app/riva_asr.py | 12 +- .../tools/background_tool_manager.py | 13 ++- .../tools/move_head.py | 4 +- .../vision/yolo_head_tracker.py | 14 ++- .../tests/test_openai_realtime.py | 109 +++++++++++++++++- .../tests/test_riva_asr.py | 87 +++++++++++++- .../tools/test_background_tool_manager.py | 31 +++++ projects/reachy-mini-openshell/uv.lock | 48 +++++++- 17 files changed, 432 insertions(+), 73 deletions(-) diff --git a/docs/research/reachy-mini-conversation-simulator.md b/docs/research/reachy-mini-conversation-simulator.md index 6a03c44f..51671e42 100644 --- a/docs/research/reachy-mini-conversation-simulator.md +++ b/docs/research/reachy-mini-conversation-simulator.md @@ -14,9 +14,9 @@ for the broader app family: [pollen-robotics/reachy_mini_conversation_app](https - macOS with Python 3.10, 3.11, or 3.12. Python 3.12 is the recommended local version. - `uv`. -- An API key for conversation. Microphone mode requires an OpenAI-compatible - Realtime model; text mode can also use OpenAI-compatible Chat Completions - providers such as NVIDIA NIM. +- An API key for conversation. `OpenAI Realtime` microphone mode requires an + OpenAI-compatible Realtime model. `Riva STT` and `Text` mode can use + OpenAI-compatible Chat Completions providers such as NVIDIA NIM. - This repository checked out locally. The local dependency set includes `reachy-mini[mujoco]==1.8.0`, so the MuJoCo @@ -40,6 +40,7 @@ Edit `.env`. For OpenAI Realtime microphone and text input, use: OPENAI_API_KEY=your_api_key_here OPENAI_BASE_URL=https://api.openai.com/v1 MODEL_NAME=gpt-realtime +AUDIO_INPUT_MODE=openai_realtime ``` For NVIDIA-hosted text input through an OpenAI-compatible Chat Completions @@ -49,6 +50,7 @@ endpoint, reference your existing NVIDIA API key environment variable: OPENAI_API_KEY=${NVIDIA_API_KEY} OPENAI_BASE_URL=https://inference-api.nvidia.com/v1 MODEL_NAME=azure/anthropic/claude-opus-4-8 +AUDIO_INPUT_MODE=text ``` Use the exact model ID exposed by your provider. For example, NVIDIA model IDs @@ -170,9 +172,9 @@ http://127.0.0.1:7860/ ``` You should see the `Talk with Reachy Mini` page with an empty chat transcript, -an audio stream panel, and an `Input` selector. - -![Gradio conversation UI for Talk with Reachy Mini](../assets/reachy-mini-openshell/screenshots/gradio-home.png) +an `Input` selector with `OpenAI Realtime`, `Riva STT`, and `Text` options. +`Text` mode shows the message box and send button. The two microphone modes show +the audio stream panel. If the app logs that `OPENAI_API_KEY` is missing, stop the app, update `.env`, and restart it. Credentials are intentionally not entered in the browser. If @@ -181,15 +183,20 @@ exported in the shell that starts the app. ## 6. Talk To Reachy -Use `Microphone` mode to speak when `MODEL_NAME` points to a Realtime-capable +Use `OpenAI Realtime` to speak when `MODEL_NAME` points to a Realtime-capable model. Click `Click to Access Microphone` in the `Stream` panel and allow microphone access in the browser. Once the stream starts, speak naturally. +Use `Riva STT` when you have a Riva ASR endpoint and want speech-to-text before +sending text to a Chat Completions provider. Set `AUDIO_INPUT_MODE=riva_stt`, +configure `RIVA_SERVER_URI`, and install the Riva optional dependencies with +`uv sync --extra riva`. + Use `Text` mode to type instead. Switch `Input` to `Text`, enter a message, and send it from the text composer. For non-Realtime model IDs such as NVIDIA NIM -models, text mode uses Chat Completions. Tool calls are supported in text mode, -including providers that require the tool schema to remain attached after a tool -result is returned. +models, text mode uses Chat Completions. Tool calls are supported in text mode +and in the Riva STT path, including providers that require the tool schema to +remain attached after a tool result is returned. Useful first prompts are: diff --git a/projects/reachy-mini-openshell/.env.example b/projects/reachy-mini-openshell/.env.example index be0b39a3..060850d0 100644 --- a/projects/reachy-mini-openshell/.env.example +++ b/projects/reachy-mini-openshell/.env.example @@ -5,12 +5,14 @@ MODEL_NAME=azure/anthropic/claude-opus-4-8 # Audio input modes: # - openai_realtime: microphone audio goes to an OpenAI-compatible Realtime endpoint. # - riva_stt: microphone audio goes to Riva ASR; final transcripts go to the text LLM path. -AUDIO_INPUT_MODE=openai_realtime +# - text: typed input goes to the text LLM path. +AUDIO_INPUT_MODE=text # Used only when AUDIO_INPUT_MODE=riva_stt. # Accepts either host:port or http(s)://host:port. RIVA_SERVER_URI=localhost:50051 -RIVA_USE_SSL=false +# Optional override. Leave unset to infer TLS from an https:// RIVA_SERVER_URI. +# RIVA_USE_SSL=false RIVA_LANGUAGE_CODE=en-US RIVA_ASR_MODEL= RIVA_AUTHORIZATION= diff --git a/projects/reachy-mini-openshell/README.md b/projects/reachy-mini-openshell/README.md index 5102b8d3..0e220dc5 100644 --- a/projects/reachy-mini-openshell/README.md +++ b/projects/reachy-mini-openshell/README.md @@ -77,6 +77,7 @@ Then edit `.env`. For OpenAI Realtime microphone and text input, use: OPENAI_API_KEY=your_api_key_here OPENAI_BASE_URL=https://api.openai.com/v1 MODEL_NAME=gpt-realtime +AUDIO_INPUT_MODE=openai_realtime ``` For NVIDIA-hosted text input through an OpenAI-compatible Chat Completions @@ -86,6 +87,7 @@ endpoint, reference your existing NVIDIA API key environment variable: OPENAI_API_KEY=${NVIDIA_API_KEY} OPENAI_BASE_URL=https://inference-api.nvidia.com/v1 MODEL_NAME=azure/anthropic/claude-opus-4-8 +AUDIO_INPUT_MODE=text ``` Use the exact model ID exposed by your provider. For example, NVIDIA model IDs @@ -156,15 +158,14 @@ reference another exported environment variable, such as - `OPENAI_BASE_URL`: OpenAI-compatible API base URL. - `MODEL_NAME`: provider model ID. Model names containing `realtime` use the Realtime path; other model IDs use Chat Completions for text input. -- `AUDIO_INPUT_MODE`: microphone routing mode. Use `openai_realtime` for the -template default, where audio goes to an OpenAI-compatible Realtime endpoint. -Use `riva_stt` to stream microphone audio to Riva ASR and pass final -transcripts into the text LLM path. +- `AUDIO_INPUT_MODE`: initial input mode. Use `text` for the default typed +message path, `openai_realtime` when microphone audio should go to an +OpenAI-compatible Realtime endpoint, or `riva_stt` to stream microphone audio +to Riva ASR and pass final transcripts into the text LLM path. - `RIVA_SERVER_URI`: Riva ASR server URI, for example `localhost:50051` or `http://riva-host:9000`. URL schemes are normalized for the Riva client. -- `RIVA_USE_SSL`: set to `true` for TLS-enabled Riva endpoints. If -`RIVA_SERVER_URI` starts with `https://`, TLS is enabled unless this value is -explicitly set. +- `RIVA_USE_SSL`: optional override for TLS-enabled Riva endpoints. If this is +unset and `RIVA_SERVER_URI` starts with `https://`, TLS is enabled. - `RIVA_LANGUAGE_CODE`: BCP-47 language code for Riva ASR, such as `en-US`. - `RIVA_ASR_MODEL`: optional Riva ASR model name. Leave empty to let Riva select a model from the language/configuration. @@ -193,11 +194,11 @@ http://127.0.0.1:7860/ ``` If port `7860` is busy, the launcher chooses the next free port through `7899` -and prints that URL instead. Pass app flags after the script name: +and prints that URL instead. Pass app flags that are compatible with the +no-camera simulator baseline after the script name: ```bash projects/reachy-mini-openshell/scripts/start-local.sh --debug -projects/reachy-mini-openshell/scripts/start-local.sh --head-tracker yolo ``` From inside `projects/reachy-mini-openshell`, the shorter form is: @@ -221,7 +222,7 @@ python -m reachy_mini_conversation_app --gradio --no-camera The Gradio UI includes an `Input` selector: -- `OpenAI Realtime`: template-default microphone behavior. Audio streams to an +- `OpenAI Realtime`: Realtime microphone behavior. Audio streams to an OpenAI-compatible Realtime endpoint, which handles transcription and response generation in one session. - `Riva STT`: microphone audio streams to Riva ASR. Final transcripts are sent diff --git a/projects/reachy-mini-openshell/index.html b/projects/reachy-mini-openshell/index.html index d241f1fc..752400d6 100644 --- a/projects/reachy-mini-openshell/index.html +++ b/projects/reachy-mini-openshell/index.html @@ -32,10 +32,10 @@

    Installation

    Configuration

    -

    OpenAI API Key

    +

    Provider Configuration

    -

    This app requires an OpenAI API key for voice conversations. Set it via the web interface or environment variable.

    +

    Configure provider credentials, model routing, and input mode in .env, then run ./scripts/start-local.sh.

    diff --git a/projects/reachy-mini-openshell/pyproject.toml b/projects/reachy-mini-openshell/pyproject.toml index a9a7a66e..6c955849 100644 --- a/projects/reachy-mini-openshell/pyproject.toml +++ b/projects/reachy-mini-openshell/pyproject.toml @@ -42,9 +42,9 @@ conflicts = [ [project.optional-dependencies] riva = [ "nvidia-riva-client>=2.19,<3",] local_vision = [ "torch>=2.1", "transformers==5.0.0rc2", "num2words",] -yolo_vision = [ "ultralytics", "supervision",] +yolo_vision = [ "ultralytics", "supervision", "onnxruntime",] mediapipe_vision = [ "mediapipe==0.10.14",] -all_vision = [ "torch>=2.1", "transformers==5.0.0rc2", "num2words", "ultralytics", "supervision", "mediapipe==0.10.14",] +all_vision = [ "torch>=2.1", "transformers==5.0.0rc2", "num2words", "ultralytics", "supervision", "onnxruntime", "mediapipe==0.10.14",] [project.scripts] reachy-mini-conversation-app = "reachy_mini_conversation_app.main:main" diff --git a/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/config.py b/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/config.py index bb04df19..115fcdae 100644 --- a/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/config.py +++ b/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/config.py @@ -2,6 +2,7 @@ import sys import logging from pathlib import Path +from collections.abc import Mapping from dotenv import find_dotenv, load_dotenv, dotenv_values @@ -57,15 +58,34 @@ def _env_flag(name: str, default: bool = False) -> bool: logger.warning("No .env file found") -def _dotenv_value(name: str, default: str | None = None) -> str | None: +def _dotenv_value( + name: str, + default: str | None = None, + *, + values: Mapping[str, str | None] | None = None, +) -> str | None: """Return a value from the loaded .env file only.""" - value = _dotenv_values.get(name) + source = _dotenv_values if values is None else values + value = source.get(name) if value is None: return default value = value.strip() return value if value else default +def _config_value( + name: str, + default: str | None = None, + *, + values: Mapping[str, str | None] | None = None, +) -> str | None: + """Return .env value first, then the process environment.""" + value = _dotenv_value(name, values=values) + if value is not None: + return value + return os.getenv(name, default) + + class Config: """Configuration class for the conversation app.""" @@ -91,5 +111,29 @@ def __init__(self) -> None: """Initialize the configuration.""" logger.info("Using locked profile '%s' from %s", LOCKED_PROFILE, DEFAULT_PROFILES_DIRECTORY) + def apply_dotenv_values(self, values: Mapping[str, str | None]) -> None: + """Refresh runtime configuration from an explicit dotenv mapping.""" + self.OPENAI_API_KEY = _dotenv_value("OPENAI_API_KEY", values=values) + self.OPENAI_BASE_URL = _dotenv_value("OPENAI_BASE_URL", "https://api.openai.com/v1", values=values) + self.MODEL_NAME = _config_value("MODEL_NAME", "gpt-realtime", values=values) or "gpt-realtime" + self.AUDIO_INPUT_MODE = _config_value("AUDIO_INPUT_MODE", "openai_realtime", values=values) or "openai_realtime" + self.HF_HOME = _config_value("HF_HOME", "./cache", values=values) or "./cache" + self.LOCAL_VISION_MODEL = ( + _config_value("LOCAL_VISION_MODEL", "HuggingFaceTB/SmolVLM2-2.2B-Instruct", values=values) + or "HuggingFaceTB/SmolVLM2-2.2B-Instruct" + ) + self.HF_TOKEN = _config_value("HF_TOKEN", values=values) + + def load_dotenv_file(self, env_path: Path) -> bool: + """Load a dotenv file and refresh all runtime config fields.""" + if not env_path.exists(): + return False + + values = dict(dotenv_values(env_path)) + load_dotenv(dotenv_path=env_path, override=True) + self.apply_dotenv_values(values) + logger.info("Configuration loaded from %s", env_path) + return True + config = Config() diff --git a/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/console.py b/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/console.py index ff284fca..6f3ff17f 100644 --- a/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/console.py +++ b/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/console.py @@ -55,17 +55,9 @@ def launch(self) -> None: # Try to load an existing instance .env first for Reachy Mini app-shell runs. if self._instance_path: try: - from dotenv import load_dotenv, dotenv_values - env_path = Path(self._instance_path) / ".env" - if env_path.exists(): - load_dotenv(dotenv_path=str(env_path), override=True) - values = dotenv_values(env_path) - config.OPENAI_API_KEY = (values.get("OPENAI_API_KEY") or "").strip() or None - config.OPENAI_BASE_URL = ( - (values.get("OPENAI_BASE_URL") or "").strip() - or "https://api.openai.com/v1" - ) + if config.load_dotenv_file(env_path): + self.handler.set_audio_input_mode(config.AUDIO_INPUT_MODE) except Exception: pass # Instance .env loading is optional; continue with defaults @@ -117,13 +109,16 @@ def close(self) -> None: except Exception as e: logger.debug(f"Error stopping playback (may already be stopped): {e}") - # Now signal async loops to stop - self._stop_event.set() + def stop_async_tasks() -> None: + self._stop_event.set() + for task in self._tasks: + if not task.done(): + task.cancel() - # Cancel all running tasks - for task in self._tasks: - if not task.done(): - task.cancel() + if self._asyncio_loop is not None and self._asyncio_loop.is_running(): + self._asyncio_loop.call_soon_threadsafe(stop_async_tasks) + else: + stop_async_tasks() def clear_audio_queue(self) -> None: """Flush the player's appsrc to drop any queued audio immediately.""" diff --git a/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/main.py b/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/main.py index 3382e089..5aeddf94 100644 --- a/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/main.py +++ b/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/main.py @@ -7,6 +7,7 @@ import argparse import threading from typing import Any, Dict, List, Optional +from pathlib import Path from reachy_mini import ReachyMini, ReachyMiniApp from reachy_mini_conversation_app.utils import ( @@ -52,6 +53,7 @@ def run( from reachy_mini_conversation_app.config import config from reachy_mini_conversation_app.console import LocalStream from reachy_mini_conversation_app.openai_realtime import ( + AUDIO_MODE_TEXT, AUDIO_MODE_RIVA_STT, AUDIO_MODE_OPENAI_REALTIME, OpenaiRealtimeHandler, @@ -62,6 +64,12 @@ def run( logger = setup_logger(args.debug) logger.info("Starting Reachy Mini Conversation App") + if instance_path: + try: + config.load_dotenv_file(Path(instance_path) / ".env") + except Exception as exc: + logger.debug("Instance .env loading skipped: %s", exc) + if args.no_camera and args.head_tracker is not None: logger.warning( "Head tracking disabled: --no-camera flag is set. " @@ -165,9 +173,12 @@ def run( input_mode_choices = { "OpenAI Realtime": AUDIO_MODE_OPENAI_REALTIME, "Riva STT": AUDIO_MODE_RIVA_STT, - "Text": "text", + "Text": AUDIO_MODE_TEXT, } - initial_input_mode = "Riva STT" if handler.audio_input_mode == AUDIO_MODE_RIVA_STT else "OpenAI Realtime" + mode_labels = {value: label for label, value in input_mode_choices.items()} + initial_input_mode = mode_labels.get(handler.audio_input_mode, "OpenAI Realtime") + initial_text_mode = initial_input_mode == "Text" + stream.webrtc_component.visible = not initial_text_mode input_mode = gr.Radio( choices=list(input_mode_choices), @@ -179,14 +190,13 @@ def run( label="Message", lines=2, max_lines=5, - visible=False, + visible=initial_text_mode, ) - send_button = gr.Button("Send", variant="primary", visible=False) + send_button = gr.Button("Send", variant="primary", visible=initial_text_mode) def switch_input_mode(mode: str) -> tuple[dict[str, Any], dict[str, Any], dict[str, Any]]: text_mode = mode == "Text" - if not text_mode: - handler.set_audio_input_mode(input_mode_choices.get(mode, config.AUDIO_INPUT_MODE)) + handler.set_audio_input_mode(input_mode_choices.get(mode, config.AUDIO_INPUT_MODE)) return ( gr.update(visible=not text_mode), gr.update(visible=text_mode), diff --git a/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/openai_realtime.py b/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/openai_realtime.py index ad173807..b0ef9cfa 100644 --- a/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/openai_realtime.py +++ b/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/openai_realtime.py @@ -37,7 +37,8 @@ OPEN_AI_OUTPUT_SAMPLE_RATE: Final[Literal[24000]] = 24000 AUDIO_MODE_OPENAI_REALTIME: Final = "openai_realtime" AUDIO_MODE_RIVA_STT: Final = "riva_stt" -AUDIO_INPUT_MODES: Final = {AUDIO_MODE_OPENAI_REALTIME, AUDIO_MODE_RIVA_STT} +AUDIO_MODE_TEXT: Final = "text" +AUDIO_INPUT_MODES: Final = {AUDIO_MODE_OPENAI_REALTIME, AUDIO_MODE_RIVA_STT, AUDIO_MODE_TEXT} # Cost tracking from usage data (pricing as of Feb 2026 https://openai.com/api/pricing/) AUDIO_INPUT_COST_PER_1M = 32.0 @@ -56,6 +57,8 @@ def _normalize_audio_input_mode(audio_input_mode: str) -> str: return AUDIO_MODE_OPENAI_REALTIME if normalized in {"riva", "riva_asr", "riva_stt"}: return AUDIO_MODE_RIVA_STT + if normalized in {"chat", "chat_completions", "text"}: + return AUDIO_MODE_TEXT if normalized not in AUDIO_INPUT_MODES: logger.warning("Unknown AUDIO_INPUT_MODE=%r; using %s", audio_input_mode, AUDIO_MODE_OPENAI_REALTIME) return AUDIO_MODE_OPENAI_REALTIME @@ -620,6 +623,11 @@ async def _response_sender_loop(self) -> None: self._last_response_rejected = False try: + # Mark the just-requested response as active immediately. + # The server's response.created event can arrive after + # response.create() returns, so waiting on the old set + # event here would let the next queued response race ahead. + self._response_done_event.clear() await self.connection.response.create(**kwargs) except Exception as e: logger.debug("_response_sender_loop: send failed: %s", e) @@ -993,6 +1001,8 @@ async def receive(self, frame: Tuple[int, NDArray[np.int16]]) -> None: if self.audio_input_mode == AUDIO_MODE_RIVA_STT: await self._receive_riva_stt(frame) return + if self.audio_input_mode == AUDIO_MODE_TEXT: + return await self._receive_openai_realtime_audio(frame) @@ -1036,9 +1046,21 @@ async def _receive_riva_stt(self, frame: Tuple[int, NDArray[np.int16]]) -> None: on_final_transcript=self._handle_riva_final_transcript, on_partial_transcript=self._handle_riva_partial_transcript, ) - await self._riva_transcriber.start(input_sample_rate) + try: + await self._riva_transcriber.start(input_sample_rate) + except RuntimeError as exc: + self._riva_transcriber = None + await self._report_microphone_error_once(f"[error] Riva STT stream is not available: {exc}") + return - await self._riva_transcriber.send_audio(audio_frame.tobytes()) + try: + if await self._riva_transcriber.send_audio(audio_frame.tobytes()) is False: + self._riva_transcriber = None + await self._report_microphone_error_once("[error] Riva STT stream is not running.") + except RuntimeError as exc: + logger.warning("Riva STT stream stopped: %s", exc) + self._riva_transcriber = None + await self._report_microphone_error_once(f"[error] Riva STT stream is not available: {exc}") def _prepare_audio_frame( self, diff --git a/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/riva_asr.py b/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/riva_asr.py index 134ed179..9913317b 100644 --- a/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/riva_asr.py +++ b/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/riva_asr.py @@ -64,7 +64,6 @@ def __init__( self._loop: asyncio.AbstractEventLoop | None = None self._sample_rate_hertz: int | None = None self._last_partial = "" - self._last_final = "" async def start(self, sample_rate_hertz: int) -> None: """Start the background Riva stream.""" @@ -76,10 +75,11 @@ async def start(self, sample_rate_hertz: int) -> None: self._thread = threading.Thread(target=self._run, name="riva-asr-stream", daemon=True) self._thread.start() - async def send_audio(self, audio_bytes: bytes) -> None: + async def send_audio(self, audio_bytes: bytes) -> bool: """Send one PCM16 audio chunk to the Riva stream.""" if self._thread is None or not self._thread.is_alive(): - raise RuntimeError("Riva ASR stream is not running") + logger.debug("Dropping Riva audio frame because the ASR stream is not running") + return False try: self._audio_queue.put_nowait(audio_bytes) @@ -89,6 +89,7 @@ async def send_audio(self, audio_bytes: bytes) -> None: except queue.Empty: pass self._audio_queue.put_nowait(audio_bytes) + return True async def stop(self) -> None: """Close the stream and wait briefly for the worker to exit.""" @@ -175,9 +176,6 @@ def _schedule_partial(self, transcript: str) -> None: asyncio.run_coroutine_threadsafe(self._on_partial_transcript(transcript), self._loop) def _schedule_final(self, transcript: str) -> None: - if transcript == self._last_final: - return - self._last_final = transcript if self._loop is None: return asyncio.run_coroutine_threadsafe(self._on_final_transcript(transcript), self._loop) @@ -187,6 +185,8 @@ def _env_flag(name: str, default: bool = False) -> bool: raw = os.getenv(name) if raw is None: return default + if not raw.strip(): + return default return raw.strip().lower() in {"1", "true", "yes", "on"} diff --git a/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/tools/background_tool_manager.py b/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/tools/background_tool_manager.py index c7859c81..caa81508 100644 --- a/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/tools/background_tool_manager.py +++ b/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/tools/background_tool_manager.py @@ -205,7 +205,11 @@ async def _run_tool( tool_call_routine: ToolCallRoutine, ) -> None: """Execute the tool and handle completion.""" - result: dict[str, Any] = await tool_call_routine(self) + try: + result: dict[str, Any] = await tool_call_routine(self) + except asyncio.CancelledError: + result = {"error": "Tool cancelled"} + bg_tool.completed_at = time.monotonic() error = result.get("error") @@ -333,9 +337,16 @@ async def shutdown(self) -> None: pass self._lifecycle_tasks.clear() + running_tool_tasks: list[asyncio.Task[None]] = [] for tool_id in list(self._tools): + tool = self._tools.get(tool_id) + if tool is not None and tool.status == ToolState.RUNNING and tool._task is not None: + running_tool_tasks.append(tool._task) await self.cancel_tool(tool_id, log=False) + if running_tool_tasks: + await asyncio.gather(*running_tool_tasks, return_exceptions=True) + logger.info("BackgroundToolManager shut down") async def timeout_tools(self) -> int: diff --git a/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/tools/move_head.py b/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/tools/move_head.py index 4633572e..dbf1f4c1 100644 --- a/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/tools/move_head.py +++ b/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/tools/move_head.py @@ -53,7 +53,7 @@ async def __call__(self, deps: ToolDependencies, **kwargs: Any) -> Dict[str, Any # Get current state for interpolation current_head_pose = deps.reachy_mini.get_current_head_pose() - _, current_antennas = deps.reachy_mini.get_current_joint_positions() + head_joints, current_antennas = deps.reachy_mini.get_current_joint_positions() # Create goto move goto_move = GotoQueueMove( @@ -65,7 +65,7 @@ async def __call__(self, deps: ToolDependencies, **kwargs: Any) -> Dict[str, Any current_antennas[1], ), # Skip body_yaw target_body_yaw=0, # Reset body yaw - start_body_yaw=current_antennas[0], # body_yaw is first in joint positions + start_body_yaw=head_joints[0], duration=deps.motion_duration_s, ) diff --git a/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/vision/yolo_head_tracker.py b/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/vision/yolo_head_tracker.py index 3619bc7e..97ceebfa 100644 --- a/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/vision/yolo_head_tracker.py +++ b/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/vision/yolo_head_tracker.py @@ -18,14 +18,19 @@ logger = logging.getLogger(__name__) +DEFAULT_YOLO_FACE_MODEL_REPO = "AdamCodd/YOLOv11n-face-detection" +DEFAULT_YOLO_FACE_MODEL_REVISION = "0e97fea5eacb1460b35725c929d813c7095841b5" +DEFAULT_YOLO_FACE_MODEL_FILENAME = "model.onnx" + class HeadTracker: """Lightweight head tracker using YOLO for face detection.""" def __init__( self, - model_repo: str = "AdamCodd/YOLOv11n-face-detection", - model_filename: str = "model.pt", + model_repo: str = DEFAULT_YOLO_FACE_MODEL_REPO, + model_filename: str = DEFAULT_YOLO_FACE_MODEL_FILENAME, + model_revision: str = DEFAULT_YOLO_FACE_MODEL_REVISION, confidence_threshold: float = 0.3, device: str = "cpu", ) -> None: @@ -34,6 +39,7 @@ def __init__( Args: model_repo: HuggingFace model repository model_filename: Model file name + model_revision: Pinned Hugging Face commit SHA for the model repository confidence_threshold: Minimum confidence for face detection device: Device to run inference on ('cpu' or 'cuda') @@ -42,9 +48,9 @@ def __init__( try: # Download and load YOLO model - model_path = hf_hub_download(repo_id=model_repo, filename=model_filename) + model_path = hf_hub_download(repo_id=model_repo, filename=model_filename, revision=model_revision) self.model = YOLO(model_path).to(device) - logger.info(f"YOLO face detection model loaded from {model_repo}") + logger.info("YOLO face detection model loaded from %s@%s", model_repo, model_revision) except Exception as e: logger.error(f"Failed to load YOLO model: {e}") raise diff --git a/projects/reachy-mini-openshell/tests/test_openai_realtime.py b/projects/reachy-mini-openshell/tests/test_openai_realtime.py index 06a5e5e3..40bc25cd 100644 --- a/projects/reachy-mini-openshell/tests/test_openai_realtime.py +++ b/projects/reachy-mini-openshell/tests/test_openai_realtime.py @@ -412,6 +412,65 @@ def test_handler_copies_share_audio_input_mode() -> None: assert copied_handler.audio_input_mode == rt_mod.AUDIO_MODE_RIVA_STT +@pytest.mark.asyncio +async def test_receive_text_mode_ignores_microphone_frames() -> None: + """Text input mode should not open an audio connection when WebRTC is hidden.""" + deps = ToolDependencies(reachy_mini=MagicMock(), movement_manager=MagicMock()) + handler = rt_mod.OpenaiRealtimeHandler(deps, audio_input_mode=rt_mod.AUDIO_MODE_TEXT) + + await handler.receive((24000, np.array([0, 1000], dtype=np.int16))) + + assert handler.connection is None + assert handler.output_queue.empty() + + +@pytest.mark.asyncio +async def test_receive_riva_mode_does_not_raise_when_transcriber_stops(monkeypatch: Any) -> None: + """A failed Riva worker should report through callbacks, not escape from receive().""" + + class StoppedRivaTranscriber: + async def start(self, _sample_rate_hertz: int) -> None: + return None + + async def send_audio(self, _audio_bytes: bytes) -> None: + raise RuntimeError("Riva ASR stream is not running") + + monkeypatch.setattr(rt_mod, "RivaStreamingTranscriber", lambda **_kw: StoppedRivaTranscriber()) + + deps = ToolDependencies(reachy_mini=MagicMock(), movement_manager=MagicMock()) + handler = rt_mod.OpenaiRealtimeHandler(deps, audio_input_mode=rt_mod.AUDIO_MODE_RIVA_STT) + + await handler.receive((16000, np.array([0, 1000], dtype=np.int16))) + + output = await asyncio.wait_for(handler.output_queue.get(), timeout=1) + assert isinstance(output, rt_mod.AdditionalOutputs) + assert "Riva STT stream is not available" in output.args[0]["content"] + + +@pytest.mark.asyncio +async def test_receive_riva_mode_resets_dead_transcriber(monkeypatch: Any) -> None: + """Dead Riva streams should be cleared so later frames can restart the stream.""" + + class DeadRivaTranscriber: + async def start(self, _sample_rate_hertz: int) -> None: + return None + + async def send_audio(self, _audio_bytes: bytes) -> bool: + return False + + monkeypatch.setattr(rt_mod, "RivaStreamingTranscriber", lambda **_kw: DeadRivaTranscriber()) + + deps = ToolDependencies(reachy_mini=MagicMock(), movement_manager=MagicMock()) + handler = rt_mod.OpenaiRealtimeHandler(deps, audio_input_mode=rt_mod.AUDIO_MODE_RIVA_STT) + + await handler.receive((16000, np.array([0, 1000], dtype=np.int16))) + + output = await asyncio.wait_for(handler.output_queue.get(), timeout=1) + assert isinstance(output, rt_mod.AdditionalOutputs) + assert output.args[0]["content"] == "[error] Riva STT stream is not running." + assert handler._riva_transcriber is None + + @pytest.mark.asyncio async def test_send_text_message_reports_missing_dotenv_key(monkeypatch: Any) -> None: """Text mode reports the actual missing-key problem instead of a generic connection error.""" @@ -692,7 +751,6 @@ async def test_response_sender_retries_on_active_response_rejection(monkeypatch: event_queue: asyncio.Queue[Any] = asyncio.Queue() response_create_log: list[tuple[int, dict[str, Any]]] = [] - handler_ref: list[Any] = [] # ---- Fake event / error objects mirroring the OpenAI SDK shapes ---- @@ -729,16 +787,15 @@ class FakeResponseAPI: def __init__(self) -> None: self._call_count = 0 self._serialization_violations: list[int] = [] + self._server_active = False async def create(self, **kwargs: Any) -> None: self._call_count += 1 n = self._call_count response_create_log.append((n, kwargs)) - h = handler_ref[0] - # Real backend rejects when a response is already active. - if not h._response_done_event.is_set(): + if self._server_active: self._serialization_violations.append(n) await event_queue.put( FakeEvent( @@ -757,6 +814,7 @@ async def create(self, **kwargs: Any) -> None: await event_queue.put( FakeEvent("response.done", response=MagicMock()) ) + self._server_active = False return # Intentional rejections (simulating a race where another @@ -777,11 +835,13 @@ async def create(self, **kwargs: Any) -> None: ) await asyncio.sleep(0) else: + self._server_active = True await event_queue.put(FakeEvent("response.created")) await event_queue.put( FakeEvent("response.done", response=MagicMock()) ) + self._server_active = False async def cancel(self, **_kw: Any) -> None: @@ -851,7 +911,6 @@ async def _fake_dispatch( deps = ToolDependencies(reachy_mini=MagicMock(), movement_manager=MagicMock()) handler = rt_mod.OpenaiRealtimeHandler(deps) - handler_ref.append(handler) asyncio.create_task(handler.start_up()) @@ -921,6 +980,46 @@ async def _fake_dispatch( # ---- Response creation timeout guard tests ---- +@pytest.mark.asyncio +async def test_response_sender_marks_response_active_before_create_returns() -> None: + """The sender should not wait for response.created before blocking the next response.""" + deps = ToolDependencies(reachy_mini=MagicMock(), movement_manager=MagicMock()) + handler = rt_mod.OpenaiRealtimeHandler(deps) + + create_started = asyncio.Event() + create_returned = asyncio.Event() + allow_done = asyncio.Event() + event_states_at_create: list[bool] = [] + + class FakeResponse: + async def create(self, **_kw: Any) -> None: + event_states_at_create.append(handler._response_done_event.is_set()) + create_started.set() + await allow_done.wait() + handler._response_done_event.set() + create_returned.set() + + async def cancel(self, **_kw: Any) -> None: + pass + + fake_conn = MagicMock() + fake_conn.response = FakeResponse() + handler.connection = fake_conn + + await handler._safe_response_create(instructions="req1") + sender_task = asyncio.create_task(handler._response_sender_loop()) + + await asyncio.wait_for(create_started.wait(), timeout=1) + assert event_states_at_create == [False] + + allow_done.set() + await asyncio.wait_for(create_returned.wait(), timeout=1) + + handler.connection = None + await handler._safe_response_create(instructions="stop") + await asyncio.wait_for(sender_task, timeout=1) + + @pytest.mark.asyncio async def test_response_sender_loop_times_out_waiting_for_response_done( monkeypatch: Any, caplog: Any, diff --git a/projects/reachy-mini-openshell/tests/test_riva_asr.py b/projects/reachy-mini-openshell/tests/test_riva_asr.py index 9a28d01b..0779e274 100644 --- a/projects/reachy-mini-openshell/tests/test_riva_asr.py +++ b/projects/reachy-mini-openshell/tests/test_riva_asr.py @@ -1,4 +1,10 @@ -from reachy_mini_conversation_app.riva_asr import RivaAsrConfig +import sys +import asyncio +from collections.abc import Callable + +import pytest + +from reachy_mini_conversation_app.riva_asr import RivaAsrConfig, RivaStreamingTranscriber def test_riva_config_accepts_http_endpoint_url(monkeypatch): @@ -32,3 +38,82 @@ def test_riva_use_ssl_env_overrides_endpoint_url_scheme(monkeypatch): assert config.server_uri == "riva.example.test:443" assert config.use_ssl is False + + +def test_blank_riva_use_ssl_env_keeps_endpoint_url_inference(monkeypatch): + """Blank RIVA_USE_SSL values should not disable https:// inference.""" + monkeypatch.setenv("RIVA_SERVER_URI", "https://riva.example.test:443") + monkeypatch.setenv("RIVA_USE_SSL", "") + + config = RivaAsrConfig.from_env() + + assert config.server_uri == "riva.example.test:443" + assert config.use_ssl is True + + +@pytest.mark.asyncio +async def test_riva_missing_dependency_reports_error_without_send_audio_raise(monkeypatch): + """Missing nvidia-riva-client should report through callbacks without crashing send_audio.""" + monkeypatch.setitem(sys.modules, "riva", None) + delivered: list[str] = [] + + async def on_final(transcript: str) -> None: + delivered.append(transcript) + + transcriber = RivaStreamingTranscriber( + config=RivaAsrConfig( + server_uri="localhost:50051", + language_code="en-US", + model="", + use_ssl=False, + ssl_cert=None, + authorization=None, + metadata=(), + interim_results=True, + automatic_punctuation=True, + ), + on_final_transcript=on_final, + ) + + await transcriber.start(16000) + await asyncio.wait_for(_wait_until(lambda: bool(delivered)), timeout=1) + await transcriber.send_audio(b"\x00\x00") + + assert "Riva STT mode requires the optional dependency" in delivered[0] + + +@pytest.mark.asyncio +async def test_repeated_final_transcripts_are_delivered() -> None: + """Separate identical final utterances should both be routed to the text path.""" + delivered: list[str] = [] + + async def on_final(transcript: str) -> None: + delivered.append(transcript) + + transcriber = RivaStreamingTranscriber( + config=RivaAsrConfig( + server_uri="localhost:50051", + language_code="en-US", + model="", + use_ssl=False, + ssl_cert=None, + authorization=None, + metadata=(), + interim_results=True, + automatic_punctuation=True, + ), + on_final_transcript=on_final, + ) + transcriber._loop = asyncio.get_running_loop() + + transcriber._schedule_final("yes") + transcriber._schedule_final("yes") + await asyncio.wait_for(_wait_until(lambda: len(delivered) == 2), timeout=1) + + assert delivered == ["yes", "yes"] + + +async def _wait_until(predicate: Callable[[], bool]) -> None: + """Yield until predicate returns true.""" + while not predicate(): + await asyncio.sleep(0) diff --git a/projects/reachy-mini-openshell/tests/tools/test_background_tool_manager.py b/projects/reachy-mini-openshell/tests/tools/test_background_tool_manager.py index 90b7a7f1..7f6e38a6 100644 --- a/projects/reachy-mini-openshell/tests/tools/test_background_tool_manager.py +++ b/projects/reachy-mini-openshell/tests/tools/test_background_tool_manager.py @@ -517,6 +517,37 @@ async def test_startup_multiple_callbacks(self, manager: BackgroundToolManager) assert cb1.call_count == 1 assert cb2.call_count == 1 + @pytest.mark.asyncio + async def test_shutdown_waits_for_running_tool_tasks(self, manager: BackgroundToolManager) -> None: + """Shutdown should cancel and drain running tool tasks before returning.""" + started = asyncio.Event() + cancelled = asyncio.Event() + routine = MagicMock(spec=ToolCallRoutine) + routine.tool_name = "long_tool" + routine.args_json_str = "{}" + + async def _call(_manager: BackgroundToolManager) -> dict[str, Any]: + started.set() + try: + await asyncio.sleep(10) + except asyncio.CancelledError: + cancelled.set() + raise + return {"ok": True} + + routine.__call__ = _call # type: ignore[method-assign] + routine.side_effect = _call + + bg = await manager.start_tool("c1", routine, is_idle_tool_call=False) + await asyncio.wait_for(started.wait(), timeout=1) + + await manager.shutdown() + + assert cancelled.is_set() + assert bg._task is not None + assert bg._task.done() + assert bg.status == ToolState.CANCELLED + class TestNotificationQueue: """Verify notifications are enqueued on tool completion or failure.""" diff --git a/projects/reachy-mini-openshell/uv.lock b/projects/reachy-mini-openshell/uv.lock index b4ec368f..f9160eb6 100644 --- a/projects/reachy-mini-openshell/uv.lock +++ b/projects/reachy-mini-openshell/uv.lock @@ -486,7 +486,7 @@ name = "exceptiongroup" version = "1.3.1" source = { registry = "https://pypi.org/simple" } dependencies = [ - { name = "typing-extensions", marker = "sys_platform == 'darwin' or (extra == 'extra-28-reachy-mini-conversation-app-all-vision' and extra == 'extra-28-reachy-mini-conversation-app-riva') or (extra == 'extra-28-reachy-mini-conversation-app-mediapipe-vision' and extra == 'extra-28-reachy-mini-conversation-app-riva')" }, + { name = "typing-extensions", marker = "(python_full_version < '3.11' and sys_platform == 'darwin') or (python_full_version >= '3.11' and extra == 'extra-28-reachy-mini-conversation-app-all-vision' and extra == 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sys_platform == 'darwin' and extra == 'extra-28-reachy-mini-conversation-app-all-vision') or (python_full_version < '3.11' and sys_platform == 'darwin' and extra == 'extra-28-reachy-mini-conversation-app-mediapipe-vision') or (python_full_version < '3.11' and sys_platform == 'darwin' and extra != 'extra-28-reachy-mini-conversation-app-riva') or (python_full_version >= '3.11' and extra == 'extra-28-reachy-mini-conversation-app-all-vision' and extra == 'extra-28-reachy-mini-conversation-app-riva') or (python_full_version >= '3.11' and extra == 'extra-28-reachy-mini-conversation-app-mediapipe-vision' and extra == 'extra-28-reachy-mini-conversation-app-riva') or (sys_platform != 'darwin' and extra == 'extra-28-reachy-mini-conversation-app-all-vision' and extra == 'extra-28-reachy-mini-conversation-app-riva') or (sys_platform != 'darwin' and extra == 'extra-28-reachy-mini-conversation-app-mediapipe-vision' and extra == 'extra-28-reachy-mini-conversation-app-riva')" }, + { name = 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'extra-28-reachy-mini-conversation-app-mediapipe-vision' and extra == 'extra-28-reachy-mini-conversation-app-riva')" }, { name = "supervision", marker = "sys_platform == 'darwin' or (extra == 'extra-28-reachy-mini-conversation-app-all-vision' and extra == 'extra-28-reachy-mini-conversation-app-riva') or (extra == 'extra-28-reachy-mini-conversation-app-mediapipe-vision' and extra == 'extra-28-reachy-mini-conversation-app-riva')" }, { name = "ultralytics", marker = "sys_platform == 'darwin' or (extra == 'extra-28-reachy-mini-conversation-app-all-vision' and extra == 'extra-28-reachy-mini-conversation-app-riva') or (extra == 'extra-28-reachy-mini-conversation-app-mediapipe-vision' and extra == 'extra-28-reachy-mini-conversation-app-riva')" }, ] @@ -2226,6 +2270,8 @@ requires-dist = [ { name = "num2words", marker = "extra == 'all-vision'" }, { name = "num2words", marker = "extra == 'local-vision'" }, { name = "nvidia-riva-client", marker = "extra == 'riva'", specifier = ">=2.19,<3" }, + { name = "onnxruntime", marker = "extra == 'all-vision'" }, + { name = "onnxruntime", marker = "extra == 'yolo-vision'" }, { name = "openai", specifier = ">=2.1" }, { name = "opencv-python", specifier = ">=4.12.0.88" }, { name = "python-dotenv" }, From 4eaef06c61df1b33f6604375530d34c8cc521b5a Mon Sep 17 00:00:00 2001 From: Johnny Greco Date: Fri, 26 Jun 2026 16:07:11 -0400 Subject: [PATCH 16/45] Finalize Reachy conversation backend refactor --- .gitignore | 1 + .../reachy-mini-conversation-simulator.md | 254 ++- projects/reachy-mini-openshell/.env.example | 74 +- .../.env.hf-realtime.example | 21 + .../.env.local-stt.example | 28 + .../.env.openai-realtime.example | 17 + projects/reachy-mini-openshell/README.md | 383 +++- projects/reachy-mini-openshell/pyproject.toml | 12 +- .../scripts/fake_openai_backend.py | 149 ++ .../scripts/smoke-local-stt.sh | 300 +++ .../scripts/start-local.sh | 3 + .../reachy_mini_conversation_app/__init__.py | 12 +- .../audio/__init__.py | 2 +- .../audio/mic_phrase.py | 87 + .../reachy_mini_conversation_app/audio/pcm.py | 141 ++ .../backend_check.py | 786 +++++++ .../backend_runtime.py | 209 ++ .../camera_worker.py | 15 +- .../chat_completions.py | 270 +++ .../reachy_mini_conversation_app/config.py | 491 ++++- .../reachy_mini_conversation_app/console.py | 62 +- ...nai_realtime.py => conversation_stream.py} | 777 ++++--- .../dance_emotion_moves.py | 4 +- .../goto_queue_move.py | 4 +- .../local_stt_backend.py | 101 + .../src/reachy_mini_conversation_app/main.py | 83 +- .../src/reachy_mini_conversation_app/moves.py | 34 +- .../sweep_look.py | 4 +- .../realtime_backends.py | 162 ++ .../reachy_mini_conversation_app/riva_asr.py | 220 -- .../speech_endpoints.py | 110 + .../tools/background_tool_manager.py | 9 +- .../tools/camera.py | 6 +- .../tools/core_tools.py | 4 +- .../tools/move_head.py | 2 +- .../tools/play_emotion.py | 70 +- .../tools/task_status.py | 4 +- .../src/reachy_mini_conversation_app/utils.py | 12 +- .../vision/__init__.py | 2 +- .../vision/processors.py | 65 +- .../vision/yolo_head_tracker.py | 6 +- .../tests/audio/test_pcm.py | 34 + .../tests/test_backend_check.py | 1007 +++++++++ .../tests/test_backend_runtime.py | 65 + .../tests/test_config.py | 464 +++++ .../tests/test_conversation_stream.py | 1826 +++++++++++++++++ .../tests/test_fake_openai_backend.py | 83 + .../tests/test_local_stt_backend.py | 105 + .../reachy-mini-openshell/tests/test_main.py | 44 + .../tests/test_mic_phrase.py | 61 + .../tests/test_openai_realtime.py | 1129 ---------- .../tests/test_package.py | 7 + .../tests/test_realtime_backends.py | 91 + .../tests/test_riva_asr.py | 119 -- .../tests/test_speech_endpoints.py | 103 + .../tools/test_background_tool_manager.py | 2 - .../tests/tools/test_play_emotion.py | 31 + .../tests/vision/test_processors.py | 39 +- projects/reachy-mini-openshell/uv.lock | 947 ++++----- 59 files changed, 8369 insertions(+), 2784 deletions(-) create mode 100644 projects/reachy-mini-openshell/.env.hf-realtime.example create mode 100644 projects/reachy-mini-openshell/.env.local-stt.example create mode 100644 projects/reachy-mini-openshell/.env.openai-realtime.example create mode 100755 projects/reachy-mini-openshell/scripts/fake_openai_backend.py create mode 100755 projects/reachy-mini-openshell/scripts/smoke-local-stt.sh create mode 100644 projects/reachy-mini-openshell/src/reachy_mini_conversation_app/audio/mic_phrase.py create mode 100644 projects/reachy-mini-openshell/src/reachy_mini_conversation_app/audio/pcm.py create mode 100644 projects/reachy-mini-openshell/src/reachy_mini_conversation_app/backend_check.py create mode 100644 projects/reachy-mini-openshell/src/reachy_mini_conversation_app/backend_runtime.py create mode 100644 projects/reachy-mini-openshell/src/reachy_mini_conversation_app/chat_completions.py rename projects/reachy-mini-openshell/src/reachy_mini_conversation_app/{openai_realtime.py => conversation_stream.py} (63%) create mode 100644 projects/reachy-mini-openshell/src/reachy_mini_conversation_app/local_stt_backend.py create mode 100644 projects/reachy-mini-openshell/src/reachy_mini_conversation_app/realtime_backends.py delete mode 100644 projects/reachy-mini-openshell/src/reachy_mini_conversation_app/riva_asr.py create mode 100644 projects/reachy-mini-openshell/src/reachy_mini_conversation_app/speech_endpoints.py create mode 100644 projects/reachy-mini-openshell/tests/audio/test_pcm.py create mode 100644 projects/reachy-mini-openshell/tests/test_backend_check.py create mode 100644 projects/reachy-mini-openshell/tests/test_backend_runtime.py create mode 100644 projects/reachy-mini-openshell/tests/test_config.py create mode 100644 projects/reachy-mini-openshell/tests/test_conversation_stream.py create mode 100644 projects/reachy-mini-openshell/tests/test_fake_openai_backend.py create mode 100644 projects/reachy-mini-openshell/tests/test_local_stt_backend.py create mode 100644 projects/reachy-mini-openshell/tests/test_main.py create mode 100644 projects/reachy-mini-openshell/tests/test_mic_phrase.py delete mode 100644 projects/reachy-mini-openshell/tests/test_openai_realtime.py create mode 100644 projects/reachy-mini-openshell/tests/test_package.py create mode 100644 projects/reachy-mini-openshell/tests/test_realtime_backends.py delete mode 100644 projects/reachy-mini-openshell/tests/test_riva_asr.py create mode 100644 projects/reachy-mini-openshell/tests/test_speech_endpoints.py create mode 100644 projects/reachy-mini-openshell/tests/tools/test_play_emotion.py diff --git a/.gitignore b/.gitignore index f1304db4..245e108a 100644 --- a/.gitignore +++ b/.gitignore @@ -13,6 +13,7 @@ Thumbs.db .env .env.* !.env.example +!.env.*.example *.local *.key *.pem diff --git a/docs/research/reachy-mini-conversation-simulator.md b/docs/research/reachy-mini-conversation-simulator.md index 51671e42..545e3084 100644 --- a/docs/research/reachy-mini-conversation-simulator.md +++ b/docs/research/reachy-mini-conversation-simulator.md @@ -14,9 +14,10 @@ for the broader app family: [pollen-robotics/reachy_mini_conversation_app](https - macOS with Python 3.10, 3.11, or 3.12. Python 3.12 is the recommended local version. - `uv`. -- An API key for conversation. `OpenAI Realtime` microphone mode requires an - OpenAI-compatible Realtime model. `Riva STT` and `Text` mode can use - OpenAI-compatible Chat Completions providers such as NVIDIA NIM. +- Provider credentials for the backend you select in `.env`. The app supports + OpenAI Realtime, the default Pollen/Hugging Face realtime path, and a local + STT cascade that combines an OpenAI-compatible transcription endpoint, Chat + Completions, and TTS. - This repository checked out locally. The local dependency set includes `reachy-mini[mujoco]==1.8.0`, so the MuJoCo @@ -31,34 +32,197 @@ cd projects/reachy-mini-openshell uv venv --python 3.12 source .venv/bin/activate uv sync -cp .env.example .env ``` -Edit `.env`. For OpenAI Realtime microphone and text input, use: +Choose one backend starter and copy it to `.env`: ```sh -OPENAI_API_KEY=your_api_key_here -OPENAI_BASE_URL=https://api.openai.com/v1 -MODEL_NAME=gpt-realtime -AUDIO_INPUT_MODE=openai_realtime +cp .env.openai-realtime.example .env +# or: cp .env.hf-realtime.example .env +# or: cp .env.local-stt.example .env ``` -For NVIDIA-hosted text input through an OpenAI-compatible Chat Completions -endpoint, reference your existing NVIDIA API key environment variable: +`.env.example` is the combined local-STT starter used by the launcher when no +`.env` exists. + +For OpenAI Realtime microphone and text input, use: + +```sh +BACKEND_PROVIDER=openai_realtime +OPENAI_REALTIME_BASE_URL=https://api.openai.com/v1 +OPENAI_REALTIME_MODEL=gpt-realtime +OPENAI_REALTIME_VOICE=cedar +``` + +OpenAI Realtime uses the standard, globally exported `OPENAI_API_KEY` directly. +Do not copy the global key into `.env` for the normal OpenAI path. Start the app +from a shell where `OPENAI_API_KEY` is already exported. Set +`OPENAI_REALTIME_API_KEY` in `.env` only when this app should use a different +key from the global OpenAI key. + +For the default Pollen/Hugging Face realtime path, use: + +```sh +BACKEND_PROVIDER=hf_realtime +HF_REALTIME_CONNECTION_MODE=deployed +HF_REALTIME_MODEL= +HF_REALTIME_VOICE=Aiden +``` + +For a local Hugging Face realtime backend, point at the backend websocket: + +```sh +BACKEND_PROVIDER=hf_realtime +HF_REALTIME_CONNECTION_MODE=local +HF_REALTIME_WS_URL=ws://127.0.0.1:8765/v1/realtime +``` + +For a local STT cascade, combine an OpenAI-compatible transcription endpoint, a +Chat Completions model, and a TTS endpoint: ```sh -OPENAI_API_KEY=${NVIDIA_API_KEY} -OPENAI_BASE_URL=https://inference-api.nvidia.com/v1 -MODEL_NAME=azure/anthropic/claude-opus-4-8 -AUDIO_INPUT_MODE=text +BACKEND_PROVIDER=local_stt +CHAT_API_KEY=${NVIDIA_INFERENCE_API_KEY} +CHAT_BASE_URL=https://inference-api.nvidia.com/v1 +CHAT_MODEL_NAME=azure/anthropic/claude-opus-4-8 +STT_API_KEY=not-needed +STT_BASE_URL=http://127.0.0.1:9000/v1 +STT_MODEL_NAME=whisper-1 +TTS_API_KEY=${OPENAI_API_KEY} +TTS_BASE_URL=https://api.openai.com/v1 +TTS_MODEL_NAME=gpt-4o-mini-tts +TTS_VOICE=cedar ``` Use the exact model ID exposed by your provider. For example, NVIDIA model IDs can look like `nvidia/nemotron-3-super-120b-a12b` or `azure/anthropic/claude-opus-4-8`, depending on the endpoint and account. +The API key values can reference exported system environment variables using +dotenv syntax, for example `${NVIDIA_INFERENCE_API_KEY}`. + +Backend routing and model selection are loaded from `.env`. Secret values can +be literal dotenv values, dotenv references to exported variables, or exported +`OPENAI_API_KEY` for OpenAI Realtime. The standard OpenAI Realtime path uses +the global `OPENAI_API_KEY` directly. The browser UI does not include fields +for credentials, endpoint routing, or model selection. + +`BACKEND_PROVIDER` must be set exactly to `openai_realtime`, `hf_realtime`, or +`local_stt`. The app does not choose a backend implicitly; missing or unknown +values fail preflight and startup. -Those provider values are loaded from `.env` only. The browser UI does not -include fields for credentials, endpoint routing, or model selection. +Before launching the UI, validate the selected backend: + +```sh +reachy-mini-backend-check +``` + +To call configured backend endpoints without opening the browser, add `--live`: + +```sh +reachy-mini-backend-check --live +``` + +For `BACKEND_PROVIDER=openai_realtime` and `BACKEND_PROVIDER=hf_realtime`, this +opens a realtime session, sends the app's session configuration, and then shuts +the session down. For `BACKEND_PROVIDER=local_stt`, `--live` defaults to the +app-flow check: it feeds audio through the handler's microphone receive path +against fake Reachy dependencies, then verifies +`mic frame handling -> STT -> Chat Completions -> Reachy tools -> TTS`. + +You can also name the app-flow stage explicitly: + +```sh +reachy-mini-backend-check --live --stage app-flow \ + --seed-text "Reachy, use the sweep_look tool, then tell me what you did." +``` + +The app-flow check uses fake Reachy tool dependencies by default. After the +simulator daemon is running, add `--real-reachy` to connect through the Reachy +SDK and queue movements through the real movement manager: + +```sh +reachy-mini-backend-check --live --stage app-flow --require-tool --real-reachy \ + --seed-text "Reachy, use the sweep_look tool, then tell me what you did." +``` + +If your real STT endpoint is not reachable yet, start the local fake +OpenAI-compatible smoke workflow: + +```sh +scripts/smoke-local-stt.sh +scripts/smoke-local-stt.sh --real-reachy +scripts/smoke-local-stt.sh --gradio +``` + +The first command checks the app handler path against fake Reachy dependencies. +The second also connects through the Reachy SDK and movement manager, so it +requires the simulator daemon to be running. The `--gradio` variant launches +the actual Gradio app, verifies the `Talk with Reachy Mini` UI, and sends a +text tool-call prompt through the running app process. + +For manual debugging, you can run the fake backend directly: + +```sh +uv run python scripts/fake_openai_backend.py +``` + +In another terminal, point a disposable config at it and run the same app-flow +check: + +```sh +cat > .env.smoke <<'EOF' +BACKEND_PROVIDER=local_stt +CHAT_API_KEY=not-needed +CHAT_BASE_URL=http://127.0.0.1:8766/v1 +CHAT_MODEL_NAME=fake-chat +STT_API_KEY=not-needed +STT_BASE_URL=http://127.0.0.1:8766/v1 +STT_MODEL_NAME=fake-whisper +TTS_API_KEY=not-needed +TTS_BASE_URL=http://127.0.0.1:8766/v1 +TTS_MODEL_NAME=fake-tts +TTS_VOICE=fake-voice +EOF + +reachy-mini-backend-check --env-file .env.smoke --live --stage app-flow --require-tool +reachy-mini-backend-check --env-file .env.smoke --live --stage app-flow --require-tool --real-reachy +``` + +This checks the app's OpenAI-compatible HTTP plumbing and simulator movement +path. It does not replace a final check against the real STT service. + +While services are coming online, check each local STT stage independently: + +```sh +reachy-mini-backend-check --live --stage stt --audio-file ./sample-input.wav +reachy-mini-backend-check --live --stage chat \ + --seed-text "Reachy, use the sweep_look tool, then tell me what you did." \ + --require-tool +reachy-mini-backend-check --live --stage tts \ + --seed-text "Hello, I am Reachy." +``` + +`--stage stt` only needs `STT_*` values and a sample audio file. +`--stage chat` only needs `CHAT_*` values. `--stage tts` only needs `TTS_*` +values. The full `--stage app-flow` check still requires all local-STT pieces +and feeds audio through the handler's microphone receive path before STT. +Use `--require-tool` with `--stage chat` or `--stage app-flow` when the check +should fail unless the model calls a Reachy tool. + +To try a candidate dotenv file without replacing `.env`, pass it explicitly to +the checker: + +```sh +reachy-mini-backend-check --env-file .env.local-stt +``` + +Launch the app with that same candidate file by setting +`REACHY_MINI_DOTENV_PATH`: + +```sh +REACHY_MINI_DOTENV_PATH=.env.local-stt \ + python -m reachy_mini_conversation_app --gradio --no-camera +``` Run a quick import check: @@ -172,30 +336,31 @@ http://127.0.0.1:7860/ ``` You should see the `Talk with Reachy Mini` page with an empty chat transcript, -an `Input` selector with `OpenAI Realtime`, `Riva STT`, and `Text` options. -`Text` mode shows the message box and send button. The two microphone modes show -the audio stream panel. +an audio stream panel, and an `Input` selector. -If the app logs that `OPENAI_API_KEY` is missing, stop the app, update `.env`, -and restart it. Credentials are intentionally not entered in the browser. If -`.env` references `${NVIDIA_API_KEY}`, make sure that variable is -exported in the shell that starts the app. +![Gradio conversation UI for Talk with Reachy Mini](../assets/reachy-mini-openshell/screenshots/gradio-home.png) -## 6. Talk To Reachy +If the app logs a missing local backend value such as `CHAT_API_KEY`, +`STT_BASE_URL`, or `TTS_BASE_URL`, stop the app, update `.env`, and restart it. +Credentials are intentionally not entered in the browser. For OpenAI Realtime, +export the standard `OPENAI_API_KEY` in the shell that starts the app. Set +`OPENAI_REALTIME_API_KEY` in `.env` only if this app should use a different +OpenAI key. If `.env` references `${NVIDIA_INFERENCE_API_KEY}`, make sure that +variable is exported in the shell that starts the app. -Use `OpenAI Realtime` to speak when `MODEL_NAME` points to a Realtime-capable -model. Click `Click to Access Microphone` in the `Stream` panel and allow -microphone access in the browser. Once the stream starts, speak naturally. +## 6. Talk To Reachy -Use `Riva STT` when you have a Riva ASR endpoint and want speech-to-text before -sending text to a Chat Completions provider. Set `AUDIO_INPUT_MODE=riva_stt`, -configure `RIVA_SERVER_URI`, and install the Riva optional dependencies with -`uv sync --extra riva`. +Use `Microphone` mode to speak. With `BACKEND_PROVIDER=openai_realtime` or +`BACKEND_PROVIDER=hf_realtime`, browser audio streams to the selected realtime +backend. With `BACKEND_PROVIDER=local_stt`, the app buffers each spoken phrase, +sends it to `STT_BASE_URL` for transcription, sends the transcript through Chat +Completions, then plays Reachy's synthesized response from `TTS_BASE_URL`. +Click `Click to Access Microphone` in the `Stream` panel and allow microphone +access in the browser. Once the stream starts, speak naturally. Use `Text` mode to type instead. Switch `Input` to `Text`, enter a message, and -send it from the text composer. For non-Realtime model IDs such as NVIDIA NIM -models, text mode uses Chat Completions. Tool calls are supported in text mode -and in the Riva STT path, including providers that require the tool schema to +send it from the text composer. Tool calls are supported in text mode and in +microphone-to-text mode, including providers that require the tool schema to remain attached after a tool result is returned. Useful first prompts are: @@ -228,13 +393,24 @@ on local URL` value from the terminal into your browser. If the browser cannot access the microphone, check the browser permission prompt and macOS microphone privacy settings. -If text mode returns `404 page not found`, check that `OPENAI_BASE_URL` matches -the provider's OpenAI-compatible endpoint and that `MODEL_NAME` is an exact +If `reachy-mini-backend-check` reports older config keys such as +`OPENAI_BASE_URL` or `MODEL_NAME`, replace that `.env` shape with one of the +current `BACKEND_PROVIDER` configurations. Those old keys are intentionally not +used. + +If text mode returns `404 page not found` with `BACKEND_PROVIDER=local_stt`, +check that `CHAT_BASE_URL` is a plain OpenAI-compatible endpoint string, such as +`https://inference-api.nvidia.com/v1`, and that `CHAT_MODEL_NAME` is an exact model ID from that provider. If text mode returns `401 Unauthorized` with NVIDIA endpoints, make sure -`OPENAI_API_KEY=${NVIDIA_API_KEY}` resolves to a key that is authorized for -generation, not only model listing. +`CHAT_API_KEY=${NVIDIA_INFERENCE_API_KEY}` resolves to a key that is authorized +for generation, not only model listing. + +If microphone-to-text returns a transcription error with +`BACKEND_PROVIDER=local_stt`, make sure `STT_BASE_URL` includes the `/v1` base +path expected by OpenAI-compatible clients and that the service exposes +`POST /audio/transcriptions` for `STT_MODEL_NAME`. If the daemon reports `MuJoCo is not installed`, make sure you started the daemon from this project environment after running `uv sync`. The dependency is diff --git a/projects/reachy-mini-openshell/.env.example b/projects/reachy-mini-openshell/.env.example index 060850d0..8df26254 100644 --- a/projects/reachy-mini-openshell/.env.example +++ b/projects/reachy-mini-openshell/.env.example @@ -1,27 +1,57 @@ -OPENAI_API_KEY=${NVIDIA_API_KEY} -OPENAI_BASE_URL=https://inference-api.nvidia.com/v1 -MODEL_NAME=azure/anthropic/claude-opus-4-8 - -# Audio input modes: -# - openai_realtime: microphone audio goes to an OpenAI-compatible Realtime endpoint. -# - riva_stt: microphone audio goes to Riva ASR; final transcripts go to the text LLM path. -# - text: typed input goes to the text LLM path. -AUDIO_INPUT_MODE=text - -# Used only when AUDIO_INPUT_MODE=riva_stt. -# Accepts either host:port or http(s)://host:port. -RIVA_SERVER_URI=localhost:50051 -# Optional override. Leave unset to infer TLS from an https:// RIVA_SERVER_URI. -# RIVA_USE_SSL=false -RIVA_LANGUAGE_CODE=en-US -RIVA_ASR_MODEL= -RIVA_AUTHORIZATION= -RIVA_METADATA= -RIVA_INTERIM_RESULTS=true -RIVA_AUTOMATIC_PUNCTUATION=true +# Default local-STT example. For backend-specific starter files, see: +# - .env.openai-realtime.example +# - .env.hf-realtime.example +# - .env.local-stt.example +# +# Required: select exactly one conversation backend. +# - openai_realtime: OpenAI Realtime API handles speech input, tools, and speech output. +# - hf_realtime: Pollen/Hugging Face realtime voice backend handles speech input, tools, and speech output. +# - local_stt: local/OpenAI-compatible STT endpoint + Chat Completions model + TTS endpoint. +BACKEND_PROVIDER=local_stt + +# Local STT cascade backend. +CHAT_API_KEY=${NVIDIA_INFERENCE_API_KEY} +CHAT_BASE_URL=https://inference-api.nvidia.com/v1 +CHAT_MODEL_NAME=azure/anthropic/claude-opus-4-8 + +STT_API_KEY=not-needed +STT_BASE_URL=http://127.0.0.1:9000/v1 +STT_MODEL_NAME=whisper-1 + +TTS_API_KEY=${OPENAI_API_KEY} +TTS_BASE_URL=https://api.openai.com/v1 +TTS_MODEL_NAME=gpt-4o-mini-tts +TTS_VOICE=cedar + +# OpenAI Realtime backend. +# Uses the globally exported OPENAI_API_KEY by default; no key is required here. +# Uncomment OPENAI_REALTIME_API_KEY only if this app should use a different key +# from the global OpenAI key. +# OPENAI_REALTIME_API_KEY= +OPENAI_REALTIME_BASE_URL=https://api.openai.com/v1 +OPENAI_REALTIME_MODEL=gpt-realtime +OPENAI_REALTIME_VOICE=cedar + +# Hugging Face realtime backend. +HF_REALTIME_CONNECTION_MODE=deployed +# Optional deployed session broker override. Leave unset for the default Pollen broker. +# HF_REALTIME_SESSION_URL=https://pollen-robotics-reachy-mini-realtime-url.hf.space/session +# For local HF realtime, set: +# HF_REALTIME_CONNECTION_MODE=local +# HF_REALTIME_WS_URL=ws://127.0.0.1:8765/v1/realtime +HF_REALTIME_MODEL= +HF_REALTIME_VOICE=Aiden +HF_TOKEN= + +REALTIME_TRANSCRIPTION_LANGUAGE=en + +# Local STT phrase detection. +MIC_TRANSCRIPTION_RMS_THRESHOLD=500 +MIC_TRANSCRIPTION_MIN_AUDIO_MS=250 +MIC_TRANSCRIPTION_SILENCE_MS=800 +MIC_TRANSCRIPTION_MAX_AUDIO_MS=12000 # Used only with --local-vision. LOCAL_VISION_MODEL=HuggingFaceTB/SmolVLM2-2.2B-Instruct HF_HOME=./cache -HF_TOKEN= diff --git a/projects/reachy-mini-openshell/.env.hf-realtime.example b/projects/reachy-mini-openshell/.env.hf-realtime.example new file mode 100644 index 00000000..424e1651 --- /dev/null +++ b/projects/reachy-mini-openshell/.env.hf-realtime.example @@ -0,0 +1,21 @@ +# Pollen/Hugging Face realtime voice backend handles speech input, tools, and speech output. +BACKEND_PROVIDER=hf_realtime + +# Use the default deployed Pollen session broker. +HF_REALTIME_CONNECTION_MODE=deployed +HF_REALTIME_MODEL= +HF_REALTIME_VOICE=Aiden +HF_TOKEN= + +# Optional deployed session broker override. Leave unset for the default Pollen broker. +# HF_REALTIME_SESSION_URL=https://pollen-robotics-reachy-mini-realtime-url.hf.space/session + +# For local HF realtime instead, use: +# HF_REALTIME_CONNECTION_MODE=local +# HF_REALTIME_WS_URL=ws://127.0.0.1:8765/v1/realtime + +REALTIME_TRANSCRIPTION_LANGUAGE=en + +# Used only with --local-vision. +LOCAL_VISION_MODEL=HuggingFaceTB/SmolVLM2-2.2B-Instruct +HF_HOME=./cache diff --git a/projects/reachy-mini-openshell/.env.local-stt.example b/projects/reachy-mini-openshell/.env.local-stt.example new file mode 100644 index 00000000..ede737b2 --- /dev/null +++ b/projects/reachy-mini-openshell/.env.local-stt.example @@ -0,0 +1,28 @@ +# Local/OpenAI-compatible STT endpoint + Chat Completions model + TTS endpoint. +BACKEND_PROVIDER=local_stt + +# Chat Completions model for reasoning and Reachy tool calls. +CHAT_API_KEY=${NVIDIA_INFERENCE_API_KEY} +CHAT_BASE_URL=https://inference-api.nvidia.com/v1 +CHAT_MODEL_NAME=azure/anthropic/claude-opus-4-8 + +# Speech-to-text endpoint. Use not-needed for local no-auth endpoints. +STT_API_KEY=not-needed +STT_BASE_URL=http://127.0.0.1:9000/v1 +STT_MODEL_NAME=whisper-1 + +# Text-to-speech endpoint used for Reachy's spoken reply. +TTS_API_KEY=${OPENAI_API_KEY} +TTS_BASE_URL=https://api.openai.com/v1 +TTS_MODEL_NAME=gpt-4o-mini-tts +TTS_VOICE=cedar + +# Local STT phrase detection. +MIC_TRANSCRIPTION_RMS_THRESHOLD=500 +MIC_TRANSCRIPTION_MIN_AUDIO_MS=250 +MIC_TRANSCRIPTION_SILENCE_MS=800 +MIC_TRANSCRIPTION_MAX_AUDIO_MS=12000 + +# Used only with --local-vision. +LOCAL_VISION_MODEL=HuggingFaceTB/SmolVLM2-2.2B-Instruct +HF_HOME=./cache diff --git a/projects/reachy-mini-openshell/.env.openai-realtime.example b/projects/reachy-mini-openshell/.env.openai-realtime.example new file mode 100644 index 00000000..9573ca57 --- /dev/null +++ b/projects/reachy-mini-openshell/.env.openai-realtime.example @@ -0,0 +1,17 @@ +# OpenAI Realtime API handles speech input, tools, and speech output. +# Uses the globally exported OPENAI_API_KEY directly by default. +# Do not paste the global OpenAI key into this file for the normal path. +# Uncomment OPENAI_REALTIME_API_KEY only if this app should use a different key +# from the global OpenAI key. +BACKEND_PROVIDER=openai_realtime + +# OPENAI_REALTIME_API_KEY= +OPENAI_REALTIME_BASE_URL=https://api.openai.com/v1 +OPENAI_REALTIME_MODEL=gpt-realtime +OPENAI_REALTIME_VOICE=cedar + +REALTIME_TRANSCRIPTION_LANGUAGE=en + +# Used only with --local-vision. +LOCAL_VISION_MODEL=HuggingFaceTB/SmolVLM2-2.2B-Instruct +HF_HOME=./cache diff --git a/projects/reachy-mini-openshell/README.md b/projects/reachy-mini-openshell/README.md index 0e220dc5..f4acae96 100644 --- a/projects/reachy-mini-openshell/README.md +++ b/projects/reachy-mini-openshell/README.md @@ -1,6 +1,5 @@ --- - -## title: Reachy OpenShell +title: Reachy OpenShell emoji: 🤖 colorFrom: purple colorTo: gray @@ -9,6 +8,7 @@ pinned: false tags: - reachy_mini - reachy_mini_python_app +--- # 🤖 Reachy OpenShell @@ -27,20 +27,16 @@ The Python package and command names intentionally match that template: - console script: `reachy-mini-conversation-app` - Reachy Mini Apps entry point: `reachy_mini_conversation_app` -The app is no longer the old `reachy_openshell` smoke/backend scaffold. There is -no standalone backend server on port `8080`, no `reachy_openshell.backend`, and -no `reachy_openshell.smoke` module. Runtime communication goes through the -Reachy Mini SDK and daemon, while the conversation UI is provided by Gradio or -the Reachy Mini app shell. +Runtime communication goes through the Reachy Mini SDK and daemon. The +conversation UI is provided by Gradio or the Reachy Mini app shell. ## What Is Here This project contains: - a forked Reachy Mini voice conversation app -- OpenAI Realtime audio conversation support -- Riva streaming ASR support for microphone-to-text input -- text conversation support through OpenAI-compatible Chat Completions +- selectable voice backends for OpenAI Realtime, Hugging Face realtime, and +local STT + Chat Completions + TTS - Reachy Mini movement, dance, emotion, and look-around tools - a locked OpenShell profile for instructions and tool selection - optional camera, local vision, YOLO head-tracking, and MediaPipe head-tracking @@ -55,9 +51,7 @@ this project. The SDK is pinned to the version compatible with the forked conversation-app dependency stack. - a running Reachy Mini daemon, either connected to hardware or started in simulator mode -- an API key for conversation. OpenAI Realtime microphone mode requires an -OpenAI-compatible Realtime model; Riva STT and text mode can use -OpenAI-compatible Chat Completions providers such as NVIDIA NIM. +- provider credentials for the backend selected in `.env` ## Install @@ -68,31 +62,73 @@ cd projects/reachy-mini-openshell uv venv --python 3.12 source .venv/bin/activate uv sync -cp .env.example .env ``` -Then edit `.env`. For OpenAI Realtime microphone and text input, use: +Then choose one backend starter and copy it to `.env`: + +```bash +cp .env.openai-realtime.example .env +# or: cp .env.hf-realtime.example .env +# or: cp .env.local-stt.example .env +``` + +`.env.example` is the combined local-STT starter used by the launcher when no +`.env` exists. + +For the OpenAI Realtime API: + +```bash +BACKEND_PROVIDER=openai_realtime +OPENAI_REALTIME_BASE_URL=https://api.openai.com/v1 +OPENAI_REALTIME_MODEL=gpt-realtime +OPENAI_REALTIME_VOICE=cedar +``` + +OpenAI Realtime uses the standard, globally exported `OPENAI_API_KEY` directly. +Do not copy the global key into `.env` for the normal OpenAI path. Start the app +from a shell where `OPENAI_API_KEY` is already exported. Set +`OPENAI_REALTIME_API_KEY` in `.env` only when this app should use a different +key from the global OpenAI key. + +For the default Pollen/Hugging Face realtime path: + +```bash +BACKEND_PROVIDER=hf_realtime +HF_REALTIME_CONNECTION_MODE=deployed +HF_REALTIME_MODEL= +HF_REALTIME_VOICE=Aiden +``` + +For a local Hugging Face realtime backend, use a direct websocket endpoint: ```bash -OPENAI_API_KEY=your_api_key_here -OPENAI_BASE_URL=https://api.openai.com/v1 -MODEL_NAME=gpt-realtime -AUDIO_INPUT_MODE=openai_realtime +BACKEND_PROVIDER=hf_realtime +HF_REALTIME_CONNECTION_MODE=local +HF_REALTIME_WS_URL=ws://127.0.0.1:8765/v1/realtime ``` -For NVIDIA-hosted text input through an OpenAI-compatible Chat Completions -endpoint, reference your existing NVIDIA API key environment variable: +For a local STT cascade, combine an OpenAI-compatible STT endpoint, a Chat +Completions model, and a TTS endpoint: ```bash -OPENAI_API_KEY=${NVIDIA_API_KEY} -OPENAI_BASE_URL=https://inference-api.nvidia.com/v1 -MODEL_NAME=azure/anthropic/claude-opus-4-8 -AUDIO_INPUT_MODE=text +BACKEND_PROVIDER=local_stt +CHAT_API_KEY=${NVIDIA_INFERENCE_API_KEY} +CHAT_BASE_URL=https://inference-api.nvidia.com/v1 +CHAT_MODEL_NAME=azure/anthropic/claude-opus-4-8 +STT_API_KEY=not-needed +STT_BASE_URL=http://127.0.0.1:9000/v1 +STT_MODEL_NAME=whisper-1 +TTS_API_KEY=${OPENAI_API_KEY} +TTS_BASE_URL=https://api.openai.com/v1 +TTS_MODEL_NAME=gpt-4o-mini-tts +TTS_VOICE=cedar ``` Use the exact model ID exposed by your provider. For example, NVIDIA model IDs can look like `nvidia/nemotron-3-super-120b-a12b` or `azure/anthropic/claude-opus-4-8`, depending on the endpoint and account. +The API key value can reference any exported system environment variable using +dotenv syntax, for example `${NVIDIA_INFERENCE_API_KEY}`. If you are not using `uv`, install the app in editable mode from the project directory: @@ -115,10 +151,9 @@ and regenerate `uv.lock` for that platform. ## Optional Dependencies -The active optional dependency groups cover Riva ASR and vision: +The active optional dependency groups are vision-related only: ```bash -uv sync --extra riva uv sync --extra local_vision uv sync --extra yolo_vision uv sync --extra mediapipe_vision @@ -128,17 +163,12 @@ uv sync --extra all_vision With `pip`, use the equivalent editable installs: ```bash -python -m pip install -e '.[riva]' python -m pip install -e '.[local_vision]' python -m pip install -e '.[yolo_vision]' python -m pip install -e '.[mediapipe_vision]' python -m pip install -e '.[all_vision]' ``` -The `riva` extra is intentionally marked incompatible with `mediapipe_vision` -and `all_vision` because the current Riva and MediaPipe client stacks require -different protobuf ranges. - There are no project-level `backend` or `sim` extras anymore. The previous backend extra belonged to the deleted scaffold. The default dependency set includes Reachy Mini's MuJoCo simulator backend because the local development @@ -146,36 +176,66 @@ workflow starts `reachy-mini-daemon --sim` from this environment. ## Configuration -The app loads `.env` from the current directory or a parent directory. Provider -credentials and routing must be configured in `.env`; they are not accepted from -the browser UI or the Reachy Mini settings UI. +The app loads `.env` from the current directory or a parent directory. To use a +candidate file without replacing `.env`, set `REACHY_MINI_DOTENV_PATH` before +starting the app. Backend routing and model selection are configured in dotenv +files; credentials are read from dotenv values, dotenv references to exported +variables, or exported `OPENAI_API_KEY` for OpenAI Realtime. They are not +accepted from the browser UI or the Reachy Mini settings UI. Supported `.env` values: -- `OPENAI_API_KEY`: API key used by the configured model provider. This can -reference another exported environment variable, such as -`${NVIDIA_API_KEY}`. -- `OPENAI_BASE_URL`: OpenAI-compatible API base URL. -- `MODEL_NAME`: provider model ID. Model names containing `realtime` use the -Realtime path; other model IDs use Chat Completions for text input. -- `AUDIO_INPUT_MODE`: initial input mode. Use `text` for the default typed -message path, `openai_realtime` when microphone audio should go to an -OpenAI-compatible Realtime endpoint, or `riva_stt` to stream microphone audio -to Riva ASR and pass final transcripts into the text LLM path. -- `RIVA_SERVER_URI`: Riva ASR server URI, for example `localhost:50051` or -`http://riva-host:9000`. URL schemes are normalized for the Riva client. -- `RIVA_USE_SSL`: optional override for TLS-enabled Riva endpoints. If this is -unset and `RIVA_SERVER_URI` starts with `https://`, TLS is enabled. -- `RIVA_LANGUAGE_CODE`: BCP-47 language code for Riva ASR, such as `en-US`. -- `RIVA_ASR_MODEL`: optional Riva ASR model name. Leave empty to let Riva -select a model from the language/configuration. -- `RIVA_AUTHORIZATION`: optional authorization metadata value, such as a bearer -token, for hosted Riva endpoints. -- `RIVA_METADATA`: optional comma-separated `key=value` metadata pairs passed -to the Riva client. +- `BACKEND_PROVIDER`: one of `openai_realtime`, `hf_realtime`, or `local_stt`. +This is the only switch that selects the voice backend. The app does not choose +a backend implicitly; missing or unknown values fail preflight and startup. +- `OPENAI_API_KEY`: standard global OpenAI API key used directly by +`BACKEND_PROVIDER=openai_realtime` when it is exported in the shell that starts +the app. This is the normal OpenAI Realtime credential path. It can also be +referenced from other dotenv values such as `TTS_API_KEY=${OPENAI_API_KEY}`. +- `OPENAI_REALTIME_API_KEY`: optional override for +`BACKEND_PROVIDER=openai_realtime`. Leave this unset unless the app should use a +different OpenAI key from the global `OPENAI_API_KEY`. +- `OPENAI_REALTIME_BASE_URL`: OpenAI Realtime API base URL. Defaults to +`https://api.openai.com/v1`. +- `OPENAI_REALTIME_MODEL`: OpenAI Realtime model ID. +- `OPENAI_REALTIME_VOICE`: OpenAI Realtime voice name. +- `HF_REALTIME_CONNECTION_MODE`: `deployed` for the default Pollen/Hugging Face +session broker, or `local` for a self-hosted Hugging Face realtime backend. +- `HF_REALTIME_SESSION_URL`: deployed Hugging Face session broker URL. Defaults +to the Pollen broker and usually does not need to be set. +- `HF_REALTIME_WS_URL`: local Hugging Face realtime websocket URL, required +when `HF_REALTIME_CONNECTION_MODE=local`. +- `HF_REALTIME_MODEL`: optional model ID passed to the Hugging Face realtime +backend. Leave empty to let the backend choose its default. +- `HF_REALTIME_VOICE`: voice name passed to the Hugging Face realtime backend. +- `HF_TOKEN`: optional token used by the deployed Hugging Face session broker +and gated Hugging Face models. +- `CHAT_API_KEY`: API key for `BACKEND_PROVIDER=local_stt` Chat Completions. +This can reference an exported shell variable, such as +`${NVIDIA_INFERENCE_API_KEY}`. +- `CHAT_BASE_URL`: OpenAI-compatible Chat Completions base URL. +- `CHAT_MODEL_NAME`: exact Chat Completions model ID exposed by the provider. +- `STT_BASE_URL`: OpenAI-compatible speech-to-text base URL. Microphone input +is buffered into a short WAV phrase, transcribed through this endpoint, then +passed to Chat Completions. +- `STT_API_KEY`: API key for `STT_BASE_URL`. For local no-auth STT endpoints, +use `not-needed`. +- `STT_MODEL_NAME`: transcription model ID. Defaults to `whisper-1`. +- `TTS_BASE_URL`: OpenAI-compatible text-to-speech base URL. +- `TTS_API_KEY`: API key for `TTS_BASE_URL`. For local no-auth TTS endpoints, +use `not-needed`. +- `TTS_MODEL_NAME`: speech model ID. Defaults to `gpt-4o-mini-tts`. +- `TTS_VOICE`: voice name for synthesized Reachy speech. +- `MIC_TRANSCRIPTION_RMS_THRESHOLD`: voice activity threshold for mic-to-text. +Defaults to `500`. +- `MIC_TRANSCRIPTION_MIN_AUDIO_MS`: minimum phrase length before the app can +submit audio for transcription. Defaults to `250`. +- `MIC_TRANSCRIPTION_SILENCE_MS`: trailing silence used to end a phrase. +Defaults to `800`. +- `MIC_TRANSCRIPTION_MAX_AUDIO_MS`: maximum phrase length before forcing a +transcription request. Defaults to `12000`. - `LOCAL_VISION_MODEL`: Hugging Face model used with `--local-vision`. - `HF_HOME`: Hugging Face cache directory. Defaults to `./cache`. -- `HF_TOKEN`: optional Hugging Face token for gated models. ## Run Locally @@ -186,19 +246,19 @@ projects/reachy-mini-openshell/scripts/start-local.sh ``` The script creates `.venv` when needed, runs `uv sync`, creates `.env` from -`.env.example` if missing, starts `reachy-mini-daemon --sim`, launches the -Gradio app, and prints the browser URL: +`.env.example` if missing, validates the selected backend config, starts +`reachy-mini-daemon --sim`, launches the Gradio app, and prints the browser URL: ```text http://127.0.0.1:7860/ ``` If port `7860` is busy, the launcher chooses the next free port through `7899` -and prints that URL instead. Pass app flags that are compatible with the -no-camera simulator baseline after the script name: +and prints that URL instead. Pass app flags after the script name: ```bash projects/reachy-mini-openshell/scripts/start-local.sh --debug +projects/reachy-mini-openshell/scripts/start-local.sh --head-tracker yolo ``` From inside `projects/reachy-mini-openshell`, the shorter form is: @@ -220,19 +280,164 @@ reachy-mini-daemon --sim --scene minimal --headless --no-media --fastapi-host 12 python -m reachy_mini_conversation_app --gradio --no-camera ``` -The Gradio UI includes an `Input` selector: +Before starting the app, you can validate the selected backend without opening +the browser or connecting to Reachy: + +```bash +reachy-mini-backend-check +python -m reachy_mini_conversation_app.backend_check +``` + +To validate a candidate dotenv file without replacing `.env`, pass it +explicitly: + +```bash +reachy-mini-backend-check --env-file .env.local-stt.example +``` -- `OpenAI Realtime`: Realtime microphone behavior. Audio streams to an -OpenAI-compatible Realtime endpoint, which handles transcription and response -generation in one session. -- `Riva STT`: microphone audio streams to Riva ASR. Final transcripts are sent -to the same text LLM path used by typed messages, so OpenAI-compatible Chat -Completions providers such as NVIDIA NIM can answer. -- `Text`: typed messages only. +Launch the app with that same candidate file, or with your edited private copy, +by setting `REACHY_MINI_DOTENV_PATH`: + +```bash +REACHY_MINI_DOTENV_PATH=.env.local-stt.example \ + python -m reachy_mini_conversation_app --gradio --no-camera +``` + +The preflight can also call configured backend endpoints: + +```bash +reachy-mini-backend-check --live +reachy-mini-backend-check --env-file .env.local-stt.example --live +``` -Tool calls are supported in text mode and in the Riva STT path; the app keeps -the tool schema attached on the post-tool follow-up request for providers that -require it. +For `BACKEND_PROVIDER=openai_realtime` and `BACKEND_PROVIDER=hf_realtime`, +`--live` opens a realtime session, sends the app's session configuration, and +then shuts the session down. For `BACKEND_PROVIDER=local_stt`, `--live` +defaults to the app-flow check: it feeds audio through the handler's microphone +receive path against fake Reachy dependencies, then verifies +`mic frame handling -> STT -> Chat Completions -> Reachy tools -> TTS`. + +Without `--audio-file`, the live check synthesizes a short seed phrase through +the configured TTS endpoint, sends that audio to STT, sends the transcript to +Chat Completions, then synthesizes the assistant response. It prints only +non-secret routing details, the transcript, response text, and audio durations. + +When setting up local STT services one at a time, use `--stage` to check only +the piece you have ready: + +```bash +reachy-mini-backend-check --env-file .env.local-stt.example --live --stage stt-probe +reachy-mini-backend-check --env-file .env.local-stt.example --live --stage stt \ + --audio-file ./sample-input.wav +reachy-mini-backend-check --env-file .env.local-stt.example --live --stage chat \ + --seed-text "Reachy, use the sweep_look tool, then tell me what you did." \ + --require-tool +reachy-mini-backend-check --env-file .env.local-stt.example --live --stage tts \ + --seed-text "Hello, I am Reachy." +reachy-mini-backend-check --env-file .env.local-stt.example --live --stage chain \ + --audio-file ./sample-input.wav +``` + +`--stage stt-probe` only needs `STT_*` values. It checks `/models` when that +endpoint is available, reports whether `STT_MODEL_NAME` is listed, then sends a +short synthetic WAV to `/audio/transcriptions`. It passes if the endpoint can +handle an audio request, even if the probe tone transcribes to empty text. +`--stage stt` checks actual transcription quality and only needs `STT_*` +values and an audio file unless TTS is already configured to synthesize the +seed phrase. `--stage chat` only needs `CHAT_*` values and can validate +model/tool compatibility before STT or TTS are ready. `--stage tts` only needs +`TTS_*` values. `--stage chain` checks the direct `STT -> Chat Completions -> +TTS` endpoint chain without the app handler or Reachy tool path. + +The app-flow path is the default local-STT live check, but you can name it +explicitly with `--stage app-flow` or its `--app-flow` shortcut: + +```bash +reachy-mini-backend-check --live --stage app-flow \ + --seed-text "Reachy, use the sweep_look tool, then tell me what you did." +reachy-mini-backend-check --live --app-flow --require-tool \ + --seed-text "Reachy, use the sweep_look tool, then tell me what you did." +``` + +When the simulator daemon or a physical Reachy Mini is already running, add +`--real-reachy` to use the real Reachy SDK client and movement manager instead +of fake tool dependencies: + +```bash +reachy-mini-backend-check --live --stage app-flow --require-tool --real-reachy \ + --seed-text "Reachy, use the sweep_look tool, then tell me what you did." +``` + +Use `--robot-name ` with `--real-reachy` if your daemon is advertised +under a non-default robot name. + +If your real STT endpoint is not online yet, run the local fake +OpenAI-compatible smoke workflow: + +```bash +scripts/smoke-local-stt.sh +scripts/smoke-local-stt.sh --real-reachy +scripts/smoke-local-stt.sh --gradio +``` + +The first command starts a fake STT/chat/TTS backend and checks the app handler +path against fake Reachy dependencies. The second also connects through the +Reachy SDK and movement manager, so it requires the simulator daemon or a +physical Reachy Mini to be running. The `--gradio` variant launches the actual +Gradio app, verifies the `Talk with Reachy Mini` UI, and sends a text tool-call +prompt through the running app process. It also requires a running daemon or +simulator. + +For manual debugging, you can run the fake backend directly: + +```bash +uv run python scripts/fake_openai_backend.py +``` + +Then point a disposable smoke config at it: + +```bash +cat > .env.smoke <<'EOF' +BACKEND_PROVIDER=local_stt +CHAT_API_KEY=not-needed +CHAT_BASE_URL=http://127.0.0.1:8766/v1 +CHAT_MODEL_NAME=fake-chat +STT_API_KEY=not-needed +STT_BASE_URL=http://127.0.0.1:8766/v1 +STT_MODEL_NAME=fake-whisper +TTS_API_KEY=not-needed +TTS_BASE_URL=http://127.0.0.1:8766/v1 +TTS_MODEL_NAME=fake-tts +TTS_VOICE=fake-voice +EOF + +reachy-mini-backend-check --env-file .env.smoke --live --stage app-flow --require-tool +reachy-mini-backend-check --env-file .env.smoke --live --stage app-flow --require-tool --real-reachy +``` + +This fake backend validates the app's OpenAI-compatible HTTP plumbing, tool +loop, and audio handoff. It does not validate STT accuracy, provider auth, or a +real model's tool-calling behavior. + +`--require-tool` applies to `--stage chat` and `--stage app-flow`; it fails if +the model does not call a Reachy tool. This is useful for checking model/tool +compatibility, but it still does not replace the final browser microphone and +simulator validation. + +The Gradio UI includes an `Input` selector. With `BACKEND_PROVIDER` set to +`openai_realtime` or `hf_realtime`, `Microphone` streams audio directly to the +selected realtime backend. With `BACKEND_PROVIDER=local_stt`, `Microphone` +sends each spoken phrase to the configured `STT_BASE_URL` transcription +endpoint, sends the transcript through Chat Completions, then synthesizes +Reachy's spoken reply through `TTS_BASE_URL`. Tool calls are supported in text +mode and in microphone-to-text mode; the app keeps the tool schema attached on +the post-tool follow-up request for providers that require it. + +If the microphone appears to connect but no transcript or model response +arrives, check the visible chat error and your `.env` values. For Chat +Completions models, verify that `STT_BASE_URL` points at an OpenAI-compatible +`/audio/transcriptions` service and that `STT_MODEL_NAME` matches the model +served by that endpoint. ## Runtime Flags @@ -300,9 +505,8 @@ uv run ty check ``` `ty` is the selected Python type checker for this project. The current copied -conversation-app baseline still reports diagnostics in motion, vision, optional -dependency, and SDK event typing, so use `uv run ty check` as the active audit -while that baseline is tightened. +conversation-app baseline is expected to pass `uv run ty check` before changes +are merged. Tests require the development dependency group: @@ -320,14 +524,31 @@ name to the app with `--robot-name`. If `--local-vision`, `--head-tracker yolo`, or `--head-tracker mediapipe` fails with an import error, install the matching optional dependency group. -If text mode returns `404 page not found`, check that `OPENAI_BASE_URL` matches -the provider's OpenAI-compatible endpoint and that `MODEL_NAME` is an exact -model ID from that provider. A catalog name, marketing page slug, or doubled -namespace may not be accepted by `/chat/completions`. +If `reachy-mini-backend-check` reports older config keys such as +`OPENAI_BASE_URL` or `MODEL_NAME`, replace that `.env` shape with one of the +current `BACKEND_PROVIDER` configurations. Those old keys are intentionally not +used. + +If text mode returns `404 page not found` with `BACKEND_PROVIDER=local_stt`, +check that `CHAT_BASE_URL` is a plain OpenAI-compatible endpoint string, such +as `https://inference-api.nvidia.com/v1`, and that `CHAT_MODEL_NAME` is an +exact model ID from that provider. A catalog name, marketing page slug, or +doubled namespace may not be accepted by `/chat/completions`. If text mode returns `401 Unauthorized` with NVIDIA endpoints, make sure -`OPENAI_API_KEY=${NVIDIA_API_KEY}` resolves to a key that is authorized for -generation, not only model listing. +`CHAT_API_KEY=${NVIDIA_INFERENCE_API_KEY}` resolves to a key that is authorized +for generation, not only model listing. + +If microphone-to-text returns a transcription error, make sure `STT_BASE_URL` +includes the `/v1` base path expected by OpenAI-compatible clients, for example +`http://:9000/v1`, and that the service exposes +`POST /audio/transcriptions` for the configured `STT_MODEL_NAME`. + +If a vLLM-hosted STT endpoint returns `Please install vllm[audio] for audio +support`, the service is reachable but was deployed without vLLM's audio +dependencies. Redeploy the local STT service with the audio extra enabled, then +rerun `reachy-mini-backend-check --live --stage stt-probe` followed by +`reachy-mini-backend-check --live --stage stt`. If `uv sync` tries to build `pygobject` or `pycairo` on macOS, the resolver is including a Linux media dependency path. This project scopes uv resolution to diff --git a/projects/reachy-mini-openshell/pyproject.toml b/projects/reachy-mini-openshell/pyproject.toml index 6c955849..8adb5cbb 100644 --- a/projects/reachy-mini-openshell/pyproject.toml +++ b/projects/reachy-mini-openshell/pyproject.toml @@ -28,19 +28,8 @@ dev = [ environments = [ "sys_platform == 'darwin'", ] -conflicts = [ - [ - { extra = "riva" }, - { extra = "mediapipe_vision" }, - ], - [ - { extra = "riva" }, - { extra = "all_vision" }, - ], -] [project.optional-dependencies] -riva = [ "nvidia-riva-client>=2.19,<3",] local_vision = [ "torch>=2.1", "transformers==5.0.0rc2", "num2words",] yolo_vision = [ "ultralytics", "supervision", "onnxruntime",] mediapipe_vision = [ "mediapipe==0.10.14",] @@ -48,6 +37,7 @@ all_vision = [ "torch>=2.1", "transformers==5.0.0rc2", "num2words", "ultralytics [project.scripts] reachy-mini-conversation-app = "reachy_mini_conversation_app.main:main" +reachy-mini-backend-check = "reachy_mini_conversation_app.backend_check:main" [tool.setuptools] include-package-data = true diff --git a/projects/reachy-mini-openshell/scripts/fake_openai_backend.py b/projects/reachy-mini-openshell/scripts/fake_openai_backend.py new file mode 100755 index 00000000..54f5f459 --- /dev/null +++ b/projects/reachy-mini-openshell/scripts/fake_openai_backend.py @@ -0,0 +1,149 @@ +#!/usr/bin/env python3 +"""Tiny OpenAI-compatible backend for local Reachy conversation smoke tests.""" + +import io +import math +import time +import wave +import argparse +from typing import Any + +import uvicorn +from fastapi import FastAPI, Request, Response + + +def _wav_bytes(text: str, *, sample_rate: int = 24_000, duration_seconds: float = 0.7) -> bytes: + """Return a small mono WAV payload.""" + frequency = 523.25 if "swept" in text.lower() else 440.0 + frame_count = max(1, int(sample_rate * duration_seconds)) + frames = bytearray() + for index in range(frame_count): + sample = int(math.sin(2 * math.pi * frequency * index / sample_rate) * 6000) + frames.extend(sample.to_bytes(2, byteorder="little", signed=True)) + + buffer = io.BytesIO() + with wave.open(buffer, "wb") as wav_file: + wav_file.setnchannels(1) + wav_file.setsampwidth(2) + wav_file.setframerate(sample_rate) + wav_file.writeframes(bytes(frames)) + return buffer.getvalue() + + +def _message_has_tool_result(messages: list[Any]) -> bool: + """Return whether a Chat Completions request includes a tool result.""" + return any(isinstance(message, dict) and message.get("role") == "tool" for message in messages) + + +def build_app( + *, + transcript: str, + assistant_text: str, + tool_name: str, + call_tool: bool, + audio_duration_seconds: float, +) -> FastAPI: + """Build the fake OpenAI-compatible FastAPI app.""" + app = FastAPI(title="Reachy fake OpenAI-compatible backend") + + @app.get("/v1/models") + async def models() -> dict[str, Any]: + return { + "object": "list", + "data": [ + {"id": "fake-whisper", "object": "model"}, + {"id": "fake-chat", "object": "model"}, + {"id": "fake-tts", "object": "model"}, + ], + } + + @app.post("/v1/audio/transcriptions") + async def transcriptions(request: Request) -> dict[str, str]: + await request.body() + return {"text": transcript} + + @app.post("/v1/audio/speech") + async def speech(request: Request) -> Response: + try: + payload = await request.json() + except Exception: + payload = {} + input_text = str(payload.get("input", "hello")) + return Response( + content=_wav_bytes(input_text, duration_seconds=audio_duration_seconds), + media_type="audio/wav", + ) + + @app.post("/v1/chat/completions") + async def chat_completions(request: Request) -> dict[str, Any]: + payload = await request.json() + messages = payload.get("messages", []) + if not isinstance(messages, list): + messages = [] + + if call_tool and not _message_has_tool_result(messages): + message = { + "role": "assistant", + "content": None, + "tool_calls": [ + { + "id": "call_fake_reachy_tool", + "type": "function", + "function": {"name": tool_name, "arguments": "{}"}, + } + ], + } + finish_reason = "tool_calls" + else: + message = {"role": "assistant", "content": assistant_text} + finish_reason = "stop" + + return { + "id": "chatcmpl-fake-reachy", + "object": "chat.completion", + "created": int(time.time()), + "model": payload.get("model", "fake-chat"), + "choices": [{"index": 0, "message": message, "finish_reason": finish_reason}], + } + + return app + + +def build_parser() -> argparse.ArgumentParser: + """Build CLI parser.""" + parser = argparse.ArgumentParser(description="Run a fake OpenAI-compatible backend for Reachy smoke tests.") + parser.add_argument("--host", default="127.0.0.1", help="host to bind.") + parser.add_argument("--port", type=int, default=8766, help="port to bind.") + parser.add_argument( + "--transcript", + default="Reachy, use the sweep_look tool, then tell me what you did.", + help="transcription text returned by POST /v1/audio/transcriptions.", + ) + parser.add_argument( + "--assistant-text", + default="I swept my gaze and returned to center.", + help="final assistant text returned after a tool result.", + ) + parser.add_argument("--tool-name", default="sweep_look", help="tool name to request from Chat Completions.") + parser.add_argument( + "--no-tool", action="store_true", help="return assistant text immediately without a tool call." + ) + parser.add_argument("--audio-duration", type=float, default=0.7, help="duration in seconds for fake TTS WAVs.") + return parser + + +def main() -> None: + """Run the fake backend.""" + args = build_parser().parse_args() + app = build_app( + transcript=args.transcript, + assistant_text=args.assistant_text, + tool_name=args.tool_name, + call_tool=not args.no_tool, + audio_duration_seconds=args.audio_duration, + ) + uvicorn.run(app, host=args.host, port=args.port, log_level="info") + + +if __name__ == "__main__": + main() diff --git a/projects/reachy-mini-openshell/scripts/smoke-local-stt.sh b/projects/reachy-mini-openshell/scripts/smoke-local-stt.sh new file mode 100755 index 00000000..cf278910 --- /dev/null +++ b/projects/reachy-mini-openshell/scripts/smoke-local-stt.sh @@ -0,0 +1,300 @@ +#!/usr/bin/env bash +set -euo pipefail + +SCRIPT_DIR="$(cd -- "$(dirname -- "${BASH_SOURCE[0]}")" && pwd)" +PROJECT_DIR="$(cd -- "${SCRIPT_DIR}/.." && pwd)" + +HOST="${SMOKE_BACKEND_HOST:-127.0.0.1}" +PORT="${SMOKE_BACKEND_PORT:-8766}" +REAL_REACHY="${SMOKE_REAL_REACHY:-0}" +GRADIO_SMOKE="${SMOKE_GRADIO:-0}" +APP_HOST="${SMOKE_APP_HOST:-127.0.0.1}" +APP_PORT="${SMOKE_APP_PORT:-7897}" +ROBOT_NAME="${SMOKE_ROBOT_NAME:-}" +SEED_TEXT="${SMOKE_SEED_TEXT:-Reachy, use the sweep_look tool, then tell me what you did.}" +STARTUP_TIMEOUT="${SMOKE_BACKEND_TIMEOUT:-10}" +APP_STARTUP_TIMEOUT="${SMOKE_APP_TIMEOUT:-20}" +SHUTDOWN_TIMEOUT="${SMOKE_SHUTDOWN_TIMEOUT:-25}" + +SERVER_PID="" +APP_PID="" +SMOKE_ENV="" + +usage() { + cat <<'EOF' +Usage: scripts/smoke-local-stt.sh [--real-reachy] [--gradio] [--robot-name NAME] + +Runs a local OpenAI-compatible fake STT/chat/TTS backend, writes a temporary +local_stt config, and checks the app's microphone app-flow path. + +Options: + --real-reachy Also run the app-flow check through the real Reachy SDK + and movement manager. Requires a running daemon/simulator. + --gradio Also launch the Gradio app, verify the UI labels, and send + a text tool-call prompt through the running app. Requires + a running daemon/simulator. + --robot-name NAME Robot name to pass to reachy-mini-backend-check with + --real-reachy and to the Gradio app smoke when provided. + -h, --help Show this help. + +Environment: + SMOKE_BACKEND_HOST Fake backend host. Default: 127.0.0.1 + SMOKE_BACKEND_PORT Fake backend port. Default: 8766 + SMOKE_APP_HOST Gradio app host for --gradio. Default: 127.0.0.1 + SMOKE_APP_PORT Gradio app port for --gradio. Default: 7897 + SMOKE_SEED_TEXT Seed text for the generated input speech. + SMOKE_BACKEND_TIMEOUT Seconds to wait for the fake backend. Default: 10 + SMOKE_APP_TIMEOUT Seconds to wait for the Gradio app. Default: 20 + SMOKE_SHUTDOWN_TIMEOUT Seconds to wait before forcing shutdown. Default: 25 +EOF +} + +log() { + printf '[reachy-smoke] %s\n' "$*" +} + +terminate_process_tree() { + local pid="$1" + local signal="$2" + local children child + + children="$(pgrep -P "${pid}" 2>/dev/null || true)" + for child in ${children}; do + terminate_process_tree "${child}" "${signal}" + done + kill "-${signal}" "${pid}" >/dev/null 2>&1 || true +} + +wait_for_process_exit() { + local pid="$1" + local timeout_seconds="$2" + local deadline=$((SECONDS + timeout_seconds)) + + while kill -0 "${pid}" >/dev/null 2>&1; do + if (( SECONDS >= deadline )); then + return 1 + fi + sleep 0.2 + done + return 0 +} + +stop_process_tree() { + local pid="$1" + local label="$2" + if [[ -z "${pid}" ]] || ! kill -0 "${pid}" >/dev/null 2>&1; then + return + fi + + terminate_process_tree "${pid}" INT + if ! wait_for_process_exit "${pid}" "${SHUTDOWN_TIMEOUT}"; then + log "Forcing ${label} shutdown" + terminate_process_tree "${pid}" TERM + if ! wait_for_process_exit "${pid}" 3; then + terminate_process_tree "${pid}" KILL + fi + fi + wait "${pid}" >/dev/null 2>&1 || true +} + +cleanup() { + stop_process_tree "${APP_PID}" "Gradio app" + stop_process_tree "${SERVER_PID}" "fake backend" + if [[ -n "${SMOKE_ENV}" ]]; then + rm -f "${SMOKE_ENV}" + fi +} +trap cleanup EXIT INT TERM + +while [[ $# -gt 0 ]]; do + case "$1" in + --real-reachy) + REAL_REACHY=1 + shift + ;; + --gradio) + GRADIO_SMOKE=1 + shift + ;; + --robot-name) + if [[ $# -lt 2 ]]; then + printf 'Missing value for --robot-name\n' >&2 + exit 2 + fi + ROBOT_NAME="$2" + shift 2 + ;; + -h|--help) + usage + exit 0 + ;; + *) + printf 'Unknown argument: %s\n' "$1" >&2 + usage >&2 + exit 2 + ;; + esac +done + +cd "${PROJECT_DIR}" + +if ! command -v uv >/dev/null 2>&1; then + printf 'Missing required command: uv\n' >&2 + exit 1 +fi + +ensure_url_ready() { + local url="$1" + local timeout_seconds="$2" + local label="$3" + + local deadline=$((SECONDS + timeout_seconds)) + until uv run python - "${url}" <<'PY' >/dev/null 2>&1 +import sys +import urllib.request + +url = sys.argv[1] +try: + with urllib.request.urlopen(url, timeout=0.5) as response: + raise SystemExit(0 if 200 <= response.status < 300 else 1) +except Exception: + raise SystemExit(1) +PY + do + if (( SECONDS >= deadline )); then + printf '%s did not become ready within %s seconds.\n' "${label}" "${timeout_seconds}" >&2 + exit 1 + fi + sleep 0.25 + done +} + +SMOKE_ENV="$(mktemp "${TMPDIR:-/tmp}/reachy-local-stt-smoke.XXXXXX")" +cat >"${SMOKE_ENV}" < MicPhraseResult: + """Add one audio frame and return a completed phrase when ready.""" + audio_frame = prepare_mono_int16_audio(frame, self.config.sample_rate) + if audio_frame.size == 0: + return MicPhraseResult(phrase_audio=None, saw_speech=False) + + frame_ms = len(audio_frame) * 1000.0 / self.config.sample_rate + is_speech = audio_rms(audio_frame) >= self.config.rms_threshold + + if is_speech: + self._has_speech = True + self._silence_ms = 0.0 + elif self._has_speech: + self._silence_ms += frame_ms + else: + return MicPhraseResult(phrase_audio=None, saw_speech=False) + + self._buffer.append(audio_frame) + self._buffer_ms += frame_ms + + should_flush = self._buffer_ms >= self.config.max_audio_ms or ( + self._buffer_ms >= self.config.min_audio_ms and self._silence_ms >= self.config.silence_ms + ) + if not should_flush: + return MicPhraseResult(phrase_audio=None, saw_speech=is_speech) + + return MicPhraseResult(phrase_audio=self.flush(), saw_speech=is_speech) + + def flush(self) -> NDArray[np.int16] | None: + """Return the buffered phrase and reset phrase-detection state.""" + if not self._buffer: + return None + + audio_frame = np.concatenate(self._buffer).astype(np.int16, copy=False) + self.reset() + return audio_frame + + def reset(self) -> None: + """Clear buffered audio and voice activity state.""" + self._buffer = [] + self._buffer_ms = 0.0 + self._silence_ms = 0.0 + self._has_speech = False diff --git a/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/audio/pcm.py b/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/audio/pcm.py new file mode 100644 index 00000000..84e35147 --- /dev/null +++ b/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/audio/pcm.py @@ -0,0 +1,141 @@ +"""PCM and WAV helpers shared by realtime and local-STT backends.""" + +import io +import wave +import asyncio +from typing import Any + +import numpy as np +from fastrtc import audio_to_int16 +from numpy.typing import NDArray +from scipy.signal import resample + + +def first_mono_channel(audio_frame: NDArray[Any]) -> NDArray[Any]: + """Return one mono channel from common FastRTC and scipy audio layouts.""" + if audio_frame.ndim == 1: + return audio_frame + + if audio_frame.ndim != 2: + raise ValueError(f"Expected 1D or 2D audio, got shape {audio_frame.shape}") + + rows, columns = audio_frame.shape + if rows == 1: + return audio_frame[0, :] + if columns == 1: + return audio_frame[:, 0] + if rows in {2, 6, 8} and columns > rows: + return audio_frame[0, :] + if columns in {2, 6, 8}: + return audio_frame[:, 0] + if rows < columns: + return audio_frame[0, :] + return audio_frame[:, 0] + + +def coerce_audio_to_int16(audio_frame: NDArray[Any]) -> NDArray[np.int16]: + """Convert supported PCM audio arrays to int16. + + FastRTC accepts normalized float32 audio, while scipy resampling returns + float64 values in the original PCM amplitude range. Preserve that scale + instead of multiplying resampled PCM by 32767 a second time. + """ + if audio_frame.dtype == np.int16: + return audio_frame + + if np.issubdtype(audio_frame.dtype, np.floating): + finite_audio = np.nan_to_num(audio_frame, nan=0.0, posinf=32767.0, neginf=-32768.0) + max_abs = float(np.max(np.abs(finite_audio))) if finite_audio.size else 0.0 + if max_abs <= 1.0: + return audio_to_int16(finite_audio.astype(np.float32, copy=False)) + return np.clip(finite_audio, -32768, 32767).astype(np.int16) + + if np.issubdtype(audio_frame.dtype, np.integer): + return np.clip(audio_frame, -32768, 32767).astype(np.int16) + + raise TypeError(f"Unsupported audio data type: {audio_frame.dtype}") + + +def prepare_mono_int16_audio( + frame: tuple[int, NDArray[Any]], + target_sample_rate: int, +) -> NDArray[np.int16]: + """Convert an incoming audio frame to mono int16 at the requested sample rate.""" + input_sample_rate, audio_frame = frame + mono_audio = first_mono_channel(audio_frame) + + if target_sample_rate != input_sample_rate and len(mono_audio) > 0: + mono_audio = resample(mono_audio, int(len(mono_audio) * target_sample_rate / input_sample_rate)) + + return coerce_audio_to_int16(mono_audio) + + +def audio_rms(audio_frame: NDArray[np.int16]) -> float: + """Return the RMS amplitude for a mono int16 audio frame.""" + if audio_frame.size == 0: + return 0.0 + samples = audio_frame.astype(np.float64) + return float(np.sqrt(np.mean(samples * samples))) + + +def wav_bytes(audio_frame: NDArray[np.int16], sample_rate: int) -> bytes: + """Encode mono int16 PCM audio as a WAV file.""" + buffer = io.BytesIO() + with wave.open(buffer, "wb") as wav_file: + wav_file.setnchannels(1) + wav_file.setsampwidth(2) + wav_file.setframerate(sample_rate) + wav_file.writeframes(audio_frame.tobytes()) + return buffer.getvalue() + + +def read_wav_audio(wav_payload: bytes) -> tuple[int, NDArray[np.int16]]: + """Decode a mono/stereo 16-bit WAV payload to mono int16 audio.""" + with wave.open(io.BytesIO(wav_payload), "rb") as wav_file: + channels = wav_file.getnchannels() + sample_width = wav_file.getsampwidth() + sample_rate = wav_file.getframerate() + frames = wav_file.readframes(wav_file.getnframes()) + + if sample_width != 2: + raise ValueError(f"Expected 16-bit WAV audio, got sample width {sample_width}") + + audio_frame = np.frombuffer(frames, dtype=np.int16) + if channels > 1: + audio_frame = audio_frame.reshape(-1, channels)[:, 0] + return sample_rate, audio_frame + + +def normalize_wav_bytes(wav_payload: bytes) -> bytes: + """Return a 16-bit mono WAV with concrete RIFF/data sizes.""" + sample_rate, audio_frame = read_wav_audio(wav_payload) + return wav_bytes(audio_frame, sample_rate) + + +def wav_duration_seconds(wav_payload: bytes) -> float: + """Return the duration of a WAV payload.""" + sample_rate, audio_frame = read_wav_audio(wav_payload) + return len(audio_frame) / float(sample_rate) if sample_rate else 0.0 + + +async def binary_response_bytes(response: Any) -> bytes: + """Read bytes from an OpenAI binary response object.""" + content = getattr(response, "content", None) + if isinstance(content, bytes): + return content + + read = getattr(response, "read", None) + if callable(read): + result = read() + if asyncio.iscoroutine(result): + result = await result + if isinstance(result, bytes): + return result + + aread = getattr(response, "aread", None) + if callable(aread): + result = await aread() + if isinstance(result, bytes): + return result + + raise TypeError(f"Unsupported binary response type: {type(response).__name__}") diff --git a/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/backend_check.py b/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/backend_check.py new file mode 100644 index 00000000..546a07d1 --- /dev/null +++ b/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/backend_check.py @@ -0,0 +1,786 @@ +"""Backend configuration and endpoint smoke checks for the conversation app.""" + +import asyncio +import argparse +from typing import Any, cast +from pathlib import Path + +import numpy as np +from openai import AsyncOpenAI +from numpy.typing import NDArray + +from reachy_mini_conversation_app.config import ( + config, + load_dotenv_file, + loaded_dotenv_keys, + loaded_dotenv_path, +) +from reachy_mini_conversation_app.audio.pcm import ( + wav_bytes, + read_wav_audio, + wav_duration_seconds, + prepare_mono_int16_audio, +) +from reachy_mini_conversation_app.backend_runtime import ( + selected_backend, + backend_config_error, + describe_selected_backend, + local_stt_tts_config_error, + local_stt_stage_config_error, +) +from reachy_mini_conversation_app.tools.core_tools import ToolDependencies +from reachy_mini_conversation_app.local_stt_backend import LocalSTTBackend +from reachy_mini_conversation_app.tools.background_tool_manager import BackgroundToolManager + + +def _required(value: str | None, name: str) -> str: + """Return a required string config value or raise a clear error.""" + if value and value.strip(): + return value.strip() + raise RuntimeError(f"{name} is required") + + +def _backend_config_hint(error: str) -> str | None: + """Return an actionable hint for common backend config errors.""" + if not error.startswith("BACKEND_PROVIDER is missing"): + return None + + keys = loaded_dotenv_keys() + legacy_keys = {"MODEL_NAME", "OPENAI_BASE_URL"} & keys + loaded_path = loaded_dotenv_path() + if legacy_keys: + legacy_list = ", ".join(sorted(legacy_keys)) + location = f" in {loaded_path}" if loaded_path else "" + return ( + f"Found older config keys{location}: {legacy_list}. They are no longer used. " + "Choose one BACKEND_PROVIDER and set the matching new keys: OPENAI_REALTIME_* for " + "openai_realtime, HF_REALTIME_* for hf_realtime, or CHAT_*/STT_*/TTS_* for local_stt." + ) + + if loaded_path is None: + return ( + "No .env file was loaded. Copy .env.example to .env, set BACKEND_PROVIDER to " + "openai_realtime, hf_realtime, or local_stt, or pass --env-file." + ) + + return ( + f"Loaded config from {loaded_path}. Set BACKEND_PROVIDER there to " + "openai_realtime, hf_realtime, or local_stt, or pass --env-file." + ) + + +def _wav_duration_seconds(wav_payload: bytes) -> float: + """Return the duration of a WAV payload.""" + return wav_duration_seconds(wav_payload) + + +def _audio_duration_seconds(sample_rate: int, audio_frame: NDArray[np.int16]) -> float: + """Return the duration of a mono/channel-first int16 frame.""" + if sample_rate <= 0: + return 0.0 + sample_count = audio_frame.shape[-1] if audio_frame.ndim > 1 else len(audio_frame) + return sample_count / float(sample_rate) + + +def _read_wav_audio(wav_payload: bytes) -> tuple[int, NDArray[np.int16]]: + """Decode a WAV payload into mono int16 audio.""" + return read_wav_audio(wav_payload) + + +def _audio_chunks( + audio_frame: NDArray[np.int16], sample_rate: int, *, chunk_ms: float = 100.0 +) -> list[NDArray[np.int16]]: + """Split audio into chunks that resemble browser microphone frames.""" + chunk_size = max(1, int(sample_rate * chunk_ms / 1000.0)) + return [audio_frame[start : start + chunk_size] for start in range(0, len(audio_frame), chunk_size)] + + +def _silence_frame(sample_rate: int, silence_ms: float) -> NDArray[np.int16]: + """Return a mono silence frame long enough to end the mic phrase.""" + sample_count = max(1, int(sample_rate * silence_ms / 1000.0)) + return np.zeros(sample_count, dtype=np.int16) + + +def _tone_wav_bytes() -> bytes: + """Return a tiny placeholder WAV when an endpoint needs valid audio bytes.""" + sample_rate = 16_000 + t = np.linspace(0, 0.25, int(sample_rate * 0.25), endpoint=False) + samples = (np.sin(2 * np.pi * 440 * t) * 2000).astype(np.int16) + return wav_bytes(samples, sample_rate) + + +def _speech_endpoint_error(component: str, context: str, endpoint_path: str, exc: Exception) -> str: + """Return a concise endpoint failure message without exposing secrets.""" + return ( + f"{component} endpoint request failed ({context}). Check the base URL and that the service exposes " + f"{endpoint_path}. {type(exc).__name__}: {exc}" + ) + + +def _model_ids(models_response: Any) -> list[str]: + """Extract model IDs from common OpenAI-compatible /models response shapes.""" + data = ( + models_response.get("data", []) if isinstance(models_response, dict) else getattr(models_response, "data", []) + ) + ids: list[str] = [] + for model in data or []: + model_id = model.get("id") if isinstance(model, dict) else getattr(model, "id", None) + if isinstance(model_id, str) and model_id.strip(): + ids.append(model_id.strip()) + return sorted(set(ids)) + + +def _format_model_ids(model_ids: list[str], *, limit: int = 5) -> str: + """Return a compact non-secret model list for diagnostics.""" + if not model_ids: + return "" + visible = model_ids[:limit] + suffix = f", ... (+{len(model_ids) - limit} more)" if len(model_ids) > limit else "" + return ", ".join(visible) + suffix + + +async def _stt_models_diagnostic_lines() -> list[str]: + """Return diagnostic lines for the STT /models endpoint when available.""" + _required(config.STT_MODEL_NAME, "STT_MODEL_NAME") + client = AsyncOpenAI( + api_key=(config.STT_API_KEY or "not-needed").strip() or "not-needed", + base_url=config.STT_BASE_URL, + ) + try: + models_response = await client.models.list() + except Exception as exc: + return [f"stt_models_endpoint=unavailable ({type(exc).__name__}: {exc})"] + + ids = _model_ids(models_response) + model_listed = config.STT_MODEL_NAME in ids + return [ + "stt_models_endpoint=reachable", + f"stt_model_listed={'yes' if model_listed else 'no'}", + f"stt_available_models={_format_model_ids(ids)}", + ] + + +def _build_fake_local_stt_backend() -> tuple[LocalSTTBackend, BackgroundToolManager, Any]: + """Build local-STT backend dependencies for CLI smoke checks.""" + movement_manager = _FakeMovementManager() + deps = ToolDependencies( + reachy_mini=cast(Any, _FakeReachyMini()), + movement_manager=movement_manager, + ) + tool_manager = BackgroundToolManager() + return ( + LocalSTTBackend( + deps=deps, + tool_manager=tool_manager, + client_factory=AsyncOpenAI, + ), + tool_manager, + movement_manager, + ) + + +def _chat_summary_from_messages(messages: list[dict[str, Any]], *, require_tool: bool) -> tuple[str, list[str]]: + """Return final assistant text and tool result titles from chatbot messages.""" + assistant_text = "" + tool_titles: list[str] = [] + + for message in messages: + content = message.get("content") + if message.get("role") != "assistant" or not isinstance(content, str): + continue + metadata = message.get("metadata") + if isinstance(metadata, dict) and isinstance(metadata.get("title"), str): + tool_titles.append(metadata["title"]) + elif content.startswith("[error]"): + raise RuntimeError(content) + else: + assistant_text = content + + if not assistant_text: + raise RuntimeError("Chat endpoint returned no final assistant response") + if require_tool and not tool_titles: + raise RuntimeError("Chat check did not execute a Reachy tool") + + return assistant_text, tool_titles + + +async def live_realtime_session_check() -> list[str]: + """Exercise the selected realtime backend's session startup path.""" + from reachy_mini_conversation_app.tools.core_tools import ToolDependencies + from reachy_mini_conversation_app.conversation_stream import ConversationStreamHandler + + movement_manager = _FakeMovementManager() + deps = ToolDependencies( + reachy_mini=cast(Any, _FakeReachyMini()), + movement_manager=movement_manager, + ) + handler = ConversationStreamHandler(deps) + + try: + backend = selected_backend() + connected = await handler._ensure_realtime_session("backend-check-realtime-session") + if not connected: + startup_error = getattr(handler, "_startup_error", None) + raise RuntimeError(startup_error or "Realtime session did not connect before the startup timeout") + + return [ + "realtime_session=connected", + f"realtime_model={backend.realtime_model or ''}", + f"realtime_voice={backend.realtime_voice or ''}", + ] + finally: + await handler.shutdown() + startup_task = getattr(handler, "_realtime_startup_task", None) + if startup_task is not None: + try: + await asyncio.wait_for(startup_task, timeout=2.0) + except asyncio.TimeoutError: + startup_task.cancel() + try: + await startup_task + except asyncio.CancelledError: + pass + + +def _stage_name(args: argparse.Namespace) -> str: + """Return the selected live-check stage, preserving --app-flow as a shortcut.""" + stage = getattr(args, "stage", None) + if stage: + return str(stage) + if getattr(args, "app_flow", False): + return "app-flow" + if getattr(args, "live", False) and selected_backend().uses_local_stt: + return "app-flow" + return "chain" + + +def _require_tool_usage_error(args: argparse.Namespace, stage: str) -> str | None: + """Return an error when --require-tool would otherwise be ignored.""" + if not getattr(args, "require_tool", False): + return None + if not getattr(args, "live", False): + return "--require-tool only applies when --live is set." + if not selected_backend().uses_local_stt: + return "--require-tool is only supported for BACKEND_PROVIDER=local_stt --stage chat or --stage app-flow." + if stage not in {"chat", "app-flow"}: + return "--require-tool only applies to --stage chat or --stage app-flow." + return None + + +def _real_reachy_usage_error(args: argparse.Namespace, stage: str) -> str | None: + """Return an error when --real-reachy would otherwise be ignored.""" + if not getattr(args, "real_reachy", False): + return None + if not getattr(args, "live", False) or not selected_backend().uses_local_stt or stage != "app-flow": + return "--real-reachy only applies to BACKEND_PROVIDER=local_stt with --live --stage app-flow." + return None + + +async def _synthesize_input_audio(seed_text: str) -> bytes: + """Use the configured TTS endpoint to generate a speech sample for STT.""" + _required(config.TTS_MODEL_NAME, "TTS_MODEL_NAME") + _required(config.TTS_VOICE, "TTS_VOICE") + backend, tool_manager, _movement_manager = _build_fake_local_stt_backend() + try: + try: + return await backend.synthesize_speech_wav_bytes(seed_text) + except Exception as exc: + raise RuntimeError(_speech_endpoint_error("TTS", backend.tts_context, "POST /audio/speech", exc)) from exc + finally: + await tool_manager.shutdown() + + +async def live_local_stt_probe_check() -> list[str]: + """Probe the local_stt STT endpoint with synthetic audio without requiring recognized text.""" + _required(config.STT_MODEL_NAME, "STT_MODEL_NAME") + model_lines = await _stt_models_diagnostic_lines() + if "stt_model_listed=no" in model_lines: + raise RuntimeError("; ".join(model_lines)) + + input_audio = _tone_wav_bytes() + backend, tool_manager, _movement_manager = _build_fake_local_stt_backend() + try: + try: + transcript = await backend.transcribe_wav_bytes( + input_audio, + filename="backend-check-probe.wav", + ) + except Exception as exc: + raise RuntimeError( + "; ".join( + [ + *model_lines, + _speech_endpoint_error("STT", backend.stt_context, "POST /audio/transcriptions", exc), + ] + ) + ) from exc + finally: + await tool_manager.shutdown() + + return [ + *model_lines, + "input_audio=synthetic probe tone", + f"input_audio_duration={_wav_duration_seconds(input_audio):.2f}s", + "stt_endpoint=reachable", + f"transcript={transcript or ''}", + ] + + +async def live_local_stt_transcription_check(seed_text: str, audio_file: Path | None) -> list[str]: + """Exercise only the local_stt STT endpoint.""" + if audio_file is not None: + input_audio = audio_file.read_bytes() + input_label = str(audio_file) + else: + tts_error = local_stt_tts_config_error() + if tts_error: + raise RuntimeError("--stage stt requires --audio-file unless TTS is configured to synthesize seed audio") + input_audio = await _synthesize_input_audio(seed_text) + input_label = "configured TTS seed" + + _required(config.STT_MODEL_NAME, "STT_MODEL_NAME") + backend, tool_manager, _movement_manager = _build_fake_local_stt_backend() + try: + try: + transcript = await backend.transcribe_wav_bytes( + input_audio or _tone_wav_bytes(), + filename="backend-check.wav", + ) + except Exception as exc: + raise RuntimeError( + _speech_endpoint_error("STT", backend.stt_context, "POST /audio/transcriptions", exc) + ) from exc + finally: + await tool_manager.shutdown() + if not transcript: + raise RuntimeError("STT endpoint returned an empty transcript") + + return [ + f"input_audio={input_label}", + f"input_audio_duration={_wav_duration_seconds(input_audio):.2f}s", + f"transcript={transcript}", + ] + + +async def live_local_stt_chat_check(seed_text: str, *, require_tool: bool) -> list[str]: + """Exercise only the local_stt Chat Completions and Reachy tool path.""" + backend, tool_manager, movement_manager = _build_fake_local_stt_backend() + try: + _required(config.CHAT_MODEL_NAME, "CHAT_MODEL_NAME") + messages = await backend.send_text_message(seed_text) + assistant_text, tool_titles = _chat_summary_from_messages(messages, require_tool=require_tool) + finally: + await tool_manager.shutdown() + + return [ + f"seed_text={seed_text}", + f"assistant_text={assistant_text}", + f"tool_results={', '.join(tool_titles) if tool_titles else ''}", + f"queued_moves={len(movement_manager.queued_moves)}", + ] + + +async def live_local_stt_tts_check(seed_text: str) -> list[str]: + """Exercise only the local_stt TTS endpoint.""" + output_audio = await _synthesize_input_audio(seed_text) + return [ + f"seed_text={seed_text}", + f"output_audio_duration={_wav_duration_seconds(output_audio):.2f}s", + ] + + +async def live_local_stt_check(seed_text: str, audio_file: Path | None) -> list[str]: + """Exercise local_stt endpoints without connecting to a Reachy daemon.""" + if audio_file is not None: + input_audio = audio_file.read_bytes() + input_label = str(audio_file) + else: + input_audio = await _synthesize_input_audio(seed_text) + input_label = "configured TTS seed" + + _required(config.STT_MODEL_NAME, "STT_MODEL_NAME") + backend, tool_manager, _movement_manager = _build_fake_local_stt_backend() + try: + try: + transcript = await backend.transcribe_wav_bytes( + input_audio or _tone_wav_bytes(), + filename="backend-check.wav", + ) + except Exception as exc: + raise RuntimeError( + _speech_endpoint_error("STT", backend.stt_context, "POST /audio/transcriptions", exc) + ) from exc + if not transcript: + raise RuntimeError("STT endpoint returned an empty transcript") + + _required(config.CHAT_MODEL_NAME, "CHAT_MODEL_NAME") + messages = await backend.send_text_message(transcript) + assistant_text, _tool_titles = _chat_summary_from_messages(messages, require_tool=False) + output_audio = await backend.synthesize_speech_wav_bytes(assistant_text) + finally: + await tool_manager.shutdown() + + return [ + f"input_audio={input_label}", + f"input_audio_duration={_wav_duration_seconds(input_audio):.2f}s", + f"transcript={transcript}", + f"assistant_text={assistant_text}", + f"output_audio_duration={_wav_duration_seconds(output_audio):.2f}s", + ] + + +class _FakeReachyMini: + """Small Reachy stand-in for app-flow backend checks.""" + + def get_current_head_pose(self) -> NDArray[np.float64]: + return np.eye(4, dtype=np.float64) + + def get_current_joint_positions(self) -> tuple[NDArray[np.float64], NDArray[np.float64]]: + return np.array([0.0], dtype=np.float64), np.array([0.0, 0.0], dtype=np.float64) + + +class _FakeMovementManager: + """Movement manager stand-in that records queued Reachy moves.""" + + def __init__(self) -> None: + self.queued_moves: list[Any] = [] + self.clear_count = 0 + self.moving_state_durations: list[float] = [] + + def clear_move_queue(self) -> None: + self.clear_count += 1 + self.queued_moves.clear() + + def queue_move(self, move: Any) -> None: + self.queued_moves.append(move) + + def set_moving_state(self, duration: float) -> None: + self.moving_state_durations.append(duration) + + def is_idle(self) -> bool: + return True + + +class _AppFlowDeps: + """Dependencies and cleanup hooks for app-flow checks.""" + + def __init__(self, reachy_mini: Any, movement_manager: Any, *, real_reachy: bool = False): + self.reachy_mini = reachy_mini + self.movement_manager = movement_manager + self.real_reachy = real_reachy + + def start(self) -> None: + if self.real_reachy: + self.movement_manager.start() + + def movement_summary_lines(self) -> list[str]: + if not self.real_reachy: + return [f"queued_moves={len(self.movement_manager.queued_moves)}"] + + status = self.movement_manager.get_status() + loop_frequency = status.get("loop_frequency", {}) if isinstance(status, dict) else {} + return [ + "movement_manager=real", + f"movement_queue_size={status.get('queue_size', '') if isinstance(status, dict) else ''}", + f"movement_loop_samples={loop_frequency.get('samples', '')}", + ] + + def stop(self) -> None: + if self.real_reachy: + self.movement_manager.stop() + try: + self.reachy_mini.client.disconnect() + except Exception: + pass + + +def _build_app_flow_deps(*, real_reachy: bool, robot_name: str | None) -> _AppFlowDeps: + """Build fake or real Reachy dependencies for app-flow checks.""" + if not real_reachy: + movement_manager = _FakeMovementManager() + return _AppFlowDeps( + reachy_mini=cast(Any, _FakeReachyMini()), + movement_manager=movement_manager, + real_reachy=False, + ) + + from reachy_mini import ReachyMini + from reachy_mini_conversation_app.moves import MovementManager + + robot_kwargs = {"robot_name": robot_name} if robot_name else {} + reachy_mini = ReachyMini(**robot_kwargs) + movement_manager = MovementManager(current_robot=reachy_mini) + return _AppFlowDeps(reachy_mini=reachy_mini, movement_manager=movement_manager, real_reachy=True) + + +async def live_local_stt_app_flow_check( + seed_text: str, + audio_file: Path | None, + *, + require_tool: bool, + real_reachy: bool = False, + robot_name: str | None = None, +) -> list[str]: + """Exercise the app handler's mic -> local_stt STT -> chat/tools -> TTS flow.""" + from reachy_mini_conversation_app.tools.core_tools import ToolDependencies + from reachy_mini_conversation_app.conversation_stream import ( + MIC_TRANSCRIPTION_SAMPLE_RATE, + ConversationStreamHandler, + ) + + if audio_file is not None: + input_audio = audio_file.read_bytes() + input_label = str(audio_file) + else: + input_audio = await _synthesize_input_audio(seed_text) + input_label = "configured TTS seed" + + sample_rate, input_frame = _read_wav_audio(input_audio or _tone_wav_bytes()) + prepared_frame = prepare_mono_int16_audio( + (sample_rate, input_frame), + MIC_TRANSCRIPTION_SAMPLE_RATE, + ) + + app_flow_deps = _build_app_flow_deps(real_reachy=real_reachy, robot_name=robot_name) + app_flow_deps.start() + deps = ToolDependencies(reachy_mini=app_flow_deps.reachy_mini, movement_manager=app_flow_deps.movement_manager) + handler = ConversationStreamHandler(deps) + + transcript = "" + assistant_text = "" + tool_titles: list[str] = [] + error_messages: list[str] = [] + output_audio_duration = 0.0 + try: + for chunk in _audio_chunks(prepared_frame, MIC_TRANSCRIPTION_SAMPLE_RATE): + await handler.receive((MIC_TRANSCRIPTION_SAMPLE_RATE, chunk)) + + silence_ms = max(config.MIC_TRANSCRIPTION_SILENCE_MS + 50.0, 1.0) + await handler.receive( + (MIC_TRANSCRIPTION_SAMPLE_RATE, _silence_frame(MIC_TRANSCRIPTION_SAMPLE_RATE, silence_ms)) + ) + + await _wait_for_app_flow_mic_tasks(handler) + + while not handler.output_queue.empty(): + output = handler.output_queue.get_nowait() + if isinstance(output, tuple): + output_sample_rate, audio_frame = output + if isinstance(output_sample_rate, int) and isinstance(audio_frame, np.ndarray): + output_audio_duration += _audio_duration_seconds( + output_sample_rate, + cast(NDArray[np.int16], np.asarray(audio_frame, dtype=np.int16)), + ) + continue + + for message in getattr(output, "args", ()): + if not isinstance(message, dict): + continue + content = message.get("content") + if message.get("role") == "user" and isinstance(content, str): + transcript = content + elif message.get("role") == "assistant" and isinstance(content, str): + metadata = message.get("metadata") + if isinstance(metadata, dict) and isinstance(metadata.get("title"), str): + tool_titles.append(metadata["title"]) + if real_reachy: + await asyncio.sleep(0.2) + elif content.startswith("[error]"): + error_messages.append(content) + elif not content.startswith("[error]"): + assistant_text = content + finally: + await handler.shutdown() + app_flow_deps.stop() + + if error_messages: + raise RuntimeError("; ".join(error_messages)) + if not transcript: + raise RuntimeError("App-flow check did not produce a transcript") + if not assistant_text: + raise RuntimeError("App-flow check did not produce a final assistant response") + if output_audio_duration <= 0: + raise RuntimeError("App-flow check did not produce synthesized audio") + if require_tool and not tool_titles: + raise RuntimeError("App-flow check did not execute a Reachy tool") + + return [ + f"input_audio={input_label}", + f"input_audio_duration={_wav_duration_seconds(input_audio):.2f}s", + f"transcript={transcript}", + f"assistant_text={assistant_text}", + f"tool_results={', '.join(tool_titles) if tool_titles else ''}", + *app_flow_deps.movement_summary_lines(), + f"output_audio_duration={output_audio_duration:.2f}s", + ] + + +async def _wait_for_app_flow_mic_tasks(handler: Any) -> None: + """Wait for the handler's microphone transcription task to finish.""" + for _ in range(50): + tasks = list(getattr(handler, "_mic_transcription_tasks", ())) + if tasks: + await asyncio.gather(*tasks) + return + if not handler.output_queue.empty(): + return + await asyncio.sleep(0.05) + + raise RuntimeError("App-flow check did not flush microphone audio through the receive path") + + +async def run_check(args: argparse.Namespace) -> int: + """Run the selected backend check.""" + env_file = getattr(args, "env_file", None) + if env_file is not None and not load_dotenv_file(env_file): + print(f"[error] Could not load env file: {env_file}") + return 2 + + stage = _stage_name(args) + + for line in describe_selected_backend(): + print(line) + + error = ( + local_stt_stage_config_error(stage) + if getattr(args, "live", False) and selected_backend().uses_local_stt + else backend_config_error() + ) + if error: + print(f"[error] {error}") + hint = _backend_config_hint(error) + if hint: + print(f"[hint] {hint}") + return 2 + + require_tool_error = _require_tool_usage_error(args, stage) + if require_tool_error: + print(f"[error] {require_tool_error}") + return 2 + + real_reachy_error = _real_reachy_usage_error(args, stage) + if real_reachy_error: + print(f"[error] {real_reachy_error}") + return 2 + + print( + f"[ok] local_stt {stage} config is valid" + if getattr(args, "live", False) and selected_backend().uses_local_stt + else "[ok] backend config is valid" + ) + + if not args.live: + return 0 + + backend = selected_backend() + if not backend.uses_local_stt: + if not backend.uses_realtime: + print("[error] --live supports realtime backends and BACKEND_PROVIDER=local_stt") + return 2 + + try: + results = await live_realtime_session_check() + except Exception as e: + print(f"[error] realtime live session check failed: {type(e).__name__}: {e}") + return 1 + + for line in results: + print(line) + print("[ok] realtime live session check completed") + return 0 + + try: + if stage == "stt-probe": + results = await live_local_stt_probe_check() + elif stage == "stt": + results = await live_local_stt_transcription_check(args.seed_text, args.audio_file) + elif stage == "chat": + results = await live_local_stt_chat_check( + args.seed_text, + require_tool=getattr(args, "require_tool", False), + ) + elif stage == "tts": + results = await live_local_stt_tts_check(args.seed_text) + elif stage == "app-flow": + results = await live_local_stt_app_flow_check( + args.seed_text, + args.audio_file, + require_tool=getattr(args, "require_tool", False), + real_reachy=getattr(args, "real_reachy", False), + robot_name=getattr(args, "robot_name", None), + ) + else: + results = await live_local_stt_check(args.seed_text, args.audio_file) + except Exception as e: + print(f"[error] local_stt live {stage} check failed: {type(e).__name__}: {e}") + return 1 + + for line in results: + print(line) + print(f"[ok] local_stt live {stage} check completed") + return 0 + + +def build_parser() -> argparse.ArgumentParser: + """Build the backend check argument parser.""" + parser = argparse.ArgumentParser(description="Validate Reachy conversation backend configuration.") + parser.add_argument( + "--live", + action="store_true", + help="call configured endpoints. Realtime backends validate session startup; local_stt can validate each stage.", + ) + parser.add_argument( + "--seed-text", + default="Hi Reachy, please introduce yourself in one short sentence.", + help="text to synthesize as the input speech sample when --live is used without --audio-file.", + ) + parser.add_argument( + "--audio-file", + type=Path, + help="WAV or provider-supported audio file to send to STT instead of synthesizing seed text.", + ) + parser.add_argument( + "--stage", + choices=["stt-probe", "stt", "chat", "tts", "chain", "app-flow"], + default=None, + help=( + "with --live and BACKEND_PROVIDER=local_stt, check one stage. " + "Defaults to app-flow for local_stt live checks and is ignored by realtime backends." + ), + ) + parser.add_argument( + "--env-file", + type=Path, + help="load this dotenv file for backend validation instead of the default .env search.", + ) + parser.add_argument( + "--app-flow", + action="store_true", + help="shortcut for --stage app-flow.", + ) + parser.add_argument( + "--require-tool", + action="store_true", + help="with --live --stage chat or --live --stage app-flow, fail unless the model executes a Reachy tool.", + ) + parser.add_argument( + "--real-reachy", + action="store_true", + help="with --live --stage app-flow, use the real Reachy SDK/daemon instead of fake tool dependencies.", + ) + parser.add_argument( + "--robot-name", + help="optional Reachy daemon robot name/prefix, used with --real-reachy.", + ) + return parser + + +def main() -> None: + """CLI entry point.""" + parser = build_parser() + args = parser.parse_args() + raise SystemExit(asyncio.run(run_check(args))) + + +if __name__ == "__main__": + main() diff --git a/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/backend_runtime.py b/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/backend_runtime.py new file mode 100644 index 00000000..f94f3c9f --- /dev/null +++ b/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/backend_runtime.py @@ -0,0 +1,209 @@ +from typing import Final, Literal +from dataclasses import dataclass + +from reachy_mini_conversation_app.config import ( + BACKEND_LOCAL_STT, + BACKEND_PROVIDERS, + BACKEND_HF_REALTIME, + BACKEND_OPENAI_REALTIME, + HF_REALTIME_CONNECTION_LOCAL, + config, + is_configured_value, + openai_realtime_api_key, +) + + +OPENAI_COMPATIBLE_STREAM_SAMPLE_RATE: Final[int] = 24_000 +HF_REALTIME_STREAM_SAMPLE_RATE: Final[int] = 16_000 + +BackendTransport = Literal["realtime", "local_stt", "unknown"] + + +@dataclass(frozen=True) +class BackendRuntimeSpec: + """Runtime traits derived from the single BACKEND_PROVIDER selector.""" + + provider: str + transport: BackendTransport + stream_sample_rate: int + realtime_model: str = "" + realtime_voice: str = "" + refresh_realtime_client_on_retry: bool = False + + @property + def uses_realtime(self) -> bool: + """Return whether microphone/text input should use a realtime websocket.""" + return self.transport == "realtime" + + @property + def uses_local_stt(self) -> bool: + """Return whether microphone input should use STT plus Chat Completions.""" + return self.transport == "local_stt" + + +def selected_backend() -> BackendRuntimeSpec: + """Return the runtime backend selected by BACKEND_PROVIDER.""" + provider = config.BACKEND_PROVIDER + if provider == BACKEND_OPENAI_REALTIME: + return BackendRuntimeSpec( + provider=provider, + transport="realtime", + stream_sample_rate=OPENAI_COMPATIBLE_STREAM_SAMPLE_RATE, + realtime_model=config.OPENAI_REALTIME_MODEL or "", + realtime_voice=config.OPENAI_REALTIME_VOICE or "", + refresh_realtime_client_on_retry=False, + ) + + if provider == BACKEND_HF_REALTIME: + return BackendRuntimeSpec( + provider=provider, + transport="realtime", + stream_sample_rate=HF_REALTIME_STREAM_SAMPLE_RATE, + realtime_model=(config.HF_REALTIME_MODEL or "").strip(), + realtime_voice=config.HF_REALTIME_VOICE or "", + refresh_realtime_client_on_retry=True, + ) + + if provider == BACKEND_LOCAL_STT: + return BackendRuntimeSpec( + provider=provider, + transport="local_stt", + stream_sample_rate=OPENAI_COMPATIBLE_STREAM_SAMPLE_RATE, + ) + + return BackendRuntimeSpec( + provider=provider, + transport="unknown", + stream_sample_rate=OPENAI_COMPATIBLE_STREAM_SAMPLE_RATE, + ) + + +def configured_marker(value: str | None) -> str: + """Return a display-safe configured/missing marker.""" + return "configured" if is_configured_value(value) else "missing" + + +def local_stt_chat_config_error() -> str | None: + """Return a config error for the local-STT Chat Completions component.""" + if not is_configured_value(config.CHAT_API_KEY): + return ( + "CHAT_API_KEY is missing for BACKEND_PROVIDER=local_stt. If .env uses " + "CHAT_API_KEY=${NVIDIA_INFERENCE_API_KEY}, make sure NVIDIA_INFERENCE_API_KEY is exported " + "in the shell that starts the app." + ) + if not is_configured_value(config.CHAT_BASE_URL): + return "CHAT_BASE_URL is missing for BACKEND_PROVIDER=local_stt." + if not is_configured_value(config.CHAT_MODEL_NAME): + return "CHAT_MODEL_NAME is missing for BACKEND_PROVIDER=local_stt." + return None + + +def local_stt_transcription_config_error() -> str | None: + """Return a config error for the local-STT speech-to-text component.""" + if not is_configured_value(config.STT_API_KEY): + return "STT_API_KEY is missing for BACKEND_PROVIDER=local_stt." + if not is_configured_value(config.STT_BASE_URL): + return "STT_BASE_URL is missing for BACKEND_PROVIDER=local_stt." + if not is_configured_value(config.STT_MODEL_NAME): + return "STT_MODEL_NAME is missing for BACKEND_PROVIDER=local_stt." + return None + + +def local_stt_tts_config_error() -> str | None: + """Return a config error for the local-STT text-to-speech component.""" + if not is_configured_value(config.TTS_API_KEY): + return "TTS_API_KEY is missing for BACKEND_PROVIDER=local_stt." + if not is_configured_value(config.TTS_BASE_URL): + return "TTS_BASE_URL is missing for BACKEND_PROVIDER=local_stt." + if not is_configured_value(config.TTS_MODEL_NAME): + return "TTS_MODEL_NAME is missing for BACKEND_PROVIDER=local_stt." + return None + + +def backend_config_error() -> str | None: + """Return a startup-blocking config error for the selected backend, if any.""" + backend = selected_backend() + expected = ", ".join(sorted(BACKEND_PROVIDERS)) + if not is_configured_value(backend.provider): + return f"BACKEND_PROVIDER is missing; set it to one of {expected}." + + if backend.provider not in BACKEND_PROVIDERS: + return f"Unknown BACKEND_PROVIDER={backend.provider!r}; expected one of {expected}." + + if backend.provider == BACKEND_OPENAI_REALTIME: + if openai_realtime_api_key() is None: + return ( + "OPENAI_API_KEY is missing for BACKEND_PROVIDER=openai_realtime. " + "Export OPENAI_API_KEY in the shell that starts the app; set OPENAI_REALTIME_API_KEY " + "only if this app needs a different OpenAI key." + ) + if not is_configured_value(config.OPENAI_REALTIME_BASE_URL): + return "OPENAI_REALTIME_BASE_URL is missing for BACKEND_PROVIDER=openai_realtime." + if not is_configured_value(backend.realtime_model): + return "OPENAI_REALTIME_MODEL is missing for BACKEND_PROVIDER=openai_realtime." + return None + + if backend.provider == BACKEND_HF_REALTIME: + if config.HF_REALTIME_CONNECTION_MODE == HF_REALTIME_CONNECTION_LOCAL and not is_configured_value( + config.HF_REALTIME_WS_URL + ): + return "HF_REALTIME_WS_URL is missing for HF_REALTIME_CONNECTION_MODE=local." + return None + + if backend.provider == BACKEND_LOCAL_STT: + return local_stt_chat_config_error() or local_stt_transcription_config_error() or local_stt_tts_config_error() + + return None + + +def local_stt_stage_config_error(stage: str) -> str | None: + """Return the config error relevant to a local_stt live-check stage.""" + if stage in {"stt", "stt-probe"}: + return local_stt_transcription_config_error() + if stage == "chat": + return local_stt_chat_config_error() + if stage == "tts": + return local_stt_tts_config_error() + return backend_config_error() + + +def describe_selected_backend() -> list[str]: + """Return a non-secret summary of the selected backend configuration.""" + backend = selected_backend() + lines = [f"backend={backend.provider}"] + if backend.provider == BACKEND_OPENAI_REALTIME: + lines.extend( + [ + f"openai_realtime.base_url={config.OPENAI_REALTIME_BASE_URL}", + f"openai_realtime.model={backend.realtime_model}", + f"openai_realtime.voice={backend.realtime_voice}", + f"openai_realtime.api_key={configured_marker(openai_realtime_api_key())}", + ] + ) + elif backend.provider == BACKEND_HF_REALTIME: + lines.extend( + [ + f"hf_realtime.connection_mode={config.HF_REALTIME_CONNECTION_MODE}", + f"hf_realtime.session_url={config.HF_REALTIME_SESSION_URL}", + f"hf_realtime.ws_url={config.HF_REALTIME_WS_URL or ''}", + f"hf_realtime.model={backend.realtime_model or ''}", + f"hf_realtime.voice={backend.realtime_voice}", + f"hf_realtime.token={configured_marker(config.HF_TOKEN)}", + ] + ) + elif backend.provider == BACKEND_LOCAL_STT: + lines.extend( + [ + f"chat.base_url={config.CHAT_BASE_URL}", + f"chat.model={config.CHAT_MODEL_NAME}", + f"chat.api_key={configured_marker(config.CHAT_API_KEY)}", + f"stt.base_url={config.STT_BASE_URL}", + f"stt.model={config.STT_MODEL_NAME}", + f"stt.api_key={configured_marker(config.STT_API_KEY)}", + f"tts.base_url={config.TTS_BASE_URL}", + f"tts.model={config.TTS_MODEL_NAME}", + f"tts.voice={config.TTS_VOICE}", + f"tts.api_key={configured_marker(config.TTS_API_KEY)}", + ] + ) + return lines diff --git a/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/camera_worker.py b/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/camera_worker.py index e625c009..046bd8db 100644 --- a/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/camera_worker.py +++ b/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/camera_worker.py @@ -51,7 +51,7 @@ def __init__(self, reachy_mini: ReachyMini, head_tracker: Any = None) -> None: # Face tracking timing variables (same as main_works.py) self.last_face_detected_time: float | None = None self.interpolation_start_time: float | None = None - self.interpolation_start_pose: NDArray[np.float32] | None = None + self.interpolation_start_pose: NDArray[np.float64] | None = None self.face_lost_delay = 2.0 # seconds to wait before starting interpolation self.interpolation_duration = 1.0 # seconds to interpolate back to neutral @@ -102,7 +102,7 @@ def working_loop(self) -> None: logger.debug("Starting camera working loop") # Initialize head tracker if available - neutral_pose = np.eye(4) # Neutral pose (identity matrix) + neutral_pose = np.eye(4, dtype=np.float64) # Neutral pose (identity matrix) self.previous_head_tracking_state = self.is_head_tracking_enabled while not self._stop_event.is_set(): @@ -190,7 +190,7 @@ def working_loop(self) -> None: current_translation = self.face_tracking_offsets[:3] current_rotation_euler = self.face_tracking_offsets[3:] # Convert to 4x4 pose matrix - pose_matrix = np.eye(4, dtype=np.float32) + pose_matrix = np.eye(4, dtype=np.float64) pose_matrix[:3, 3] = current_translation pose_matrix[:3, :3] = R.from_euler( "xyz", @@ -199,12 +199,17 @@ def working_loop(self) -> None: self.interpolation_start_pose = pose_matrix # Calculate interpolation progress (t from 0 to 1) - elapsed_interpolation = current_time - self.interpolation_start_time + interpolation_start_time = self.interpolation_start_time + interpolation_start_pose = self.interpolation_start_pose + if interpolation_start_time is None or interpolation_start_pose is None: + continue + + elapsed_interpolation = current_time - interpolation_start_time t = min(1.0, elapsed_interpolation / self.interpolation_duration) # Interpolate between current pose and neutral pose interpolated_pose = linear_pose_interpolation( - self.interpolation_start_pose, + interpolation_start_pose, neutral_pose, t, ) diff --git a/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/chat_completions.py b/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/chat_completions.py new file mode 100644 index 00000000..882f6d0b --- /dev/null +++ b/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/chat_completions.py @@ -0,0 +1,270 @@ +"""Chat Completions text/tool loop for the local-STT backend.""" + +import re +import json +import uuid +import asyncio +import logging +from typing import Any, Final, cast + +from reachy_mini_conversation_app.prompts import get_session_instructions +from reachy_mini_conversation_app.tools.core_tools import ( + ToolDependencies, + get_tool_specs, + dispatch_tool_call_with_manager, +) +from reachy_mini_conversation_app.tools.background_tool_manager import BackgroundToolManager + + +logger = logging.getLogger(__name__) + +_RATE_LIMIT_ATTEMPTS: Final[int] = 3 +_RATE_LIMIT_DEFAULT_DELAY: Final[float] = 5.0 +_RATE_LIMIT_MAX_DELAY: Final[float] = 30.0 +_TOOL_ROUND_LIMIT: Final[int] = 5 +_WAIT_RE: Final[re.Pattern[str]] = re.compile( + r"(?:please\s+)?wait\s+(\d+(?:\.\d+)?)\s+seconds?", + re.IGNORECASE, +) + + +def chat_completion_tool_specs() -> list[dict[str, Any]]: + """Convert Realtime-style tool specs to Chat Completions tool specs.""" + chat_tools: list[dict[str, Any]] = [] + for tool in get_tool_specs(): + if tool.get("type") != "function": + continue + chat_tools.append( + { + "type": "function", + "function": { + "name": tool.get("name"), + "description": tool.get("description", ""), + "parameters": tool.get("parameters", {}), + }, + } + ) + return chat_tools + + +def _tool_call_value(tool_call: Any, name: str) -> Any: + """Read a value from either an SDK model object or a dict.""" + if isinstance(tool_call, dict): + return tool_call.get(name) + return getattr(tool_call, name, None) + + +def _message_value(message: Any, name: str) -> Any: + """Read a chat message value from either an SDK model object or a dict.""" + if isinstance(message, dict): + return message.get(name) + return getattr(message, name, None) + + +def _choice_message(choice: Any) -> Any: + """Read a Chat Completions choice message from either an object or a dict.""" + if isinstance(choice, dict): + return choice.get("message") + return getattr(choice, "message", None) + + +def _tool_call_function_value(tool_call: Any, name: str) -> Any: + """Read a function value from either an SDK tool-call object or a dict.""" + function = _tool_call_value(tool_call, "function") + if isinstance(function, dict): + return function.get(name) + return getattr(function, name, None) + + +def _serialize_tool_call(tool_call: Any) -> dict[str, Any]: + """Convert a tool call into the dict shape Chat Completions expects.""" + if hasattr(tool_call, "model_dump"): + return tool_call.model_dump() + if isinstance(tool_call, dict): + return tool_call + return { + "id": getattr(tool_call, "id", None), + "type": getattr(tool_call, "type", "function"), + "function": { + "name": getattr(getattr(tool_call, "function", None), "name", None), + "arguments": getattr(getattr(tool_call, "function", None), "arguments", "{}"), + }, + } + + +def _rate_limit_delay(exc: Exception) -> float | None: + """Return a retry delay when a Chat Completions error is a provider rate limit.""" + status_code = getattr(exc, "status_code", None) + message = str(exc) + is_rate_limit = ( + status_code == 429 + or "ratelimit" in type(exc).__name__.lower() + or "rate limit" in message.lower() + or "throttling" in message.lower() + ) + if not is_rate_limit: + return None + + response = getattr(exc, "response", None) + headers = getattr(response, "headers", None) + if headers is not None: + retry_after = headers.get("retry-after") or headers.get("Retry-After") + if retry_after: + try: + return min(float(retry_after), _RATE_LIMIT_MAX_DELAY) + except (TypeError, ValueError): + pass + + match = _WAIT_RE.search(message) + if match: + try: + return min(float(match.group(1)), _RATE_LIMIT_MAX_DELAY) + except (TypeError, ValueError): + pass + + return _RATE_LIMIT_DEFAULT_DELAY + + +class ChatCompletionRunner: + """Run a Chat Completions turn, including Reachy tool calls.""" + + def __init__( + self, + *, + client: Any, + deps: ToolDependencies, + tool_manager: BackgroundToolManager, + model_name: str, + base_url: str | None, + ) -> None: + """Initialize the runner.""" + self.client = client + self.deps = deps + self.tool_manager = tool_manager + self.model_name = model_name + self.base_url = base_url + + async def create_with_retries(self, operation: str, **kwargs: Any) -> Any: + """Create a Chat Completions response, retrying short provider rate limits.""" + for attempt in range(1, _RATE_LIMIT_ATTEMPTS + 1): + try: + return await self.client.chat.completions.create(**kwargs) + except Exception as e: + delay = _rate_limit_delay(e) + if delay is None or attempt == _RATE_LIMIT_ATTEMPTS: + raise + + logger.warning( + "%s rate-limited by provider; retrying in %.1fs (%d/%d)", + operation, + delay, + attempt, + _RATE_LIMIT_ATTEMPTS, + ) + await asyncio.sleep(delay) + + raise RuntimeError("unreachable Chat Completions retry state") + + async def send_text_message(self, text: str) -> list[dict[str, Any]]: + """Send a user text turn through Chat Completions and Reachy tools.""" + chatbot_messages: list[dict[str, Any]] = [{"role": "user", "content": text}] + chat_messages: list[dict[str, Any]] = [ + {"role": "system", "content": get_session_instructions()}, + {"role": "user", "content": text}, + ] + chat_tools = chat_completion_tool_specs() + + operation = "Chat Completions request" + request_kwargs: dict[str, Any] = { + "model": self.model_name, + "messages": cast(Any, chat_messages), + "tools": cast(Any, chat_tools), + "tool_choice": "auto", + } + + for tool_round in range(_TOOL_ROUND_LIMIT + 1): + try: + completion = await self.create_with_retries(operation, **request_kwargs) + except Exception as e: + logger.exception("%s failed", operation) + chatbot_messages.append( + { + "role": "assistant", + "content": ( + f"[error] {operation} failed " + f"(model={self.model_name!r}, base_url={self.base_url!r}): " + f"{type(e).__name__}: {e}" + ), + } + ) + return chatbot_messages + + choice = completion.choices[0] if completion.choices else None + assistant_message = _choice_message(choice) if choice else None + assistant_content = _message_value(assistant_message, "content") or "" + tool_calls = _message_value(assistant_message, "tool_calls") or [] + + if not tool_calls: + chatbot_messages.append({"role": "assistant", "content": assistant_content or "[no response]"}) + return chatbot_messages + + if tool_round >= _TOOL_ROUND_LIMIT: + chatbot_messages.append( + { + "role": "assistant", + "content": ( + f"[error] Chat Completions exceeded the configured tool round limit ({_TOOL_ROUND_LIMIT})." + ), + } + ) + return chatbot_messages + + chat_messages.append( + { + "role": "assistant", + "content": assistant_content, + "tool_calls": [_serialize_tool_call(tool_call) for tool_call in tool_calls], + } + ) + + for tool_call in tool_calls: + tool_call_id = _tool_call_value(tool_call, "id") or str(uuid.uuid4()) + tool_name = _tool_call_function_value(tool_call, "name") + args_json = _tool_call_function_value(tool_call, "arguments") or "{}" + if not isinstance(tool_name, str): + tool_result = {"error": "tool call did not include a valid function name"} + else: + tool_result = await dispatch_tool_call_with_manager( + tool_name, + args_json, + self.deps, + self.tool_manager, + ) + + tool_result_json = json.dumps(tool_result) + chat_messages.append( + { + "role": "tool", + "tool_call_id": tool_call_id, + "content": tool_result_json, + } + ) + chatbot_messages.append( + { + "role": "assistant", + "content": tool_result_json, + "metadata": { + "title": f"Used tool {tool_name or 'unknown'}", + "status": "done", + }, + } + ) + + operation = "Chat Completions tool follow-up" + request_kwargs = { + "model": self.model_name, + "messages": cast(Any, chat_messages), + "tools": cast(Any, chat_tools), + } + + raise RuntimeError("unreachable Chat Completions tool round state") diff --git a/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/config.py b/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/config.py index 115fcdae..c90f86ac 100644 --- a/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/config.py +++ b/projects/reachy-mini-openshell/src/reachy_mini_conversation_app/config.py @@ -1,16 +1,36 @@ import os +import re import sys import logging +from typing import Mapping from pathlib import Path -from collections.abc import Mapping +from dataclasses import dataclass +from urllib.parse import urlsplit, parse_qsl, urlunsplit -from dotenv import find_dotenv, load_dotenv, dotenv_values +from dotenv import find_dotenv, dotenv_values LOCKED_PROFILE = "_reachy_mini_conversation_app_locked_profile" DEFAULT_PROFILES_DIRECTORY = Path(__file__).parent / "profiles" +BACKEND_OPENAI_REALTIME = "openai_realtime" +BACKEND_HF_REALTIME = "hf_realtime" +BACKEND_LOCAL_STT = "local_stt" +BACKEND_PROVIDERS = { + BACKEND_OPENAI_REALTIME, + BACKEND_HF_REALTIME, + BACKEND_LOCAL_STT, +} + +HF_REALTIME_CONNECTION_DEPLOYED = "deployed" +HF_REALTIME_CONNECTION_LOCAL = "local" +HF_REALTIME_SESSION_PROXY_URL = "https://pollen-robotics-reachy-mini-realtime-url.hf.space/session" + logger = logging.getLogger(__name__) +_MARKDOWN_URL_RE = re.compile(r"^\[(?P     -## Featured tutorial +## Featured project ### Reachy Mini + OpenShell -Build a physical Reachy Mini application with an authenticated MCP robot -service, an OpenShell-sandboxed conversation agent, separate Realtime and -vision model routes, and policy-controlled robot tools. +Run a voice agent onboard a physical Reachy Mini while OpenShell independently +allows camera capture and denies head motion. The robot-native controller owns +media; the conversation and model-selected REST tools stay inside the sandbox. -[Start the step-by-step tutorial](projects/reachy-mini-openshell-sandbox.md){ .md-button .md-button--primary } +[Read the Dev Note](dev-notes/posts/2026-07-13-policy-controlling-reachy-mini-with-openshell.md){ .md-button .md-button--primary } +[Open the setup tutorial](https://github.com/NVIDIA/OpenShell-Research/blob/kirit93/reachy-implementation/projects/reachy-mini-openshell/ONBOARD_SETUP.md){ .md-button } [View the project overview](projects/reachy-mini-openshell/index.md){ .md-button } ## Starting points @@ -30,7 +31,7 @@ vision model routes, and policy-controlled robot tools. - [Research engineering](research/index.md) - [Projects](projects/index.md) - [Reachy Mini + OpenShell project](projects/reachy-mini-openshell/index.md) -- [Reachy Mini OpenShell sandbox tutorial](projects/reachy-mini-openshell-sandbox.md) +- [Designing OpenShell for the Edge](dev-notes/posts/2026-07-13-policy-controlling-reachy-mini-with-openshell.md) - [Runtime notes](research/runtime.md) - [Application patterns](research/applications.md) - [Dev Notes](dev-notes/index.md) diff --git a/docs/projects/index.md b/docs/projects/index.md index 860e1dea..6a86e2bc 100644 --- a/docs/projects/index.md +++ b/docs/projects/index.md @@ -8,11 +8,14 @@ setup guide, validation commands, and troubleshooting notes. ### [Reachy Mini + OpenShell](reachy-mini-openshell/index.md) A physical-robot and simulator conversation demo with OpenAI Realtime, a -Gradio UI, an authenticated host-side MCP service, approved vision routing, -and OpenShell policy enforcement for robot tools. +robot-native audio and camera bridge, fixed REST actions, an optional Gradio +diagnostic UI, and OpenShell policy enforcement for physical robot tools. -**Following the POC build?** Start with the -[full step-by-step sandbox tutorial](reachy-mini-openshell-sandbox.md). +**Want the edge architecture and engineering story?** Read +[Designing OpenShell for the Edge](../dev-notes/posts/2026-07-13-policy-controlling-reachy-mini-with-openshell.md). + +**Building it on a robot?** Follow the +[project-local onboard setup tutorial](https://github.com/NVIDIA/OpenShell-Research/blob/kirit93/reachy-implementation/projects/reachy-mini-openshell/ONBOARD_SETUP.md). ## Project Page Standard diff --git a/docs/projects/reachy-mini-openshell-sandbox.md b/docs/projects/reachy-mini-openshell-sandbox.md index 05be9746..e11e7894 100644 --- a/docs/projects/reachy-mini-openshell-sandbox.md +++ b/docs/projects/reachy-mini-openshell-sandbox.md @@ -1,468 +1,9 @@ -# Run Reachy Mini Through an OpenShell REST Policy +# Reachy Mini + OpenShell Setup Tutorial -This tutorial runs the Reachy Mini conversation app inside an OpenShell sandbox, -calls the robot daemon's REST API for fixed head actions, and optionally captures -one camera frame through a narrow trusted native Reachy App adapter. +The canonical tutorial now lives beside the runnable project: -There is no MCP server, JSON-RPC adapter, scene scan, camera configuration tool, -or separate vision-model route. The existing OpenAI Realtime session receives -the captured image. +[Open the onboard setup tutorial](https://github.com/NVIDIA/OpenShell-Research/blob/kirit93/reachy-implementation/projects/reachy-mini-openshell/ONBOARD_SETUP.md){ .md-button .md-button--primary } -## What this demonstrates - -The model can translate a request such as: - -```text -Reachy, look up and then right. -``` - -into the fixed application tool call: - -```json -{"directions": ["up", "right"]} -``` - -The application maps those names to fixed head poses and sends one ordered -`POST /api/move/goto` request at a time. OpenShell decides whether that HTTP -method and path may leave the sandbox. - -For a request such as `Reachy, what do you see?`, the model calls the fixed -`camera(question)` tool. That tool sends an argument-free -`POST /camera/capture` request. OpenShell independently decides whether that -single capture endpoint may leave the sandbox. - -## Architecture - -```mermaid -flowchart LR - U["Reachy microphone and speaker"] <--> N["Trusted native Reachy App"] - N <-->|"PCM audio"| A["Conversation app
    OpenShell sandbox"] - A -->|"Realtime WebSocket"| O["OpenAI Realtime"] - A -->|"Motion REST"| P["OpenShell network policy"] - P -->|"host.openshell.internal:8000"| D["Reachy Mini daemon"] - D --> H["Head motors"] - A -->|"POST /camera/capture"| P - P -->|"host.openshell.internal:8042"| N - N --> C["Reachy camera"] -``` - -The sandbox does not start the Reachy SDK, movement manager, camera worker, or -vision router. The trusted native Reachy App owns the SDK media object and only -bridges audio plus one bounded JPEG capture operation. - -## Security boundary - -OpenShell REST rules can match: - -- Calling binary -- Destination host and port -- HTTP method -- URL path -- Query parameters - -OpenShell can therefore allow or deny: - -```text -POST /api/move/goto -POST /camera/capture -``` - -It does not currently enforce arbitrary JSON values inside that REST request. -Once `/api/move/goto` is allowed, OpenShell cannot prove that the body contains -only a head pose or distinguish `up` from `down`. - -The application reduces normal model behavior to fixed values: - -| Direction | Pitch | Yaw | -| --- | ---: | ---: | -| `up` | -30 degrees | 0 degrees | -| `down` | 30 degrees | 0 degrees | -| `left` | 0 degrees | 40 degrees | -| `right` | 0 degrees | -40 degrees | -| `front` | 0 degrees | 0 degrees | - -It also fixes duration to one second, uses `minjerk`, and omits antennas and -body yaw. These body constraints are application validation, not OpenShell -policy enforcement. - -Camera capture has a tighter adapter boundary: the request has no body fields -or query parameters. The native adapter chooses the already-open Reachy camera, -captures one JPEG, never writes it to disk, limits the response to 2 MiB, and -rate-limits calls. OpenShell still enforces the calling binary, host, port, -method, and exact path; the adapter enforces the capture semantics. - -## Prerequisites - -- Reachy Mini daemon reachable on port `8000` -- Docker-backed OpenShell gateway -- Python 3.10 through 3.12 for local development -- `uv` -- OpenAI provider configured for the sandbox - -Verify the robot daemon before adding OpenShell: - -```bash -curl http://reachy-mini.local:8000/api/daemon/status -``` - -For an on-robot sandbox, also verify the daemon through the Docker host alias: - -```bash -docker run --rm --add-host host.openshell.internal:host-gateway \ - curlimages/curl:latest \ - http://host.openshell.internal:8000/api/daemon/status -``` - -Do not continue until the daemon reports `state: running`. - -## Run locally before sandboxing - -From the project directory: - -```bash -cp .env.example .env -export OPENAI_API_KEY=sk-... -./scripts/start-local.sh -``` - -The default `.env.example` selects: - -```dotenv -REACHY_TOOL_TRANSPORT=rest -REACHY_REST_BASE_URL=http://127.0.0.1:8000 -``` - -Test these prompts in text mode first: - -```text -Reachy, look up. -Reachy, look front. -Reachy, look left and then right. -Stop moving. -``` - -## REST transport behavior - -The REST transport always advertises these physical tools: - -- `move_head(directions)` -- `stop_motion()` - -When `REACHY_CAMERA_BASE_URL` is configured, it additionally advertises: - -- `camera(question)` - -`move_head` accepts one to eight values from `left`, `right`, `up`, `down`, and -`front`. Extra keys and raw pose values are rejected before a network request is -made. - -Each successful `goto` returns a move UUID. The client polls -`GET /api/move/running` and waits for that UUID to finish before sending the next -direction. A timed-out POST is reported as `unknown_delivery` and is never -automatically retried. - -`stop_motion` lists active move UUIDs and calls `POST /api/move/stop` once for -each one. - -`camera` posts no model-supplied capture settings. It accepts only a short -question, validates the JPEG response, sends the image into the existing -Realtime conversation, and asks the assistant to answer aloud. An OpenShell -`403` becomes `status: policy_denied` and is not retried. - -## OpenShell policies - -Three relevant policies are checked in: - -```text -openshell/policy-motion-disabled.yaml -openshell/policy-camera-enabled-motion-disabled.yaml -openshell/policy-head-motion-enabled.yaml -``` - -Both allow: - -```text -GET /api/daemon/status -GET /api/move/running -POST /api/move/stop -``` - -Only `policy-head-motion-enabled.yaml` allows: - -```text -POST /api/move/goto -``` - -Only `policy-camera-enabled-motion-disabled.yaml` allows: - -```text -POST /camera/capture -``` - -That camera policy still blocks `POST /api/move/goto`. The base -`policy-motion-disabled.yaml` blocks both camera capture and motion start. - -Neither policy allows `/api/move/set_target`, `/api/motors/**`, -`/api/apps/**`, raw movement WebSockets, wake/sleep, or recorded motions. - -The permitted binary is `/opt/venv/bin/python`. A denial seen with `curl` could -therefore be a binary denial rather than a path denial; use the application or -the same Python executable for final policy tests. - -## Build the sandbox image - -```bash -docker build -f Dockerfile.openshell -t reachy-openshell-rest . -``` - -The image installs the application at `/opt/venv` and runs as the sandbox user. - -## Create the sandbox once - -Create an idle sandbox with camera enabled and motion disabled: - -```bash -openshell sandbox create \ - --name reachy-agent \ - --from ./Dockerfile.openshell \ - --policy ./openshell/policy-camera-enabled-motion-disabled.yaml \ - --provider reachy-openai \ - --env REACHY_MINI_SKIP_DOTENV=1 \ - --env BACKEND_PROVIDER=openai_realtime \ - --env REACHY_TOOL_TRANSPORT=rest \ - --env REACHY_REST_BASE_URL=http://host.openshell.internal:8000 \ - --env REACHY_CAMERA_BASE_URL=http://host.openshell.internal:8042 \ - --env REACHY_REST_TIMEOUT_SECONDS=5 \ - --env REACHY_MOTION_DURATION_SECONDS=1 \ - --env REACHY_MOTION_POLL_INTERVAL_SECONDS=0.1 \ - --env REACHY_MOTION_COMPLETION_TIMEOUT_SECONDS=10 \ - --env REACHY_AUDIO_HOST=127.0.0.1 \ - --env REACHY_AUDIO_PORT=8765 \ - --env REACHY_AGENT_START_TIMEOUT_SECONDS=120 \ - --env REACHY_MODEL_LOGS=1 \ - --env OPENAI_REALTIME_BASE_URL=https://api.openai.com/v1 \ - --env OPENAI_REALTIME_MODEL=gpt-realtime-2 \ - --env OPENAI_REALTIME_VOICE=cedar -``` - -Check that it is ready: - -```bash -openshell sandbox get reachy-agent -``` - -The 120-second agent startup window is intentional. A cold import of the audio -stack takes about 40 seconds on the Reachy Mini onboard Raspberry Pi. - -## Robot-native media and lifecycle - -The normal onboard path uses a small trusted Reachy App from -`projects/reachy-mini-openshell/native-controller`. It owns only the robot -microphone, speaker, camera snapshot adapter, and fixed OpenShell lifecycle -commands. The model, tools, and every requested action remain inside -`reachy-agent`. - -Create the loopback audio service once: - -```bash -openshell service expose reachy-agent 8765 audio -``` - -The native Reachy App's Start lifecycle then runs: - -```bash -openshell sandbox exec --name reachy-agent --no-tty -- \ - /opt/venv/bin/reachy-agent-control start -``` - -Its audio client connects locally on the robot to: - -```text -ws://reachy-agent--audio.openshell.localhost:17670/audio -``` - -The service accepts one client, mono signed 16-bit PCM at 16 kHz, and exposes -`GET /health` plus `WS /audio`. The Reachy App reads and plays audio through the -SDK media manager. No laptop, browser, Gradio page, or SSH tunnel is required -after installation. - -The same native app serves only this camera operation on the robot host: - -```text -POST http://127.0.0.1:8042/camera/capture -``` - -The sandbox addresses it as -`http://host.openshell.internal:8042/camera/capture`, so the call crosses the -OpenShell REST policy. It is not exposed as an OpenShell browser service. - -When the Reachy App is stopped it runs: - -```bash -openshell sandbox exec --name reachy-agent --no-tty -- \ - /opt/venv/bin/reachy-agent-control stop -``` - -The sandbox, provider, service endpoint, and policy remain provisioned for the -next Start. - -Build the native controller on the development machine: - -```bash -cd projects/reachy-mini-openshell -uv build --project native-controller -``` - -Copy `native-controller/dist/reachy_mini_openshell_controller-0.2.0-py3-none-any.whl` -to `/home/pollen/` on Reachy. On a Wireless unit, install it directly into the -daemon's shared app environment using the Pollen-supported manual deployment -path: - -```bash -/opt/uv/uv pip install --no-cache \ - --python /venvs/apps_venv/bin/python \ - /home/pollen/reachy_mini_openshell_controller-0.2.0-py3-none-any.whl -``` - -The `/api/apps/install` endpoint intentionally does not accept `source_kind: -local`; that endpoint installs catalog/Hugging Face apps. After the manual pip -install, `reachy_mini_openshell_controller` appears in the installed app list -and can be started from the Reachy Apps UI. The daemon launches the controller -in its shared apps environment and supplies the local `ReachyMini` media object. - -Inspect the inner process when troubleshooting: - -```bash -openshell sandbox exec --name reachy-agent --no-tty -- \ - /opt/venv/bin/reachy-agent-control status -openshell sandbox exec --name reachy-agent --no-tty -- \ - tail -n 100 /sandbox/logs/reachy-agent.log -``` - -## Optional Gradio diagnostic path - -To diagnose the model/tool path independently of robot-native audio, run the -browser application without recreating the sandbox: - -```bash -openshell sandbox exec \ - --name reachy-agent \ - --timeout 0 \ - --no-tty \ - -- \ - /opt/venv/bin/python -m reachy_mini_conversation_app \ - --gradio \ - --model-logs \ - --tool-transport rest -``` - -In another terminal, expose the Gradio port once: - -```bash -openshell service expose reachy-agent 7860 gradio -``` - -Open the URL printed by OpenShell. Keep the foreground `sandbox exec` running -until the diagnostic session is finished. The native Reachy App does not use -this Gradio endpoint. - -## Verify the denied action - -With `policy-motion-disabled.yaml` active, say: - -```text -Reachy, look up. -``` - -Expected behavior: - -1. The model selects `move_head`. -2. The app attempts `POST /api/move/goto`. -3. OpenShell returns HTTP `403`. -4. The tool result has `status: policy_denied`. -5. Reachy does not move. -6. The assistant explains that policy blocked the action and does not retry. - -## Verify camera allow and deny - -With `policy-camera-enabled-motion-disabled.yaml` active, say: - -```text -Reachy, take a picture and tell me what you see. -``` - -Expected behavior: the model selects `camera`, OpenShell permits only -`POST /camera/capture`, one JPEG is delivered to the Realtime session, and -Reachy answers aloud. Asking `Reachy, look up` remains denied. - -To prove the camera boundary, hot-reload `policy-motion-disabled.yaml` and ask -the picture question again. Reachy must not capture a frame and should explain -that policy blocked the action. Restore the camera-enabled policy to allow -snapshots again. - -Inspect logs: - -```bash -openshell logs reachy-agent --tail -``` - -## Enable head motion without restarting - -Hot-reload the enabled policy: - -```bash -openshell policy set reachy-agent \ - --policy ./openshell/policy-head-motion-enabled.yaml \ - --wait -``` - -Repeat the same request. Reachy should now move through the fixed application -pose. - -Return to the restrictive policy: - -```bash -openshell policy set reachy-agent \ - --policy ./openshell/policy-motion-disabled.yaml \ - --wait -``` - -## Negative policy tests - -Use the permitted Python binary inside the sandbox to test a dangerous path: - -```bash -openshell sandbox exec -n reachy-agent -- \ - /opt/venv/bin/python -c \ - 'import httpx; print(httpx.post("http://host.openshell.internal:8000/api/move/set_target", json={}).status_code)' -``` - -Expected result: `403`. - -Repeat for a motor path or app-management path. Those requests must remain -denied under both policies. - -## Tests - -```bash -uv run ruff check . -uv run pytest -q -docker build -f Dockerfile.openshell -t reachy-openshell-rest . -``` - -The unit suite covers fixed schemas, pose mapping, argument rejection, ordered -movement, stop behavior, OpenShell `403` conversion, no retry after an uncertain -motion POST, native JPEG limits, and exact camera-policy rules. - -## Completion criteria - -- No MCP package, server, client, token, or endpoint remains. -- The sandbox starts no local robot SDK or camera workers. -- Only fixed head directions, stop, and the optional one-frame camera tool are - model-visible robot actions. -- Motion-disabled policy blocks `goto` while preserving stop. -- Camera-enabled/motion-disabled policy permits only one fixed capture endpoint - and still blocks `goto`. -- Motion-enabled policy allows `goto` but no raw target or motor endpoints. -- Policy can be hot-reloaded without recreating the sandbox. -- Documentation states that JSON body values remain application-enforced. +For the engineering story and reusable edge architecture, read +[Designing OpenShell for the Edge: Why Policy Has to Live Next to the +Action](../dev-notes/posts/2026-07-13-policy-controlling-reachy-mini-with-openshell.md). diff --git a/docs/projects/reachy-mini-openshell/index.md b/docs/projects/reachy-mini-openshell/index.md index 8a06abbf..6f14345a 100644 --- a/docs/projects/reachy-mini-openshell/index.md +++ b/docs/projects/reachy-mini-openshell/index.md @@ -1,12 +1,21 @@ # Reachy Mini + OpenShell -This project demonstrates how OpenShell can constrain an AI-controlled physical -Reachy Mini by mediating direct REST calls from a sandboxed conversation app. +This project is a reference implementation for running OpenShell on an edge +device. A conversation agent runs in an onboard sandbox, trusted native code +owns the hardware, and local policy mediates the REST calls that can produce +physical effects on Reachy Mini. ## Start here -Follow the **[Reachy Mini OpenShell sandbox tutorial](../reachy-mini-openshell-sandbox.md)** -for the complete, copy-and-run build. +Read **[Designing OpenShell for the Edge: Why Policy Has to Live Next to the +Action](../../dev-notes/posts/2026-07-13-policy-controlling-reachy-mini-with-openshell.md)** +for the reusable edge architecture, implementation decisions, challenges, and +demo result. + +Follow the **[project-local onboard setup +tutorial](https://github.com/NVIDIA/OpenShell-Research/blob/kirit93/reachy-implementation/projects/reachy-mini-openshell/ONBOARD_SETUP.md)** +for the copy-and-run build, installation, policy verification, voice demo, and +troubleshooting steps. The tutorial progressively adds: @@ -21,16 +30,19 @@ The tutorial progressively adds: | Component | Location | Responsibility | | --- | --- | --- | | Reachy daemon | Reachy Mini | Controls the physical motors and exposes the REST API. | -| OpenShell gateway | Sandbox host | Creates the sandbox and enforces REST method/path policy. | -| Conversation application | OpenShell sandbox | Runs the Gradio UI and Realtime conversation session. | +| OpenShell gateway | Reachy Mini | Creates the onboard sandbox and enforces REST method/path policy. | +| Conversation application | OpenShell sandbox on Reachy | Runs the Realtime conversation session and fixed REST tools. | +| Native controller | Reachy App on Reachy | Owns microphone, speaker, and camera; starts/stops the sandbox agent. | ## Project resources -- [Full step-by-step tutorial](../reachy-mini-openshell-sandbox.md) -- [Application source and README](https://github.com/NVIDIA/OpenShell-Research/tree/main/projects/reachy-mini-openshell) -- [Motion-disabled policy](https://github.com/NVIDIA/OpenShell-Research/blob/main/projects/reachy-mini-openshell/openshell/policy-motion-disabled.yaml) -- [Head-motion-enabled policy](https://github.com/NVIDIA/OpenShell-Research/blob/main/projects/reachy-mini-openshell/openshell/policy-head-motion-enabled.yaml) -- [Sandbox Dockerfile](https://github.com/NVIDIA/OpenShell-Research/blob/main/projects/reachy-mini-openshell/Dockerfile.openshell) +- [Implementation Dev Note](../../dev-notes/posts/2026-07-13-policy-controlling-reachy-mini-with-openshell.md) +- [Onboard setup and troubleshooting tutorial](https://github.com/NVIDIA/OpenShell-Research/blob/kirit93/reachy-implementation/projects/reachy-mini-openshell/ONBOARD_SETUP.md) +- [Application source and README](https://github.com/NVIDIA/OpenShell-Research/tree/kirit93/reachy-implementation/projects/reachy-mini-openshell) +- [Motion-disabled policy](https://github.com/NVIDIA/OpenShell-Research/blob/kirit93/reachy-implementation/projects/reachy-mini-openshell/openshell/policy-motion-disabled.yaml) +- [Camera-enabled, motion-disabled policy](https://github.com/NVIDIA/OpenShell-Research/blob/kirit93/reachy-implementation/projects/reachy-mini-openshell/openshell/policy-camera-enabled-motion-disabled.yaml) +- [Head-motion-enabled policy](https://github.com/NVIDIA/OpenShell-Research/blob/kirit93/reachy-implementation/projects/reachy-mini-openshell/openshell/policy-head-motion-enabled.yaml) +- [Sandbox Dockerfile](https://github.com/NVIDIA/OpenShell-Research/blob/kirit93/reachy-implementation/projects/reachy-mini-openshell/Dockerfile.openshell) ## Two ways to use the project @@ -41,5 +53,5 @@ without an OpenShell sandbox. ### Build the OpenShell policy POC -Use the sandbox tutorial when you want to demonstrate direct REST restrictions, -visible policy denials, and the physical Reachy Mini architecture. +Use the onboard setup tutorial when you want to demonstrate direct REST +restrictions, visible policy denials, and the physical Reachy Mini architecture. diff --git a/docs/research/applications.md b/docs/research/applications.md index bf94f8b4..675e791a 100644 --- a/docs/research/applications.md +++ b/docs/research/applications.md @@ -15,7 +15,9 @@ research project. Keep project-specific setup in [Projects](../projects/index.md [Reachy Mini + OpenShell](../projects/reachy-mini-openshell/index.md) is the current runnable example: OpenAI Realtime conversation, a browser UI, simulator -or physical robot operation, an authenticated MCP tool boundary, approved -vision routing, and OpenShell policy enforcement for Reachy tools. Follow the -[step-by-step sandbox tutorial](../projects/reachy-mini-openshell-sandbox.md) -to build the complete POC. +or physical robot operation, a robot-native media bridge, fixed REST actions, +and OpenShell policy enforcement for Reachy tools. Read the +[implementation Dev Note](../dev-notes/posts/2026-07-13-policy-controlling-reachy-mini-with-openshell.md), +then follow the +[project-local setup tutorial](https://github.com/NVIDIA/OpenShell-Research/blob/kirit93/reachy-implementation/projects/reachy-mini-openshell/ONBOARD_SETUP.md) +to reproduce the complete onboard demo. diff --git a/projects/reachy-mini-openshell/ONBOARD_SETUP.md b/projects/reachy-mini-openshell/ONBOARD_SETUP.md new file mode 100644 index 00000000..fa9abbcc --- /dev/null +++ b/projects/reachy-mini-openshell/ONBOARD_SETUP.md @@ -0,0 +1,762 @@ +# Onboard Reachy Mini + OpenShell Setup + +This is the canonical setup guide for running the Reachy Mini conversation app +on the robot itself. The conversation agent runs inside an OpenShell sandbox; +a trusted native Reachy App owns microphone, speaker, and one-frame camera +access; and OpenShell independently allows or denies the REST requests that can +cause physical actions. + +For the implementation story, architecture decisions, and lessons from building +the demo, read the [Dev Note](https://github.com/NVIDIA/OpenShell-Research/blob/kirit93/reachy-implementation/docs/dev-notes/posts/2026-07-13-policy-controlling-reachy-mini-with-openshell.md). + +The commands alternate between a **development machine** and **Reachy**. Build +the wheel and ARM64 image on the development machine; install and run the final +artifacts on Reachy. + +## What this demonstrates + +The model can translate a request such as: + +```text +Reachy, look up and then right. +``` + +into the fixed application tool call: + +```json +{"directions": ["up", "right"]} +``` + +The application maps those names to fixed head poses and sends one ordered +`POST /api/move/goto` request at a time. OpenShell decides whether that HTTP +method and path may leave the sandbox. + +For a request such as `Reachy, what do you see?`, the model calls the fixed +`camera(question)` tool. That tool sends an argument-free +`POST /camera/capture` request. OpenShell independently decides whether that +single capture endpoint may leave the sandbox. + +## Architecture + +```mermaid +flowchart LR + U["Reachy microphone and speaker"] <--> N["Trusted native Reachy App"] + N <-->|"PCM audio"| A["Conversation app
    OpenShell sandbox"] + A -->|"Realtime WebSocket"| O["OpenAI Realtime"] + A -->|"Motion REST"| P["OpenShell network policy"] + P -->|"host.openshell.internal:8000"| D["Reachy Mini daemon"] + D --> H["Head motors"] + A -->|"POST /camera/capture"| P + P -->|"host.openshell.internal:8042"| N + N --> C["Reachy camera"] +``` + +The sandbox does not start the Reachy SDK, movement manager, camera worker, or +vision router. The trusted native Reachy App owns the SDK media object and only +bridges audio plus one bounded JPEG capture operation. + +## Security boundary + +OpenShell REST rules can match: + +- Calling binary +- Destination host and port +- HTTP method +- URL path +- Query parameters + +OpenShell can therefore allow or deny: + +```text +POST /api/move/goto +POST /camera/capture +``` + +It does not currently enforce arbitrary JSON values inside that REST request. +Once `/api/move/goto` is allowed, OpenShell cannot prove that the body contains +only a head pose or distinguish `up` from `down`. + +The application reduces normal model behavior to fixed values: + +| Direction | Pitch | Yaw | +| --- | ---: | ---: | +| `up` | -30 degrees | 0 degrees | +| `down` | 30 degrees | 0 degrees | +| `left` | 0 degrees | 40 degrees | +| `right` | 0 degrees | -40 degrees | +| `front` | 0 degrees | 0 degrees | + +It also fixes duration to one second, uses `minjerk`, and omits antennas and +body yaw. These body constraints are application validation, not OpenShell +policy enforcement. + +Camera capture has a tighter adapter boundary: the request has no body fields +or query parameters. The native adapter chooses the already-open Reachy camera, +captures one JPEG, never writes it to disk, limits the response to 2 MiB, and +rate-limits calls. OpenShell still enforces the calling binary, host, port, +method, and exact path; the adapter enforces the capture semantics. + +## Requirements and resource budget + +The proven environment was a Reachy Mini Wireless running ARM64 Debian, Reachy +Mini 1.8.3, 3.7 GiB usable RAM, 2 GiB swap, and a 14 GiB root filesystem. + +| Resource | Requirement for this setup | +| --- | --- | +| Development machine | Git, Docker Buildx, Python 3.10–3.12, and `uv` | +| Reachy architecture | `aarch64`; the container is built for `linux/arm64` | +| Reachy RAM | A 4 GB unit is known to work. The sandbox has a 2 GiB ceiling and the host retains the remaining memory. A 2 GB device is unvalidated. | +| Reachy CPU | The sandbox is limited to 2 CPUs. Build the image off-device. | +| Reachy disk | Start with at least 4 GiB free; 5 GiB is preferred. Retain 1–2 GiB free after cleanup. | +| Network | Reachy must reach the configured Realtime API and must be reachable over SSH during installation. | + +The expanded sandbox image is approximately 339 MB. Installation needs more +temporary space because the compressed archive, expanded image, Docker layer +extraction, Docker/OpenShell packages, and `/venvs/apps_venv` may coexist. The +native controller wheel is only about 13 KB, but creating the shared Reachy Apps +environment and installing its Reachy SDK dependencies can require roughly +1–1.5 GiB if that environment does not already exist. + +The model runs remotely, so no local model weights or GPU are required. The +`--memory 2Gi` value used later is a limit, not a claim that the agent +continuously consumes 2 GiB. + +## Prepare the development checkout (development machine) + +```bash +git clone git@github.com:NVIDIA/OpenShell-Research.git +cd OpenShell-Research +git switch kirit93/reachy-implementation +cd projects/reachy-mini-openshell +``` + +Run the relevant checks before building deployable artifacts: + +```bash +uv run ruff check src tests +uv run pytest -q +PYTHONPATH=native-controller/src uv run pytest -q native-controller/tests +``` + +## Verify and prepare Reachy (Reachy) + +Connect and inspect the robot before installing anything: + +```bash +ssh pollen@reachy-mini.local + +uname -m +free -h +df -h / +curl --silent --show-error http://127.0.0.1:8000/api/daemon/status +``` + +Require `aarch64`, a running physical daemon, and at least 4 GiB free. Then +verify Docker and OpenShell: + +```bash +docker --version +sudo systemctl status docker --no-pager +openshell --version +openshell sandbox list +``` + +If either command is missing, install Docker Engine using Docker's current +Debian ARM64 instructions and install OpenShell using the current OpenShell +instructions. Do not copy credentials into the image, policy, or repository. + +Create the provider once on Reachy, then verify it: + +```bash +openshell provider create \ + --name reachy-openai \ + --type openai \ + --from-existing + +openshell provider get reachy-openai +``` + +Finally, verify that containers can reach the host-side Reachy daemon: + +```bash +docker run --rm --add-host host.openshell.internal:host-gateway \ + curlimages/curl:latest \ + http://host.openshell.internal:8000/api/daemon/status +``` + +Do not continue until the daemon reports `state: running`. + +## Run locally before sandboxing + +From the project directory: + +```bash +cp .env.example .env +export OPENAI_API_KEY=sk-... +./scripts/start-local.sh +``` + +The default `.env.example` selects: + +```dotenv +REACHY_TOOL_TRANSPORT=rest +REACHY_REST_BASE_URL=http://127.0.0.1:8000 +``` + +Test these prompts in text mode first: + +```text +Reachy, look up. +Reachy, look front. +Reachy, look left and then right. +Stop moving. +``` + +## REST transport behavior + +The REST transport always advertises these physical tools: + +- `move_head(directions)` +- `stop_motion()` + +When `REACHY_CAMERA_BASE_URL` is configured, it additionally advertises: + +- `camera(question)` + +`move_head` accepts one to eight values from `left`, `right`, `up`, `down`, and +`front`. Extra keys and raw pose values are rejected before a network request is +made. + +Each successful `goto` returns a move UUID. The client polls +`GET /api/move/running` and waits for that UUID to finish before sending the next +direction. A timed-out POST is reported as `unknown_delivery` and is never +automatically retried. + +`stop_motion` lists active move UUIDs and calls `POST /api/move/stop` once for +each one. + +`camera` posts no model-supplied capture settings. It accepts only a short +question, validates the JPEG response, sends the image into the existing +Realtime conversation, and asks the assistant to answer aloud. An OpenShell +`403` becomes `status: policy_denied` and is not retried. + +## OpenShell policies + +Three relevant policies are checked in: + +```text +openshell/policy-motion-disabled.yaml +openshell/policy-camera-enabled-motion-disabled.yaml +openshell/policy-head-motion-enabled.yaml +``` + +Both allow: + +```text +GET /api/daemon/status +GET /api/move/running +POST /api/move/stop +``` + +Only `policy-head-motion-enabled.yaml` allows: + +```text +POST /api/move/goto +``` + +Only `policy-camera-enabled-motion-disabled.yaml` allows: + +```text +POST /camera/capture +``` + +That camera policy still blocks `POST /api/move/goto`. The base +`policy-motion-disabled.yaml` blocks both camera capture and motion start. + +Neither policy allows `/api/move/set_target`, `/api/motors/**`, +`/api/apps/**`, raw movement WebSockets, wake/sleep, or recorded motions. + +The permitted binary is `/opt/venv/bin/python`. A denial seen with `curl` could +therefore be a binary denial rather than a path denial; use the application or +the same Python executable for final policy tests. + +## Build the deployable artifacts (development machine) + +Build the native Reachy App wheel: + +```bash +uv build --project native-controller + +sha256sum \ + native-controller/dist/reachy_mini_openshell_controller-0.2.0-py3-none-any.whl +``` + +Build the sandbox specifically for Reachy's ARM64 computer: + +```bash +docker buildx build \ + --platform linux/arm64 \ + --load \ + --tag reachy-mini-openshell:rest-arm64 \ + --file Dockerfile.openshell \ + . + +docker image inspect reachy-mini-openshell:rest-arm64 \ + --format 'architecture={{.Architecture}} size={{.Size}} cmd={{json .Config.Cmd}}' +``` + +Require `architecture=arm64` and +`cmd=["/bin/sleep","infinity"]`. The persistent command keeps the pre-created +sandbox alive; the native Reachy App starts and stops the agent process inside +it. + +### Why this image is small + +The image is custom-built rather than copying the complete Reachy environment: + +- Both stages start from `python:3.12-slim-bookworm`. +- A disposable builder stage constructs wheels; build files do not enter the + runtime stage. +- `requirements-rest.txt` contains the sandbox's REST, Realtime, and audio + requirements. +- The application wheel is installed with `--no-deps`, preventing its normal + Reachy SDK, MuJoCo, OpenCV, simulator, dance, camera-worker, and local vision + dependencies from entering the sandbox. +- Pip caches, install-time bytecode, runtime `pip`, and APT metadata are + removed. +- Debian packages use `--no-install-recommends`. + +The image deliberately retains `iproute2` and `nftables`. OpenShell needs the +trusted `ip` helper to create the isolated sandbox network, so removing it to +save a few megabytes breaks provisioning. The tested image was 339,495,096 +bytes according to Docker. + +Export and compress the image for transfer: + +```bash +docker save reachy-mini-openshell:rest-arm64 \ + | gzip > reachy-mini-openshell-rest-arm64.tar.gz + +sha256sum reachy-mini-openshell-rest-arm64.tar.gz +``` + +## Transfer and load the artifacts + +Copy the image, controller wheel, and main demo policy from the development +machine: + +```bash +scp reachy-mini-openshell-rest-arm64.tar.gz \ + pollen@reachy-mini.local:/home/pollen/ + +scp native-controller/dist/reachy_mini_openshell_controller-0.2.0-py3-none-any.whl \ + pollen@reachy-mini.local:/home/pollen/ + +scp openshell/policy-camera-enabled-motion-disabled.yaml \ + openshell/policy-motion-disabled.yaml \ + openshell/policy-head-motion-enabled.yaml \ + pollen@reachy-mini.local:/home/pollen/ +``` + +On Reachy, compare the received checksums with the development machine, then +load and inspect the image: + +```bash +df -h / +docker system df +docker load --input ~/reachy-mini-openshell-rest-arm64.tar.gz + +docker image inspect reachy-mini-openshell:rest-arm64 \ + --format 'architecture={{.Architecture}} size={{.Size}} cmd={{json .Config.Cmd}}' +``` + +`docker load` may print nothing for several minutes on microSD storage. In a +second SSH session, check `ps`, `df -h /`, and `journalctl -u docker` before +assuming it has stalled. After a verified load, the transferred `.tar.gz` can +be deleted to recover space. + +Put policies in a stable operator-owned directory: + +```bash +mkdir -p ~/reachy-openshell +cp ~/policy-*.yaml ~/reachy-openshell/ +``` + +## Create the sandbox once (Reachy) + +Create an idle sandbox with camera enabled and motion disabled: + +```bash +openshell sandbox create \ + --name reachy-agent \ + --from reachy-mini-openshell:rest-arm64 \ + --policy ~/reachy-openshell/policy-camera-enabled-motion-disabled.yaml \ + --provider reachy-openai \ + --cpu 2 \ + --memory 2Gi \ + --env REACHY_MINI_SKIP_DOTENV=1 \ + --env BACKEND_PROVIDER=openai_realtime \ + --env REACHY_TOOL_TRANSPORT=rest \ + --env REACHY_REST_BASE_URL=http://host.openshell.internal:8000 \ + --env REACHY_CAMERA_BASE_URL=http://host.openshell.internal:8042 \ + --env REACHY_REST_TIMEOUT_SECONDS=5 \ + --env REACHY_MOTION_DURATION_SECONDS=1 \ + --env REACHY_MOTION_POLL_INTERVAL_SECONDS=0.1 \ + --env REACHY_MOTION_COMPLETION_TIMEOUT_SECONDS=10 \ + --env REACHY_AUDIO_HOST=127.0.0.1 \ + --env REACHY_AUDIO_PORT=8765 \ + --env REACHY_AGENT_START_TIMEOUT_SECONDS=120 \ + --env REACHY_MODEL_LOGS=1 \ + --env OPENAI_REALTIME_BASE_URL=https://api.openai.com/v1 \ + --env OPENAI_REALTIME_MODEL=gpt-realtime-2 \ + --env OPENAI_REALTIME_VOICE=cedar +``` + +If the CLI enters an interactive sandbox prompt after creation, type `exit`. +That exits only the shell; the image's `sleep infinity` command keeps the +sandbox alive. + +Check that it is ready: + +```bash +openshell sandbox get reachy-agent +``` + +Require `Phase: Ready`. Read the printed policy and confirm that it allows +`POST host.openshell.internal:8042/camera/capture` but has no allow rule for +`POST host.openshell.internal:8000/api/move/goto`. + +The 120-second agent startup window is intentional. A cold import of the audio +stack takes about 40 seconds on the Reachy Mini onboard Raspberry Pi. + +## Robot-native media and lifecycle + +The normal onboard path uses a small trusted Reachy App from +`projects/reachy-mini-openshell/native-controller`. It owns only the robot +microphone, speaker, camera snapshot adapter, and fixed OpenShell lifecycle +commands. The model, tools, and every requested action remain inside +`reachy-agent`. + +Before installing the native app, test the inner lifecycle directly. A cold +start took approximately 41 seconds on the tested robot: + +```bash +time openshell sandbox exec \ + --name reachy-agent \ + --no-tty \ + -- \ + /usr/bin/env REACHY_AGENT_START_TIMEOUT_SECONDS=120 \ + /opt/venv/bin/reachy-agent-control start + +openshell sandbox exec --name reachy-agent --no-tty -- \ + /opt/venv/bin/reachy-agent-control status + +openshell sandbox exec --name reachy-agent --no-tty -- \ + tail -n 100 /sandbox/logs/reachy-agent.log +``` + +Require `running` and `Application startup complete` before exposing the audio +service. + +### Expose the sandbox audio listener + +The agent listens on `127.0.0.1:8765` **inside the sandbox**. Sandbox loopback +is intentionally private, so the native Reachy App on the host cannot connect +to that address directly. Exposing the service creates a local OpenShell gateway +route from `reachy-agent--audio.openshell.localhost:17670` to the sandbox +listener: + +```bash +openshell service expose reachy-agent 8765 audio +openshell service get reachy-agent audio + +curl --silent --show-error \ + http://reachy-agent--audio.openshell.localhost:17670/health +``` + +Expected output includes: + +```json +{ + "status": "ok", + "active_audio_client": false, + "format": "pcm_s16le", + "sample_rate": 16000, + "channels": 1 +} +``` + +`active_audio_client: false` is correct until the native app connects Reachy's +microphone and speaker. The route is local to the onboard OpenShell gateway; it +does not publish the audio service to the internet or directly to the robot's +LAN. + +The controller's WebSocket URI is: + +```text +ws://reachy-agent--audio.openshell.localhost:17670/audio +``` + +The service accepts one client, mono signed 16-bit PCM at 16 kHz, and exposes +`GET /health` plus `WS /audio`. The Reachy App reads and plays audio through the +SDK media manager. No laptop, browser, Gradio page, or SSH tunnel is required +after installation. + +The same native app serves only this camera operation on the robot host: + +```text +POST http://127.0.0.1:8042/camera/capture +``` + +The sandbox addresses it as +`http://host.openshell.internal:8042/camera/capture`, so the call crosses the +OpenShell REST policy. It is not exposed as an OpenShell browser service. + +When the Reachy App is stopped it runs: + +```bash +openshell sandbox exec --name reachy-agent --no-tty -- \ + /opt/venv/bin/reachy-agent-control stop +``` + +The sandbox, provider, service endpoint, and policy remain provisioned for the +next Start. + +Stop the manually started agent before testing the native lifecycle: + +```bash +openshell sandbox exec --name reachy-agent --no-tty -- \ + /opt/venv/bin/reachy-agent-control stop +``` + +### Install the native Reachy App (Reachy) + +Reachy's application installer does not accept an arbitrary local wheel. Install +the controller into the daemon's shared application environment instead. + +Check whether that environment already exists: + +```bash +ls -l /venvs/apps_venv/bin/python +``` + +If it does not exist, create it with the same Python generation as the Reachy +daemon and install the matching Reachy SDK: + +```bash +/opt/uv/uv venv \ + --python /venvs/mini_daemon/bin/python \ + /venvs/apps_venv + +/opt/uv/uv pip install \ + --no-cache \ + --python /venvs/apps_venv/bin/python \ + 'reachy-mini==1.8.3' +``` + +Use the daemon's actual Reachy Mini version instead of `1.8.3` if it differs: + +```bash +/venvs/mini_daemon/bin/python -c \ + 'import importlib.metadata as m; print(m.version("reachy-mini"))' +``` + +Install the controller wheel that was transferred earlier: + +```bash +/opt/uv/uv pip install --no-cache \ + --python /venvs/apps_venv/bin/python \ + /home/pollen/reachy_mini_openshell_controller-0.2.0-py3-none-any.whl +``` + +The `/api/apps/install` endpoint intentionally does not accept `source_kind: +local`; that endpoint installs catalog/Hugging Face apps. After the manual pip +install, `reachy_mini_openshell_controller` appears in the installed app list +and can be started from the Reachy Apps UI. The daemon launches the controller +in its shared apps environment and supplies the local `ReachyMini` media object. + +Verify the entry point and installed version: + +```bash +/venvs/apps_venv/bin/python -c \ + 'import importlib.metadata as m; print(m.version("reachy-mini-openshell-controller")); print([ep.name for ep in m.entry_points(group="reachy_mini_apps") if "openshell" in ep.name])' +``` + +### Start and verify the native app (Reachy) + +Start it from the Reachy Apps UI, or call the same daemon endpoint: + +```bash +curl --silent --show-error -X POST \ + http://127.0.0.1:8000/api/apps/start-app/reachy_mini_openshell_controller +``` + +Verify all three layers: + +```bash +curl --silent --show-error \ + http://127.0.0.1:8000/api/apps/current-app-status + +openshell sandbox exec --name reachy-agent --no-tty -- \ + /opt/venv/bin/reachy-agent-control status + +openshell service get reachy-agent audio + +curl --silent --show-error \ + http://reachy-agent--audio.openshell.localhost:17670/health +``` + +Require the Reachy App state `running`, inner agent state `running`, an `audio` +service targeting `127.0.0.1:8765`, and a healthy response. Once the native app +connects, `active_audio_client` should become `true`. + +Inspect the inner log when troubleshooting: + +```bash +openshell sandbox exec --name reachy-agent --no-tty -- \ + tail -n 100 /sandbox/logs/reachy-agent.log +``` + +The project README retains an optional Gradio diagnostic path for testing the +model and tool flow independently of robot media. It is not part of normal +onboard operation. + +## Verify the denied action + +With `policy-camera-enabled-motion-disabled.yaml` active, say: + +```text +Reachy, look up. +``` + +Expected behavior: + +1. The model selects `move_head`. +2. The app attempts `POST /api/move/goto`. +3. OpenShell returns HTTP `403`. +4. The tool result has `status: policy_denied`. +5. Reachy does not move. +6. The assistant explains that policy blocked the action and does not retry. + +## Verify camera allow and deny + +With `policy-camera-enabled-motion-disabled.yaml` active, say: + +```text +Reachy, take a picture and tell me what you see. +``` + +Expected behavior: the model selects `camera`, OpenShell permits only +`POST /camera/capture`, one JPEG is delivered to the Realtime session, and +Reachy answers aloud. Asking `Reachy, look up` remains denied. + +To prove the camera boundary, hot-reload the policy that blocks both camera and +motion: + +```bash +openshell policy set reachy-agent \ + --policy ~/reachy-openshell/policy-motion-disabled.yaml \ + --wait +``` + +Ask the picture question again. Reachy must not capture a frame and should +explain that policy blocked the action. Restore the main demo policy afterward: + +```bash +openshell policy set reachy-agent \ + --policy ~/reachy-openshell/policy-camera-enabled-motion-disabled.yaml \ + --wait +``` + +Inspect logs: + +```bash +openshell logs reachy-agent --tail +``` + +## Enable head motion without restarting + +Hot-reload the enabled policy: + +```bash +openshell policy set reachy-agent \ + --policy ~/reachy-openshell/policy-head-motion-enabled.yaml \ + --wait +``` + +Repeat the same request. Reachy should now move through the fixed application +pose. + +Return to the restrictive policy: + +```bash +openshell policy set reachy-agent \ + --policy ~/reachy-openshell/policy-camera-enabled-motion-disabled.yaml \ + --wait +``` + +## Negative policy tests + +Use the permitted Python binary inside the sandbox to test a dangerous path: + +```bash +openshell sandbox exec -n reachy-agent -- \ + /opt/venv/bin/python -c \ + 'import httpx; print(httpx.post("http://host.openshell.internal:8000/api/move/set_target", json={}).status_code)' +``` + +Expected result: `403`. + +Repeat for a motor path or app-management path. Those requests must remain +denied under both policies. + +## Normal operation + +After provisioning, normal use does not require SSH commands: + +1. Start `reachy_mini_openshell_controller` from the Reachy Apps UI. +2. Wait for the app to report `running`; the first cold start may take about 40 + seconds. +3. Speak directly to Reachy. +4. Stop the app from the Reachy Apps UI when finished. + +Stopping the app closes the media bridge and stops the inner conversation +process. It does not delete the sandbox, provider, policy, or audio-service +definition. + +## Troubleshooting quick reference + +| Symptom | First checks | +| --- | --- | +| `docker load` is silent | In another SSH session run `ps -eo pid,etime,stat,%cpu,%mem,cmd | grep '[d]ocker load'`, `df -h /`, and `sudo journalctl -u docker -n 30 --no-pager`. Slow microSD extraction is normal. | +| Sandbox enters `ContainerRestarting` | Inspect the image command. It must be `sleep infinity`; do not append `/bin/true` to `sandbox create`. | +| `reachy-agent failed to become healthy` | Retry with the 120-second timeout and inspect `/sandbox/logs/reachy-agent.log`. A cold start took about 41 seconds. | +| Audio URL says `Service endpoint is not available` | Confirm the inner agent is `running`, then recreate or expose `audio` and check `/health`. The target listener must exist before the route is usable. | +| Audio bridge reports `Name or service not known` | Verify controller version `0.2.0`. It preserves the virtual routing hostname while connecting the socket to `127.0.0.1:17670`. | +| Reachy says it cannot take a picture | Test `POST http://127.0.0.1:8042/camera/capture`, then test the same path from the sandbox with `/opt/venv/bin/python`. If both work, inspect the model/tool logs and session instructions. | +| Local wheel install is rejected by `/api/apps/install` | This endpoint does not accept `source_kind: local`; install the wheel into `/venvs/apps_venv` with `/opt/uv/uv pip install`. | +| Root filesystem is almost full | Run `docker system df` and `sudo du -sh /var/lib/docker /venvs/apps_venv`. Remove transferred archives, obsolete images, failed layers, and old wheel versions—but not the active image or `/venvs/mini_daemon`. | + +## Development checks + +```bash +uv run ruff check src tests +uv run pytest -q +PYTHONPATH=native-controller/src uv run pytest -q native-controller/tests +``` + +The unit suite covers fixed schemas, pose mapping, argument rejection, ordered +movement, stop behavior, OpenShell `403` conversion, no retry after an uncertain +motion POST, native JPEG limits, and exact camera-policy rules. + +## Completion criteria + +- The sandbox starts no local robot SDK or camera workers. +- Only fixed head directions, stop, and the optional one-frame camera tool are + model-visible robot actions. +- Motion-disabled policy blocks `goto` while preserving stop. +- Camera-enabled/motion-disabled policy permits only one fixed capture endpoint + and still blocks `goto`. +- Motion-enabled policy allows `goto` but no raw target or motor endpoints. +- Policy can be hot-reloaded without recreating the sandbox. +- Documentation states that JSON body values remain application-enforced. diff --git a/projects/reachy-mini-openshell/README.md b/projects/reachy-mini-openshell/README.md index 3900d7b8..64f92c9d 100644 --- a/projects/reachy-mini-openshell/README.md +++ b/projects/reachy-mini-openshell/README.md @@ -5,7 +5,9 @@ and single-frame camera capture; optional Gradio input; OpenAI Realtime; and a deliberately small REST-controlled action surface. > **Building the OpenShell policy demo with a physical Reachy?** Follow the -> [full step-by-step Reachy Mini OpenShell sandbox tutorial](../../docs/projects/reachy-mini-openshell-sandbox.md). +> [onboard setup tutorial](ONBOARD_SETUP.md). For the architecture, implementation +> decisions, and lessons learned, read the +> [Dev Note](../../docs/dev-notes/posts/2026-07-13-policy-controlling-reachy-mini-with-openshell.md). Commands: @@ -84,7 +86,8 @@ Inside an OpenShell sandbox, set the base URL to `http://host.openshell.internal:8000`. OpenShell can allow or deny `POST /api/move/goto`, but REST policy does not inspect the JSON pose values. The app therefore fixes the direction, pose, duration, and interpolation before -sending the request. See the sandbox tutorial for the exact security boundary. +sending the request. See the [onboard setup guide](ONBOARD_SETUP.md#security-boundary) +for the exact security boundary. For onboard snapshots, also set `REACHY_CAMERA_BASE_URL=http://host.openshell.internal:8042`. The trusted native diff --git a/zensical.toml b/zensical.toml index 2b69d5c0..a997e276 100644 --- a/zensical.toml +++ b/zensical.toml @@ -15,14 +15,14 @@ nav = [ {"Projects" = [ "projects/index.md", {"Reachy Mini + OpenShell" = [ - "projects/reachy-mini-openshell/index.md", - {"Step-by-step sandbox tutorial" = "projects/reachy-mini-openshell-sandbox.md"} + "projects/reachy-mini-openshell/index.md" ]} ]}, {"Dev Notes" = [ "dev-notes/index.md", {"Posts" = [ # dev-notes:nav:start + {"Designing OpenShell for the Edge: Why Policy Has to Live Next to the Action" = "dev-notes/posts/2026-07-13-policy-controlling-reachy-mini-with-openshell.md"}, {"Making Dev Notes Repeatable" = "dev-notes/posts/2026-06-05-making-dev-notes-repeatable.md"}, {"Bootstrapping OpenShell Research" = "dev-notes/posts/2026-06-04-bootstrapping-openshell-research.md"} # dev-notes:nav:end From 37813eb03f3eabc907c3d93b71d8cf93604da781 Mon Sep 17 00:00:00 2001 From: Kirit93 Date: Tue, 14 Jul 2026 11:35:45 -0700 Subject: [PATCH 30/45] Updated images in dev note --- .../diagrams/boundary-stack.svg | 68 +++++++++++ .../diagrams/request-flow.svg | 110 ++++++++++++++++++ ...-controlling-reachy-mini-with-openshell.md | 53 ++------- .../reachy-mini-openshell-demo-tutorial.md | 15 +++ docs/stylesheets/dev-notes.css | 28 +++++ 5 files changed, 229 insertions(+), 45 deletions(-) create mode 100644 docs/assets/reachy-mini-openshell/diagrams/boundary-stack.svg create mode 100644 docs/assets/reachy-mini-openshell/diagrams/request-flow.svg create mode 100644 docs/projects/reachy-mini-openshell-demo-tutorial.md diff --git a/docs/assets/reachy-mini-openshell/diagrams/boundary-stack.svg b/docs/assets/reachy-mini-openshell/diagrams/boundary-stack.svg new file mode 100644 index 00000000..d12cb404 --- /dev/null +++ b/docs/assets/reachy-mini-openshell/diagrams/boundary-stack.svg @@ -0,0 +1,68 @@ + + + + + + + + + + + + + ON-DEVICE BOUNDARY STACK + + + + + + + model I/O + request + if allowed + bounded action + + + + 1 + Cloud or local model + interprets the conversation, selects a tool + + + + 2 + Agent in an on-device OpenShell sandbox + turns intent into one concrete request + + + + 3 + Local OpenShell policy decision + allow or deny before it leaves the sandbox + CONTROL POINT + + + + 4 + Narrow trusted capability adapter + one bounded operation per capability + + + + 5 + Physical device, sensor, or local data + motors, camera, microphone, files + + Each boundary enforces one thing — and can be tested on its own. + diff --git a/docs/assets/reachy-mini-openshell/diagrams/request-flow.svg b/docs/assets/reachy-mini-openshell/diagrams/request-flow.svg new file mode 100644 index 00000000..508433c2 --- /dev/null +++ b/docs/assets/reachy-mini-openshell/diagrams/request-flow.svg @@ -0,0 +1,110 @@ + + + + + + + + + + + + + + + REQUEST FLOW ON REACHY + + + + Person near Reachy + speaks and listens + + + Trusted native Reachy App + microphone · speaker · camera + + + voice + + + + OPENSHELL SANDBOX + + Conversation agent + Realtime client + fixed tools + + Loopback audio + 127.0.0.1:8765 + + + OpenAI Realtime API + remote model + + + + PCM audio + + + + + policy-checked + WebSocket + + + + + POLICY DECISION + OpenShell gateway + policy engine + evaluates binary · destination · port · method · path + + + + robot REST request + + + + + ALLOWED + One-frame camera adapter + 127.0.0.1:8042 · POST /camera/capture + returns one bounded JPEG — Reachy describes it aloud + + + + DENIED + Reachy daemon → motors + 127.0.0.1:8000 · POST /api/move/goto + stopped at the boundary — the robot stays still + + + + capture + + + move + + + + + + The camera works and the head does not move — enforced by policy, not by the app choosing to refuse. + diff --git a/docs/dev-notes/posts/2026-07-13-policy-controlling-reachy-mini-with-openshell.md b/docs/dev-notes/posts/2026-07-13-policy-controlling-reachy-mini-with-openshell.md index 9d1e1843..8655803c 100644 --- a/docs/dev-notes/posts/2026-07-13-policy-controlling-reachy-mini-with-openshell.md +++ b/docs/dev-notes/posts/2026-07-13-policy-controlling-reachy-mini-with-openshell.md @@ -200,17 +200,10 @@ device execution into components with focused responsibilities. other local systems are reached only after the preceding boundaries allow it. -```text -cloud or local model - ↕ -agent in an on-device OpenShell sandbox - ↓ -local OpenShell policy decision - ↓ -narrow trusted capability adapter - ↓ -physical device, sensor, or local data -``` +
    + On-device boundary stack. Five boundaries connected top to bottom: a cloud or local model, the agent in an on-device OpenShell sandbox, the local OpenShell policy decision as the control point, a narrow trusted capability adapter, and the physical device, sensor, or local data. +
    Reasoning, policy enforcement, hardware ownership, and device execution are separated into distinct boundaries. The local OpenShell policy decision is the control point, evaluated on the device before a request can leave the sandbox.
    +
    This decomposition gives each boundary something specific to enforce and something specific to test. We can change the model without changing the robot @@ -337,40 +330,10 @@ model endpoint. ## What This Looks Like on Reachy -```mermaid -flowchart TB - Human["Person near Reachy"] - - subgraph Robot["Reachy Mini onboard computer"] - Native["Trusted native Reachy App\nmicrophone, speaker, camera"] - Gateway["OpenShell gateway\nand policy engine"] - - subgraph Sandbox["OpenShell sandbox"] - Agent["Conversation agent\nRealtime client and fixed tools"] - Audio["Loopback audio service\n127.0.0.1:8765"] - end - - Daemon["Reachy daemon REST API\n127.0.0.1:8000"] - Camera["One-frame adapter\n127.0.0.1:8042"] - Hardware["Mic, speaker, camera, motors"] - end - - Model["OpenAI Realtime API"] - - Human <-->|"voice"| Hardware - Native <-->|"Reachy media API"| Hardware - Native <-->|"PCM through exposed service"| Gateway - Gateway <--> Audio - Audio <--> Agent - Agent <-->|"policy-checked Realtime WebSocket"| Gateway - Gateway <--> Model - Agent -->|"robot REST action"| Gateway - Gateway -->|"permitted request"| Daemon - Daemon --> Hardware - Agent -->|"POST /camera/capture"| Gateway - Gateway --> Camera - Camera --> Native -``` +
    + Request flow on Reachy. The person speaks to the trusted native Reachy App, which streams PCM audio into the OpenShell sandbox, where the conversation agent exchanges policy-checked audio with the OpenAI Realtime API. Robot requests from the agent pass through the OpenShell gateway and policy engine, which allows the POST /camera/capture path to the one-frame camera adapter and denies the POST /api/move/goto path to the Reachy daemon and motors. +
    The same policy engine sits in front of both physical capabilities. It allows the camera capture path (green) and denies the movement path (red), so the camera works and the head does not move — enforced by policy rather than by the application choosing to refuse.
    +
    There is no laptop, browser, or Gradio page in the runtime path. The complete request flow is: diff --git a/docs/projects/reachy-mini-openshell-demo-tutorial.md b/docs/projects/reachy-mini-openshell-demo-tutorial.md new file mode 100644 index 00000000..2d4780f0 --- /dev/null +++ b/docs/projects/reachy-mini-openshell-demo-tutorial.md @@ -0,0 +1,15 @@ +# Reachy Mini + OpenShell: Dev Note and Setup Tutorial + +The original combined guide has been split into two focused documents: + +- Read **[Designing OpenShell for the Edge: Why Policy Has to Live Next to the + Action](../dev-notes/posts/2026-07-13-policy-controlling-reachy-mini-with-openshell.md)** + for the reusable edge architecture, design decisions, challenges, and results. +- Follow the **[project-local onboard setup + tutorial](https://github.com/NVIDIA/OpenShell-Research/blob/kirit93/reachy-implementation/projects/reachy-mini-openshell/ONBOARD_SETUP.md)** + for build, installation, validation, policy switching, and troubleshooting + commands. + +Keeping the tutorial next to the Dockerfile, policies, native controller, and +application source makes it easier to update the procedure whenever the +implementation changes. diff --git a/docs/stylesheets/dev-notes.css b/docs/stylesheets/dev-notes.css index 844f7653..43a7cdd2 100644 --- a/docs/stylesheets/dev-notes.css +++ b/docs/stylesheets/dev-notes.css @@ -377,3 +377,31 @@ body[data-md-color-scheme="slate"][data-md-color-primary="black"] { font-size: clamp(1.2rem, 8vw, 1.55rem); } } + +/* Dev note diagrams (SVG figures) */ +.dev-note-figure { + margin: 1.9rem auto; + text-align: center; +} + +.dev-note-figure img { + width: 100%; + max-width: 620px; + height: auto; + border-radius: 14px; + border: 1px solid var(--openshell-home-hero-border, rgba(0, 0, 0, 0.08)); + box-shadow: var(--openshell-card-shadow, 0 0.55rem 1.6rem rgba(15, 23, 42, 0.11)); + background: #ffffff; +} + +.dev-note-figure--wide img { + max-width: 820px; +} + +.dev-note-figure figcaption { + margin: 0.7rem auto 0; + max-width: 42rem; + font-size: 0.8rem; + line-height: 1.5; + color: var(--md-default-fg-color--light); +} From 9ae53dd268c3fe367de3522a2bf83ab269ce7f8a Mon Sep 17 00:00:00 2001 From: Kirit93 Date: Tue, 14 Jul 2026 11:47:16 -0700 Subject: [PATCH 31/45] Updated dev note --- ...-controlling-reachy-mini-with-openshell.md | 65 ++++++++++--------- 1 file changed, 35 insertions(+), 30 deletions(-) diff --git a/docs/dev-notes/posts/2026-07-13-policy-controlling-reachy-mini-with-openshell.md b/docs/dev-notes/posts/2026-07-13-policy-controlling-reachy-mini-with-openshell.md index 8655803c..f1610e32 100644 --- a/docs/dev-notes/posts/2026-07-13-policy-controlling-reachy-mini-with-openshell.md +++ b/docs/dev-notes/posts/2026-07-13-policy-controlling-reachy-mini-with-openshell.md @@ -44,9 +44,9 @@ working while the operator is out of the loop. That growing autonomy is the motivation behind OpenShell: the more an agent can change and act on its own, the less we can rely on guardrails implemented inside the same process. -OpenShell moves the control point outside the agent. The agent can remain -capable and autonomous inside a sandbox, while separately configured policy -governs its filesystem, process, network, and inference access. If the model is +OpenShell is a runtime that moves the control point outside the agent: it runs +the agent in a sandbox while a separately configured policy layer governs the +agent's filesystem, process, network, and inference access. If the model is prompt-injected, a tool is compromised, or the agent rewrites part of its own workflow, it still cannot grant itself permissions that the runtime has not allowed. @@ -58,15 +58,12 @@ longer limited to a bad shell command or leaked cloud credential. It can expose data that was supposed to remain on-site or cause an action with material real-world consequences. -That creates two immediate requirements. Some data should never leave the -device or the site where it was produced. Some actions should never be possible -in a particular deployment, even if a model, prompt, tool, skill, or application -update tries to request them. - -Trust at the edge therefore requires the OpenShell control plane to move with -the agent. The boundary must be deterministic, provisioned independently, and -enforced locally before data leaves the device or an action reaches the -hardware. +That creates two requirements. Some data should never leave the device or the +site where it was produced, and some actions should never be possible in a given +deployment, even if a model, prompt, tool, skill, or application update tries to +request them. Meeting both means the control plane has to move with the agent: a +boundary that is deterministic, provisioned independently, and enforced locally +before data leaves the device or an action reaches the hardware. We used Reachy Mini to explore what that deployment looks like. The resulting pattern keeps the agent in an on-device OpenShell sandbox, keeps hardware @@ -103,11 +100,10 @@ policy runtime such as OpenShell fits: it enforces those boundaries at the edge, independently of the agent's instructions or behavior. **Safety has to be enforced before action.** An inspection robot may use its -camera everywhere but move only inside a controlled workcell. A building agent -may read temperature data but not change a setpoint in a public deployment. A -field device may expose an emergency stop while route changes remain disabled. -The same software image can be paired with different policies for different -operating environments. +camera everywhere but move only inside a controlled workcell. The same software +image can be paired with different policies for different operating environments, +so what an agent is allowed to physically do becomes a deployment decision rather +than a property baked into the build. **Controls have to survive agent evolution.** Models change. Prompts are tuned. Tools are added. Application code is upgraded. A safety or privacy guarantee @@ -238,9 +234,8 @@ and paths permitted by its policy. A deployment can allow an approved remote model, route through a local privacy service, or deny remote model access and use an on-device endpoint instead. -This is the central edge property. The model may remain a cloud service, but -the authority to move local data and use local capabilities remains local. -Model placement and policy placement are independent choices. +This is the central edge property: the model may remain a cloud service, but the +authority to move local data and use local capabilities stays on the device. ### Expose capabilities, not complete APIs @@ -437,6 +432,12 @@ installation, and Reachy Apps Python environment can coexist temporarily. The robot needs several gigabytes free even though the final sandbox image is only about 339 MB. +**The policy hop is cheap next to the model round-trip.** Each robot request adds +one local policy evaluation on the same host as the agent and daemon — a match on +binary, destination, port, method, and path — which is small beside the network +round-trip to the Realtime model. The latency that mattered in practice was cold +start, not steady-state enforcement. + These details are easy to dismiss as deployment issues. On an edge product, they are part of the architecture because they determine whether the security boundary survives normal starts, updates, failures, and operator workflows. @@ -474,21 +475,25 @@ adapters. What generalizes is the placement of the boundary: the less-trusted agent runs inside the sandbox, and policy-approved requests cross into narrowly defined device capabilities. +This does not remove trust so much as concentrate it. The policy engine, the +trusted adapter, and the device controller are all still trusted code. The point +is where that trust sits: instead of a large, long-running, self-modifying agent +policing itself, the parts you have to trust are small, fixed, and auditable, and +they sit outside the component most likely to change. The goal is a minimal +trusted surface, not the absence of one. + --- ## Summary Running autonomous, evolving agents at the edge is a systems problem, not just -a container-build problem. The Reachy implementation reflects seven principles: - -1. Keep the final control point outside the agent process. -2. Put policy on the device, next to the data and actions it controls. -3. Give the agent narrow capabilities rather than a complete hardware API. -4. Keep hardware handles and native SDK objects in a small trusted process. -5. Separate operator provisioning from the product's Start/Stop lifecycle. -6. Treat CPU, memory, disk, networking, and cold-start time as architecture - inputs. -7. Keep model placement independent from the local action boundary. +a container-build problem. The Reachy implementation comes down to a few choices: +keep the final control point outside the agent and on the device, next to the +data and actions it governs; give the agent narrow capabilities instead of a +complete hardware API, with hardware handles kept in a small trusted process; +separate operator provisioning from the product's start/stop lifecycle; and treat +CPU, memory, disk, networking, cold-start time, and where the model runs as +architecture inputs rather than afterthoughts. The result is more than a policy-controlled robot demo. It is a deployment pattern in which OpenShell becomes the on-device isolation and policy layer for From 808336e88d418e36364d57d6fda87e47e21dba82 Mon Sep 17 00:00:00 2001 From: Kirit93 Date: Tue, 14 Jul 2026 13:11:56 -0700 Subject: [PATCH 32/45] Updated dev note voice --- .../diagrams/boundary-stack.svg | 2 +- .../diagrams/request-flow.svg | 6 +- ...-controlling-reachy-mini-with-openshell.md | 637 +++++++++--------- 3 files changed, 309 insertions(+), 336 deletions(-) diff --git a/docs/assets/reachy-mini-openshell/diagrams/boundary-stack.svg b/docs/assets/reachy-mini-openshell/diagrams/boundary-stack.svg index d12cb404..a904533a 100644 --- a/docs/assets/reachy-mini-openshell/diagrams/boundary-stack.svg +++ b/docs/assets/reachy-mini-openshell/diagrams/boundary-stack.svg @@ -64,5 +64,5 @@ Physical device, sensor, or local data motors, camera, microphone, files - Each boundary enforces one thing — and can be tested on its own. + Each boundary enforces one thing and can be tested on its own. diff --git a/docs/assets/reachy-mini-openshell/diagrams/request-flow.svg b/docs/assets/reachy-mini-openshell/diagrams/request-flow.svg index 508433c2..69d8056a 100644 --- a/docs/assets/reachy-mini-openshell/diagrams/request-flow.svg +++ b/docs/assets/reachy-mini-openshell/diagrams/request-flow.svg @@ -86,14 +86,14 @@ ALLOWED One-frame camera adapter 127.0.0.1:8042 · POST /camera/capture - returns one bounded JPEG — Reachy describes it aloud + returns one bounded JPEG, Reachy describes it aloud DENIED Reachy daemon → motors 127.0.0.1:8000 · POST /api/move/goto - stopped at the boundary — the robot stays still + stopped at the boundary, the robot stays still @@ -106,5 +106,5 @@ - The camera works and the head does not move — enforced by policy, not by the app choosing to refuse. + The camera works and the head does not move, enforced by policy, not by the app choosing to refuse. diff --git a/docs/dev-notes/posts/2026-07-13-policy-controlling-reachy-mini-with-openshell.md b/docs/dev-notes/posts/2026-07-13-policy-controlling-reachy-mini-with-openshell.md index f1610e32..1a8163dc 100644 --- a/docs/dev-notes/posts/2026-07-13-policy-controlling-reachy-mini-with-openshell.md +++ b/docs/dev-notes/posts/2026-07-13-policy-controlling-reachy-mini-with-openshell.md @@ -38,44 +38,42 @@ card_tags: -AI agents are moving from assistants that wait for instructions to long-running -systems that pursue goals, use tools, add skills, write code, and continue -working while the operator is out of the loop. That growing autonomy is the -motivation behind OpenShell: the more an agent can change and act on its own, -the less we can rely on guardrails implemented inside the same process. - -OpenShell is a runtime that moves the control point outside the agent: it runs -the agent in a sandbox while a separately configured policy layer governs the -agent's filesystem, process, network, and inference access. If the model is -prompt-injected, a tool is compromised, or the agent rewrites part of its own -workflow, it still cannot grant itself permissions that the runtime has not -allowed. - -At the edge, the same trust problem gains a physical dimension. An agent may -observe people and places, handle data from microphones, cameras, and sensors, -and make decisions that move machines or change local systems. A failure is no -longer limited to a bad shell command or leaked cloud credential. It can expose -data that was supposed to remain on-site or cause an action with material -real-world consequences. - -That creates two requirements. Some data should never leave the device or the -site where it was produced, and some actions should never be possible in a given -deployment, even if a model, prompt, tool, skill, or application update tries to -request them. Meeting both means the control plane has to move with the agent: a -boundary that is deterministic, provisioned independently, and enforced locally -before data leaves the device or an action reaches the hardware. - -We used Reachy Mini to explore what that deployment looks like. The resulting -pattern keeps the agent in an on-device OpenShell sandbox, keeps hardware -ownership in a small trusted native process, and enforces policy locally before -a request can cross into the rest of the device. +AI agents used to wait for instructions. Now they run for a long time, pursue +goals, call tools, add skills, write code, and keep working while no one is +watching. That is the problem OpenShell exists to solve: the more an agent can +change itself and act on its own, the less you can trust a guardrail that lives +inside the same process. + +OpenShell moves the control point outside the agent. It runs the agent in a +sandbox, and a separate policy layer decides what the agent can touch: its +filesystem, processes, network, and model access. If the model is +prompt-injected, a tool is compromised, or the agent rewrites its own workflow, +it still cannot give itself a permission the runtime did not grant. + +At the edge, this problem gets physical. An agent can watch people and places, +read microphones, cameras, and sensors, and take actions that move machines or +change local systems. A failure is no longer just a bad shell command or a +leaked credential. It can leak data that was supposed to stay on-site, or move +something in the real world. + +That creates two rules. Some data should never leave the device or the site +where it was produced. Some actions should never be possible in a given +deployment, even if a model, prompt, tool, skill, or update asks for them. To +enforce both, the control point has to sit on the device with the agent. It has +to be deterministic, set up separately from the agent, and checked locally +before any data leaves or any action reaches the hardware. + +We used Reachy Mini to see what that looks like in practice. The pattern keeps +the agent in an on-device OpenShell sandbox, keeps hardware ownership in a small +trusted process, and checks policy locally before any request reaches the rest +of the device. -This post walks through the design principles behind that architecture. Reachy -makes the result easy to see: the camera works and the head does not move. The -same boundaries apply to cameras, lab instruments, industrial gateways, -vehicles, kiosks, and other AI-enabled edge systems. +This post walks through the design behind that architecture. Reachy makes the +result easy to see: the camera works and the head does not move. The same +boundaries apply to lab instruments, industrial gateways, vehicles, kiosks, and +other AI-enabled edge systems. The copy-and-run installation procedure lives separately in the [onboard setup tutorial](https://github.com/NVIDIA/OpenShell-Research/blob/kirit93/reachy-implementation/projects/reachy-mini-openshell/ONBOARD_SETUP.md). @@ -84,242 +82,227 @@ The copy-and-run installation procedure lives separately in the ## Trust Has to Move with the Agent -The same agent might run in a factory, a laboratory, a warehouse, a retail -space, or a home. Each deployment has different data boundaries, physical -risks, operators, and acceptable actions. Security controls therefore have to -be applied where the device is running, not only where the model is hosted. - -**Privacy has to be enforced before egress.** A camera may be allowed to analyze -a scene locally but prohibited from sending raw video off-site. A microphone may -support an on-device interaction while recordings remain local. A lab instrument -may expose a derived result while its raw measurements and sample metadata never -leave the facility. These devices need deterministic enforcement of where -sensitive data can be handled: what must stay on the device, what approved -services may process, and what may leave the local environment. This is where a -policy runtime such as OpenShell fits: it enforces those boundaries at the edge, -independently of the agent's instructions or behavior. - -**Safety has to be enforced before action.** An inspection robot may use its -camera everywhere but move only inside a controlled workcell. The same software -image can be paired with different policies for different operating environments, -so what an agent is allowed to physically do becomes a deployment decision rather -than a property baked into the build. - -**Controls have to survive agent evolution.** Models change. Prompts are tuned. -Tools are added. Application code is upgraded. A safety or privacy guarantee -that exists only inside one prompt or one version of the tool implementation has -to be re-established after every change. A separately provisioned policy -boundary remains in force while the agent evolves behind it. - -Deterministic enforcement does not mean that OpenShell understands the meaning -of every image, measurement, motor command, or physical environment. It means -the agent is confined to explicit filesystem and network boundaries, and that -device-specific capabilities cross through narrow trusted interfaces that -policy can allow or deny. OpenShell decides whether the agent may call a -capability. The trusted adapter constrains what that call can request, and the -device controller enforces the hardware limits while executing it, such as -joint ranges, speed limits, and emergency-stop behavior. - -The current Reachy demo uses the OpenAI Realtime API through an explicitly -allowed WebSocket endpoint, so its conversation audio and requested camera frame -are sent to that approved service. A deployment with strict data-residency -requirements could instead permit a local model endpoint, an approved on-device -preprocessing service, or only derived data. The important point is that the -egress decision is made by local policy; it is not implied by where the model -happens to run. +The same agent might run in a factory, a lab, a warehouse, a store, or a home. +Each of those places has different data to protect, different physical risks, +different operators, and different actions it should allow. So the controls have +to live where the device runs, not only where the model is hosted. + +**Stop private data before it leaves.** A camera can analyze a scene on the +device but be blocked from sending raw video off-site. A microphone can drive a +local interaction while the recording stays put. A lab instrument can hand back +a result while its raw measurements never leave the building. Each case needs a +hard rule about where sensitive data can go: what stays on the device, what an +approved service may process, and what may leave. That rule is what OpenShell +enforces, and it holds no matter what the agent is told to do. + +**Enforce safety before the action, not after.** An inspection robot may use its +camera everywhere but move only inside a controlled workcell. That workcell +limit lives in the policy an operator applies at deployment, not in the image or +the agent's code, so the same build can ship to a test bench where movement is +open and to a production line where it is denied. + +**Controls have to outlast changes to the agent.** Models get swapped, prompts +get tuned, tools get added, code gets upgraded. A guarantee that lives in the +prompt or the tool code breaks the moment any of those change, so you have to +re-check it after every update. A guarantee that lives in policy outside the +agent does not. You can change the agent without touching it. + +None of this means OpenShell understands what an image shows or what a motor +command will do. It means the agent is boxed into set filesystem and network +limits, and that anything device-specific has to go through a narrow trusted +interface that policy can allow or deny. OpenShell decides whether the agent may +call a capability at all. The trusted adapter decides what that call is allowed +to ask for. The device controller enforces the hardware limits as it runs, such +as joint ranges, speed caps, and emergency stop. + +The Reachy demo talks to the OpenAI Realtime API over one allowed WebSocket +endpoint, so the conversation audio and the requested camera frame go to that +approved service. A deployment with strict data-residency rules could allow a +local model instead, or an approved on-device preprocessing service, or only +derived data. The point is that local policy decides what leaves. Where the +model runs does not. --- ## An Edge Agent Is Not Just a Smaller Deployment -The straightforward approach is to take an existing agent, run it on the -device, and give it access to the local SDK or REST API. That is enough for an -early prototype. The agent can call the model, invoke a tool, and make the -hardware respond. +The obvious approach is to take an agent, run it on the device, and hand it the +local SDK or REST API. That is fine for a prototype. The agent calls the model, +invokes a tool, and the hardware responds. -Simply removing device access is not a solution because the agent can no longer -do the job. Requiring a person to approve every camera capture or movement -makes the system safer, but gives up the autonomy that made the agent useful. -Giving the agent full local access preserves capability and autonomy, but leaves -a long-running, evolving process responsible for policing itself. +Taking device access away is not an option, because then the agent cannot do its +job. Making a person approve every camera capture or movement is safer, but it +throws away the autonomy that made the agent worth using. Giving the agent full +local access keeps the capability and the autonomy, but it leaves a long-running, +self-changing process in charge of policing itself. -The goal is to preserve all three properties: useful device capabilities, -meaningful autonomy, and controls the agent cannot rewrite. That requires an -enforcement layer outside the agent process. +We want all three at once: real device capability, real autonomy, and controls +the agent cannot rewrite. That only works if the enforcement sits outside the +agent. -The direct-SDK approach also collapses several different kinds of authority -into one process. +The direct-SDK approach also piles several kinds of authority into one process. -**The agent gets more device access than it needs.** A robot SDK may expose -motors, raw targets, camera configuration, recorded motions, application -management, and system state. A conversational agent that needs five fixed head -directions should not inherit that entire surface. +**The agent gets more access than it needs.** A robot SDK exposes motors, raw +targets, camera settings, recorded motions, app management, and system state. An +agent that needs five fixed head directions should not inherit all of that. -**Policy is too far from the effect.** A remote model provider can decide which -tool to call, but it should not be the final authority on whether a local motor, -camera, or actuator is used. That decision belongs on the device, immediately +**The decision is made too far from the effect.** A remote model can pick which +tool to call, but it should not be the last word on whether a local motor, +camera, or actuator actually moves. That call belongs on the device, right before the request reaches the controller. -**The product lifecycle and the agent lifecycle are different.** Operators -choose credentials, images, resource limits, and policy. Users start and stop -an application. Recreating the security boundary every time the app starts -mixes those responsibilities and gives the runtime more provisioning authority -than it needs. +**The product and the agent have different lifecycles.** Operators choose +credentials, images, resource limits, and policy. Users just start and stop the +app. Rebuilding the security boundary every time the app starts mixes those two +jobs and hands the runtime more setup authority than it should have. -**Edge resources change the architecture.** Disk, memory, cold-start time, -networking, and hardware ownership are not deployment footnotes on a small -device. They determine which processes can run, which dependencies belong in -the sandbox, and how the application should recover. +**Edge resources shape the design.** On a small device, disk, memory, cold-start +time, networking, and hardware ownership are not footnotes. They decide which +processes can run, which dependencies belong in the sandbox, and how the app +recovers when something fails. -These are not problems with robots or language models. They come from treating -an edge agent as a conventional application that happens to run on smaller -hardware. What we needed was a clearer system of boundaries. +None of these are robot problems or language-model problems. They come from +treating an edge agent like an ordinary app that happens to run on small +hardware. What it needs instead is a clear set of boundaries. --- ## An Edge Agent as a System of Boundaries -The shift is to separate reasoning, policy enforcement, hardware ownership, and -device execution into components with focused responsibilities. - -1. **The model reasons.** It interprets the conversation and selects from the - tools the application advertises. The model can be remote or local. -2. **The sandboxed agent turns intent into a concrete request.** It owns the - conversation state and model-facing tool logic, but it does not own the - hardware. -3. **OpenShell decides whether the request may leave the sandbox.** Policy is - evaluated on the edge device using the calling binary, destination, port, - HTTP method, path, and query. -4. **A trusted adapter exposes a narrow capability.** It owns native device - objects and translates an approved request into one bounded operation. -5. **The device controller produces the effect.** Motors, sensors, cameras, or - other local systems are reached only after the preceding boundaries allow - it. +The fix is to split reasoning, policy, hardware ownership, and device execution +into separate parts, each with one job. + +1. **The model reasons.** It reads the conversation and picks from the tools the + app offers. It can be remote or local. +2. **The sandboxed agent turns that choice into a concrete request.** It owns the + conversation state and the tool logic, but it does not own the hardware. +3. **OpenShell decides whether the request may leave the sandbox.** It checks the + request on the device against the calling binary, destination, port, HTTP + method, path, and query. +4. **A trusted adapter exposes one narrow capability.** It owns the native device + objects and turns an approved request into a single bounded operation. +5. **The device controller does the work.** Motors, sensors, and cameras are + reached only after every boundary above has allowed it.
    On-device boundary stack. Five boundaries connected top to bottom: a cloud or local model, the agent in an on-device OpenShell sandbox, the local OpenShell policy decision as the control point, a narrow trusted capability adapter, and the physical device, sensor, or local data.
    Reasoning, policy enforcement, hardware ownership, and device execution are separated into distinct boundaries. The local OpenShell policy decision is the control point, evaluated on the device before a request can leave the sandbox.
    -This decomposition gives each boundary something specific to enforce and -something specific to test. We can change the model without changing the robot -adapter. We can change the policy without rebuilding the image. We can restart -the application without recreating credentials or resource limits. And we can -test the allowed camera path independently from the denied movement path. - -The sandbox starts from deny-by-default policy rather than inheriting every -capability available on the host. When Reachy hits a denied action, the agent -receives a structured failure and can explain the constraint instead of silently -bypassing it. An operator can then update the sandbox policy without rebuilding -the application, while the decision to grant new authority remains outside the -agent. +Each boundary now has one thing to enforce and one thing to test. You can change +the model without touching the robot adapter. You can change the policy without +rebuilding the image. You can restart the app without recreating credentials or +resource limits. And you can test the allowed camera path on its own, separate +from the denied movement path. + +The sandbox starts with deny-by-default policy instead of inheriting everything +the host can do. When Reachy hits a denied action, the agent gets a clear error +it can explain out loud, rather than quietly working around it. An operator can +change the policy without rebuilding the app, and the power to grant new +authority stays outside the agent. --- ## Design Principles Behind OpenShell at the Edge -With that framing in place, these are the principles that shaped the Reachy -implementation. +With that in place, here are the principles that shaped the Reachy build. ### Put policy next to the data and the effect -The policy engine runs on the same Reachy onboard computer as the agent and -robot daemon. When the agent attempts a movement request, OpenShell decides -locally whether that request can reach the daemon. A denial stops at the policy -boundary; it does not depend on the remote model deciding to withdraw the tool -call. +The policy engine runs on the same Reachy computer as the agent and the robot +daemon. When the agent tries to move the robot, OpenShell decides right there +whether the request reaches the daemon. A denial stops at the policy boundary. +It does not wait for the remote model to change its mind about the tool call. -The same boundary controls egress. The sandbox can connect only to destinations -and paths permitted by its policy. A deployment can allow an approved remote -model, route through a local privacy service, or deny remote model access and +The same boundary controls what leaves. The sandbox can only reach the +destinations and paths its policy allows. A deployment can allow an approved +remote model, route through a local privacy service, or block remote models and use an on-device endpoint instead. -This is the central edge property: the model may remain a cloud service, but the -authority to move local data and use local capabilities stays on the device. +This is the whole point at the edge: the model can stay in the cloud, but the +power to move local data and use local hardware stays on the device. ### Expose capabilities, not complete APIs -The conversation agent receives three robot tools: +The agent gets three robot tools: - `move_head(directions)` accepts `left`, `right`, `up`, `down`, and `front`. - `stop_motion()` stops active movements. - `camera(question)` requests one image for the current conversation. -The model selects one of those tools; it does not construct an HTTP request -itself. Python handlers inside the sandbox translate `move_head` into -`POST /api/move/goto`, `stop_motion` into `POST /api/move/stop`, and `camera` -into `POST /camera/capture`. OpenShell then evaluates the concrete request before -it can leave the sandbox. +The model picks one of these tools. It does not build the HTTP request itself. +Python handlers in the sandbox turn `move_head` into `POST /api/move/goto`, +`stop_motion` into `POST /api/move/stop`, and `camera` into +`POST /camera/capture`. OpenShell then checks that concrete request before it can +leave the sandbox. -The agent does not discover the complete Reachy API. Fixed tool inputs become -fixed REST requests, making the intended capability visible at the network -boundary. This is easier to reason about than giving an agent a general-purpose -SDK and trying to enumerate every unsafe combination afterward. +The agent never sees the full Reachy API. Fixed tool inputs become fixed REST +requests, so the capability you meant to grant is visible right at the network +boundary. That is much easier to reason about than handing the agent a +general-purpose SDK and trying to list every unsafe combination after the fact. ### Keep hardware handles in trusted native code -Reachy's microphone, speaker, and camera are already managed by its native app -lifecycle. Moving those objects into the sandbox would duplicate hardware -ownership and pull the full Reachy SDK, media stack, and vision dependencies -into the agent image. +Reachy's native app already owns the microphone, speaker, and camera. Moving +those into the sandbox would split hardware ownership in two and drag the full +Reachy SDK, media stack, and vision dependencies into the agent image. -Instead, a small trusted Reachy App owns the native media objects. It forwards -PCM audio through a local WebSocket and exposes one argument-free camera route: -`POST /camera/capture`. The sandbox gets the capability to converse and request -one frame; it does not get the camera handle, device selection, resolution -controls, or a filesystem path. +Instead, a small trusted Reachy App keeps the media objects. It forwards PCM +audio over a local WebSocket and exposes one camera route with no arguments: +`POST /camera/capture`. The sandbox can hold a conversation and ask for one +frame. It never gets the camera handle, the device choice, the resolution +controls, or a file path. ### Provision once, operate many times -Creating a sandbox chooses the image, provider, credentials, filesystem policy, +Creating a sandbox sets the image, provider, credentials, filesystem policy, network policy, CPU limit, and memory limit. Those are operator decisions, so -the native Reachy App does not create or delete the sandbox. +the native Reachy App does not create or delete the sandbox at all. -The model credential is configured through the OpenShell provider and attached -at provisioning time; it is not baked into the Docker image, policy file, or -native controller. The normal Reachy application lifecycle never asks for or -recreates that credential boundary. +The model credential is set through the OpenShell provider and attached when the +sandbox is created. It is not baked into the Docker image, the policy file, or +the native controller. Starting and stopping the app never touches that +credential boundary. -The sandbox remains provisioned while `reachy-agent-control start|stop|status` -manages the conversation process inside it. Starting the Reachy App verifies -the sandbox, starts the agent, exposes the audio route, and connects media. -Stopping the app closes media and stops the agent process. The policy and -provider remain intact for the next start. +The sandbox stays put while `reachy-agent-control start|stop|status` manages the +conversation process inside it. Starting the Reachy App checks the sandbox, +starts the agent, opens the audio route, and connects media. Stopping it closes +media and stops the agent. The policy and provider are still there for the next +start. ### Treat resource constraints as design inputs -The tested Reachy had 3.7 GiB usable RAM, 2 GiB swap, and a 14 GiB root -partition. We gave the sandbox a 2 CPU and 2 GiB memory ceiling and built the -image on a development machine rather than consuming the robot's CPU, memory, -and microSD write budget. +The Reachy we tested had 3.7 GiB of usable RAM, 2 GiB of swap, and a 14 GiB root +partition. We capped the sandbox at 2 CPUs and 2 GiB of memory, and we built the +image on a dev machine instead of spending the robot's CPU, memory, and microSD +write budget on it. -The runtime image uses a slim Python base, a disposable wheel-building stage, -a REST-only dependency list, and an application install with `--no-deps`. That -keeps the Reachy SDK, MuJoCo, OpenCV, simulator, dance, and local vision stacks -out of the sandbox. The resulting ARM64 image was 339,495,096 bytes, or about -339 MB, while retaining the networking tools OpenShell requires. +The runtime image uses a slim Python base, a throwaway wheel-building stage, a +REST-only dependency list, and an install with `--no-deps`. That keeps the +Reachy SDK, MuJoCo, OpenCV, the simulator, the dance stack, and local vision out +of the sandbox. The final ARM64 image came to 339,495,096 bytes, about 339 MB, +and still includes the networking tools OpenShell needs. ### Design for both remote and local models -The demonstrated Realtime model is remote. The conversation, policy, device -adapter, and robot controller still run on Reachy. This matters because “edge” -does not have to mean “fully offline,” and local enforcement does not require a -local foundation model. +The Realtime model in the demo is remote. The conversation, policy, device +adapter, and robot controller all still run on Reachy. That matters, because edge +does not have to mean fully offline, and local enforcement does not need a local +model. -The same architecture can later use an on-device model. The model endpoint -changes; the sandbox, trusted adapter, and local action boundary do not. +The same setup can later use an on-device model. Only the model endpoint changes. +The sandbox, the trusted adapter, and the local action boundary stay the same. -The current policy explicitly allows the chat application to connect to one -OpenAI Realtime endpoint. It does not provide content-aware privacy enforcement, -but it establishes the egress boundary needed to add it. +Today's policy allows the chat app to reach one OpenAI Realtime endpoint. It does +not inspect the content for privacy yet, but it sets up the egress boundary you +would need to add that. -A privacy-focused deployment could deny direct model access and make an -OpenShell Middleware service the sandbox's only permitted model destination. -Privacy Guard, which is on the OpenShell roadmap, could use that service to -detect sensitive camera, microphone, or sensor data and decide whether to block -it, redact it, process it locally, or route it to an approved model. The agent -would not be able to bypass that decision by connecting directly to another -model endpoint. +A privacy-focused deployment could block direct model access and make an +OpenShell Middleware service the only model destination the sandbox can reach. +Privacy Guard, which is on the OpenShell roadmap, could use that service to spot +sensitive camera, microphone, or sensor data and decide whether to block it, +redact it, handle it locally, or send it to an approved model. The agent could +not get around that by connecting straight to another model endpoint. --- @@ -327,187 +310,177 @@ model endpoint.
    Request flow on Reachy. The person speaks to the trusted native Reachy App, which streams PCM audio into the OpenShell sandbox, where the conversation agent exchanges policy-checked audio with the OpenAI Realtime API. Robot requests from the agent pass through the OpenShell gateway and policy engine, which allows the POST /camera/capture path to the one-frame camera adapter and denies the POST /api/move/goto path to the Reachy daemon and motors. -
    The same policy engine sits in front of both physical capabilities. It allows the camera capture path (green) and denies the movement path (red), so the camera works and the head does not move — enforced by policy rather than by the application choosing to refuse.
    +
    The same policy engine sits in front of both physical capabilities. It allows the camera capture path (green) and denies the movement path (red), so the camera works and the head does not move, enforced by policy rather than by the application choosing to refuse.
    -There is no laptop, browser, or Gradio page in the runtime path. The complete +There is no laptop, browser, or Gradio page in the runtime path. The full request flow is: 1. The trusted Reachy App captures microphone audio and streams PCM frames to - the audio service inside the sandbox. -2. The conversation agent sends that audio over its policy-approved WebSocket - connection to the OpenAI Realtime API. The model receives the conversation - together with the fixed `move_head`, `stop_motion`, and `camera` tool - definitions. -3. The model returns response audio or selects a tool. For a tool call, Python - code in the sandbox translates the model's arguments into one of the fixed - REST requests. -4. OpenShell evaluates the destination, port, method, and path. An allowed - request reaches the trusted adapter or Reachy daemon. A denied request returns - a policy error without reaching the hardware. -5. The conversation agent uses the tool result or policy error to continue the - conversation, and response audio travels back through the native Reachy App - to the robot's speaker. - -The active demo policy separates two physical capabilities: + the audio service in the sandbox. +2. The agent sends that audio to the OpenAI Realtime API over its + policy-approved WebSocket. The model gets the conversation along with the + fixed `move_head`, `stop_motion`, and `camera` tools. +3. The model returns audio or picks a tool. For a tool call, Python code in the + sandbox turns the model's arguments into one of the fixed REST requests. +4. OpenShell checks the destination, port, method, and path. An allowed request + reaches the trusted adapter or the Reachy daemon. A denied request comes back + as a policy error and never reaches the hardware. +5. The agent uses the tool result or the policy error to keep talking, and the + response audio goes back through the native Reachy App to the speaker. + +The demo policy splits two physical capabilities: ```text POST host.openshell.internal:8042/camera/capture allowed POST host.openshell.internal:8000/api/move/goto denied ``` -When a person says, “Take a picture of me,” the agent calls `camera`, OpenShell +When someone says, "Take a picture of me," the agent calls `camera`, OpenShell allows the capture path, the trusted adapter returns one bounded JPEG, and Reachy describes it aloud. -When the person says, “Turn right and take a picture,” the agent attempts -`POST /api/move/goto`. OpenShell returns a denial before the request reaches the -Reachy daemon. The robot stays still, and the denial becomes part of Reachy's -spoken response. +When they say, "Turn right and take a picture," the agent tries +`POST /api/move/goto`. OpenShell denies it before it reaches the Reachy daemon. +The robot stays still, and it says so out loud. -The important distinction is that the application is not simply choosing to -refuse movement. The model-facing process attempts a real action, and a -separately configured policy boundary prevents the physical effect. +The key point is that the app is not just choosing not to move. The agent makes +a real attempt to move, and a separate policy boundary stops the physical +effect. --- ## Why Narrow Endpoints Matter OpenShell's REST policy can match the calling binary, destination, method, -path, and query. It does not currently enforce arbitrary values nested inside a -JSON request body. If a broad endpoint can express many operations, allowing -that path also allows the sandbox to submit any body accepted by that endpoint. - -Reachy's fixed direction-to-pose mapping reduces normal model behavior to five -known poses, but that mapping is application validation rather than OpenShell -policy. The camera path has a stronger boundary because the request has no -model-controlled camera settings. The adapter chooses the already-open camera, -captures one JPEG, limits its size, rate-limits requests, and writes nothing to -disk. - -We intentionally stopped at REST method and path enforcement to keep the demo -small. OpenShell also supports generic JSON-RPC method rules. A next step could -add a small trusted JSON-RPC adapter that exposes semantic methods such as -`reachy.look_up` and `reachy.turn_right`. Policy could then allow or deny those -methods independently instead of treating every head movement as the same -`POST /api/move/goto` capability. - -Generic JSON-RPC policy currently matches the method, not arbitrary values in -`params`. Restrictions on angle, speed, distance, or duration would therefore -remain in the trusted adapter or device controller until OpenShell adds argument -matching. The JSON-RPC adapter would improve action-level policy granularity, -but it would not replace hardware safety validation. - -The same approach applies elsewhere. Rather than expose a broad control API, -an edge integration can define paths such as `/inspection/capture`, -`/instrument/read`, `/vehicle/emergency-stop`, or `/alarm/acknowledge`. The -trusted adapter defines exactly what each operation means, and OpenShell gains -a narrow capability it can allow or deny. +path, and query. It does not yet check arbitrary values inside a JSON body. So +if one endpoint can do many things, allowing that path also lets the sandbox +send any body that endpoint accepts. + +Reachy maps each direction to one of five fixed poses, but that check lives in +the app, not in OpenShell policy. The camera path has a tighter boundary, +because the request carries no camera settings the model can control. The +adapter uses the camera that is already open, captures one JPEG, caps its size, +rate-limits requests, and writes nothing to disk. + +We stopped at REST method and path checks on purpose, to keep the demo small. +OpenShell also supports JSON-RPC method rules. A next step would be a small +trusted JSON-RPC adapter that exposes named methods like `reachy.look_up` and +`reachy.turn_right`. Policy could then allow or deny each one on its own, +instead of treating every head movement as the same `POST /api/move/goto`. + +JSON-RPC policy matches the method today, not the values in `params`. So limits +on angle, speed, distance, or duration would still live in the trusted adapter +or the device controller until OpenShell can match arguments. The JSON-RPC +adapter would make action-level policy finer, but it would not replace hardware +safety checks. + +The same idea works elsewhere. Instead of exposing a broad control API, an edge +integration can define paths like `/inspection/capture`, `/instrument/read`, +`/vehicle/emergency-stop`, or `/alarm/acknowledge`. The trusted adapter says +exactly what each one does, and OpenShell gets a narrow capability it can allow +or deny. --- ## What We Learned Bringing It Onto the Robot -The move from a development machine to a small onboard computer exposed several -assumptions that the final architecture had to make explicit. - -**A persistent product needs a persistent sandbox.** Starting a sandbox with a -one-shot command caused the container to exit and restart. The final image stays -alive with `sleep infinity`, while the Reachy lifecycle starts and stops only -the inner agent process. - -**A service definition is not the same as a healthy service.** The audio route -could exist before the sandbox listener was ready. The native app now starts -the listener, verifies health, and only then ensures the OpenShell service route -is available. - -**Cold starts on edge hardware need realistic timeouts.** Importing and starting -the audio stack took roughly 41 seconds on the tested robot. A 120-second health -window handles the first start without hiding a process that never becomes -healthy. - -**Storage needs installation headroom, not just runtime headroom.** The -compressed archive, expanded image, Docker extraction layers, OpenShell -installation, and Reachy Apps Python environment can coexist temporarily. The -robot needs several gigabytes free even though the final sandbox image is only -about 339 MB. - -**The policy hop is cheap next to the model round-trip.** Each robot request adds -one local policy evaluation on the same host as the agent and daemon — a match on -binary, destination, port, method, and path — which is small beside the network +Moving from a dev machine to a small onboard computer forced several assumptions +into the open. + +**A persistent product needs a persistent sandbox.** Starting the sandbox with a +one-shot command made the container exit and restart. The final image stays +alive with `sleep infinity`, and the Reachy lifecycle starts and stops only the +agent process inside it. + +**A defined service is not a healthy service.** The audio route could exist +before the sandbox listener was ready. The native app now starts the listener, +checks that it is healthy, and only then brings up the OpenShell service route. + +**Cold starts on edge hardware need real timeouts.** Loading and starting the +audio stack took about 41 seconds on the robot we tested. A 120-second health +window covers the first start without masking a process that never comes up. + +**Storage needs room to install, not just room to run.** The compressed archive, +the expanded image, the Docker layers, the OpenShell install, and the Reachy +Apps Python environment can all sit on disk at once for a while. The robot needs +several gigabytes free even though the final image is only about 339 MB. + +**The policy check is cheap next to the model round-trip.** Each robot request +adds one local policy check on the same host as the agent and daemon (a match on +binary, destination, port, method, and path), which is tiny next to the network round-trip to the Realtime model. The latency that mattered in practice was cold -start, not steady-state enforcement. +start, not the check itself. -These details are easy to dismiss as deployment issues. On an edge product, -they are part of the architecture because they determine whether the security -boundary survives normal starts, updates, failures, and operator workflows. +It is easy to write these off as deployment details. On an edge product they are +part of the architecture, because they decide whether the security boundary +survives normal starts, updates, failures, and operator workflows. --- ## What This Pattern Makes Possible -Reachy is one concrete system, but its components map cleanly to other edge -applications. +Reachy is one system, but its parts map cleanly onto other edge applications. **Industrial inspection.** An agent can read sensors and capture evidence while -policy denies production-line or actuator changes. +policy blocks production-line and actuator changes. **Smart cameras.** An agent can describe a scene and send an approved alert -while continuous streaming, PTZ movement, and arbitrary upload destinations -remain unavailable. +while continuous streaming, PTZ movement, and arbitrary upload targets stay +off-limits. -**Lab instruments.** An agent can read measurements and prepare a run while -calibration, parameter changes, start, and stop remain separate policy-controlled -operations. +**Lab instruments.** An agent can read measurements and set up a run while +calibration, parameter changes, start, and stop stay as separate +policy-controlled actions. -**Field robots and vehicles.** Telemetry and camera access can remain distinct +**Field robots and vehicles.** Telemetry and camera access can stay separate from navigation, docking, route changes, and payload controls. -**Building-control gateways.** Read-only diagnosis can be separated from HVAC +**Building-control gateways.** Read-only diagnosis can stay separate from HVAC setpoints, doors, alarms, and maintenance actions. **Kiosks and local data appliances.** Microphone, speaker, approved peripherals, -local data, and outbound services can each have their own boundary. +local data, and outbound services can each get their own boundary. -OpenShell does not infer the safety semantics of a motor, valve, instrument, or -door. Each product still needs domain-specific safety engineering and trusted -adapters. What generalizes is the placement of the boundary: the less-trusted -agent runs inside the sandbox, and policy-approved requests cross into narrowly -defined device capabilities. +OpenShell does not know what a motor, valve, instrument, or door will do. Every +product still needs its own safety engineering and trusted adapters. What carries +over is where the boundary sits: the less-trusted agent runs in the sandbox, and +only policy-approved requests cross into a small set of clearly defined device +capabilities. -This does not remove trust so much as concentrate it. The policy engine, the -trusted adapter, and the device controller are all still trusted code. The point -is where that trust sits: instead of a large, long-running, self-modifying agent -policing itself, the parts you have to trust are small, fixed, and auditable, and -they sit outside the component most likely to change. The goal is a minimal -trusted surface, not the absence of one. +This does not remove trust. It concentrates it. The policy engine, the trusted +adapter, and the device controller are all still trusted code. What changes is +where that trust sits. Instead of a large, long-running agent that rewrites +itself and polices itself, the parts you have to trust are small, fixed, and +easy to audit, and they sit outside the piece most likely to change. The goal is +a small trusted surface, not none at all. --- ## Summary -Running autonomous, evolving agents at the edge is a systems problem, not just -a container-build problem. The Reachy implementation comes down to a few choices: +Running autonomous, self-changing agents at the edge is a systems problem, not +just a container-build problem. The Reachy build comes down to a few choices: keep the final control point outside the agent and on the device, next to the -data and actions it governs; give the agent narrow capabilities instead of a -complete hardware API, with hardware handles kept in a small trusted process; -separate operator provisioning from the product's start/stop lifecycle; and treat -CPU, memory, disk, networking, cold-start time, and where the model runs as -architecture inputs rather than afterthoughts. +data and actions it governs; give the agent narrow capabilities instead of a full +hardware API, and keep the hardware handles in a small trusted process; separate +operator setup from the product's start and stop; and treat CPU, memory, disk, +networking, cold-start time, and where the model runs as design inputs, not +afterthoughts. The result is more than a policy-controlled robot demo. It is a deployment -pattern in which OpenShell becomes the on-device isolation and policy layer for -autonomous AI-enabled edge systems. As future agent versions gain new models, -prompts, tools, and skills inside the sandbox, those changes do not automatically -widen their authority over the device. Reachy makes the pattern visible: the -same agent can use the camera, attempt movement, be denied locally, and explain -that denial to the person standing in front of it. - -Moving from this reference implementation to production would add fleet-level +pattern where OpenShell is the on-device isolation and policy layer for +autonomous edge systems. As later versions of the agent get new models, prompts, +tools, and skills inside the sandbox, none of that widens their power over the +device on its own. Reachy makes it visible: the same agent can use the camera, +try to move, be denied on the device, and explain that denial to the person in +front of it. + +Going from this reference implementation to production would add fleet-wide policy distribution, signed and attested images, bounded logs, structured audit -correlation, over-the-air updates, explicit offline behavior, and -safety-specific adapters for each class of hardware. Those are the next systems -problems around a boundary that now works on real edge hardware. +trails, over-the-air updates, defined offline behavior, and safety-specific +adapters for each kind of hardware. Those are the next problems to solve around a +boundary that already works on real edge hardware. Key resources: From 95a17f58c65df19166d92e70346cb7574ec84871 Mon Sep 17 00:00:00 2001 From: Kirit93 Date: Thu, 16 Jul 2026 08:35:42 -0700 Subject: [PATCH 33/45] Updated dev note --- .../diagrams/request-flow.svg | 4 +- .../screenshots/gradio-home.png | Bin 27027 -> 0 bytes ...-controlling-reachy-mini-with-openshell.md | 269 +++++++----------- 3 files changed, 102 insertions(+), 171 deletions(-) delete mode 100644 docs/assets/reachy-mini-openshell/screenshots/gradio-home.png diff --git a/docs/assets/reachy-mini-openshell/diagrams/request-flow.svg b/docs/assets/reachy-mini-openshell/diagrams/request-flow.svg index 69d8056a..64f88fdc 100644 --- a/docs/assets/reachy-mini-openshell/diagrams/request-flow.svg +++ b/docs/assets/reachy-mini-openshell/diagrams/request-flow.svg @@ -1,5 +1,5 @@ + aria-label="Reachy request flow: audio moves from the person through the trusted native app into the sandboxed agent and the OpenAI Realtime model; robot requests pass through the OpenShell gateway, which allows the camera capture path and denies the movement path."> Request flow on Reachy. The person speaks to the trusted native Reachy App, which streams PCM audio into the OpenShell sandbox, where the conversation agent exchanges policy-checked audio with the OpenAI Realtime API. Robot requests from the agent pass through the OpenShell gateway and policy engine, which allows the POST /camera/capture path to the one-frame camera adapter and denies the POST /api/move/goto path to the Reachy daemon and motors. -
    The same policy engine sits in front of both physical capabilities. It allows the camera capture path (green) and denies the movement path (red), so the camera works and the head does not move, enforced by policy rather than by the application choosing to refuse.
    + Request flow on Reachy. The person speaks to the trusted native Reachy App, which streams PCM audio into the OpenShell sandbox, where the conversation agent exchanges policy-checked audio with the OpenAI Realtime API. Robot requests from the agent pass through the OpenShell gateway, which allows the POST /camera/capture path to the one-frame camera adapter and denies the POST /api/move/goto path to the Reachy daemon and motors. +
    The same OpenShell gateway sits in front of both physical capabilities. It allows the camera capture path (green) and denies the movement path (red), so the camera works and the head does not move, enforced by policy rather than by the application choosing to refuse.
    There is no laptop, browser, or Gradio page in the runtime path. The full @@ -350,39 +370,6 @@ effect. --- -## Why Narrow Endpoints Matter - -OpenShell's REST policy can match the calling binary, destination, method, -path, and query. It does not yet check arbitrary values inside a JSON body. So -if one endpoint can do many things, allowing that path also lets the sandbox -send any body that endpoint accepts. - -Reachy maps each direction to one of five fixed poses, but that check lives in -the app, not in OpenShell policy. The camera path has a tighter boundary, -because the request carries no camera settings the model can control. The -adapter uses the camera that is already open, captures one JPEG, caps its size, -rate-limits requests, and writes nothing to disk. - -We stopped at REST method and path checks on purpose, to keep the demo small. -OpenShell also supports JSON-RPC method rules. A next step would be a small -trusted JSON-RPC adapter that exposes named methods like `reachy.look_up` and -`reachy.turn_right`. Policy could then allow or deny each one on its own, -instead of treating every head movement as the same `POST /api/move/goto`. - -JSON-RPC policy matches the method today, not the values in `params`. So limits -on angle, speed, distance, or duration would still live in the trusted adapter -or the device controller until OpenShell can match arguments. The JSON-RPC -adapter would make action-level policy finer, but it would not replace hardware -safety checks. - -The same idea works elsewhere. Instead of exposing a broad control API, an edge -integration can define paths like `/inspection/capture`, `/instrument/read`, -`/vehicle/emergency-stop`, or `/alarm/acknowledge`. The trusted adapter says -exactly what each one does, and OpenShell gets a narrow capability it can allow -or deny. - ---- - ## What We Learned Bringing It Onto the Robot Moving from a dev machine to a small onboard computer forced several assumptions @@ -418,69 +405,13 @@ survives normal starts, updates, failures, and operator workflows. --- -## What This Pattern Makes Possible - -Reachy is one system, but its parts map cleanly onto other edge applications. - -**Industrial inspection.** An agent can read sensors and capture evidence while -policy blocks production-line and actuator changes. - -**Smart cameras.** An agent can describe a scene and send an approved alert -while continuous streaming, PTZ movement, and arbitrary upload targets stay -off-limits. - -**Lab instruments.** An agent can read measurements and set up a run while -calibration, parameter changes, start, and stop stay as separate -policy-controlled actions. - -**Field robots and vehicles.** Telemetry and camera access can stay separate -from navigation, docking, route changes, and payload controls. - -**Building-control gateways.** Read-only diagnosis can stay separate from HVAC -setpoints, doors, alarms, and maintenance actions. - -**Kiosks and local data appliances.** Microphone, speaker, approved peripherals, -local data, and outbound services can each get their own boundary. - -OpenShell does not know what a motor, valve, instrument, or door will do. Every -product still needs its own safety engineering and trusted adapters. What carries -over is where the boundary sits: the less-trusted agent runs in the sandbox, and -only policy-approved requests cross into a small set of clearly defined device -capabilities. - -This does not remove trust. It concentrates it. The policy engine, the trusted -adapter, and the device controller are all still trusted code. What changes is -where that trust sits. Instead of a large, long-running agent that rewrites -itself and polices itself, the parts you have to trust are small, fixed, and -easy to audit, and they sit outside the piece most likely to change. The goal is -a small trusted surface, not none at all. - ---- +## Conclusion -## Summary - -Running autonomous, self-changing agents at the edge is a systems problem, not -just a container-build problem. The Reachy build comes down to a few choices: -keep the final control point outside the agent and on the device, next to the -data and actions it governs; give the agent narrow capabilities instead of a full -hardware API, and keep the hardware handles in a small trusted process; separate -operator setup from the product's start and stop; and treat CPU, memory, disk, -networking, cold-start time, and where the model runs as design inputs, not -afterthoughts. - -The result is more than a policy-controlled robot demo. It is a deployment -pattern where OpenShell is the on-device isolation and policy layer for -autonomous edge systems. As later versions of the agent get new models, prompts, -tools, and skills inside the sandbox, none of that widens their power over the -device on its own. Reachy makes it visible: the same agent can use the camera, -try to move, be denied on the device, and explain that denial to the person in -front of it. - -Going from this reference implementation to production would add fleet-wide -policy distribution, signed and attested images, bounded logs, structured audit -trails, over-the-air updates, defined offline behavior, and safety-specific -adapters for each kind of hardware. Those are the next problems to solve around a -boundary that already works on real edge hardware. +None of this is specific to Reachy. The same approach fits inspection robots, +smart cameras, lab instruments, field vehicles, building gateways, and kiosks. In each one, the agent can read sensors and describe what it sees, while +anything with a real consequence has to be approved by a policy first: moving an actuator, +changing a setpoint, or sending raw data off the device. We see this as a pattern for using OpenShell to bring security and trust to +autonomous edge systems. Key resources: From 8c7ebaeea7220f0629cb82fcd7358ea42ed666b3 Mon Sep 17 00:00:00 2001 From: Kirit93 Date: Thu, 16 Jul 2026 13:46:03 -0700 Subject: [PATCH 34/45] Updated blog --- ...-controlling-reachy-mini-with-openshell.md | 51 +++++-------------- 1 file changed, 13 insertions(+), 38 deletions(-) diff --git a/docs/dev-notes/posts/2026-07-13-policy-controlling-reachy-mini-with-openshell.md b/docs/dev-notes/posts/2026-07-13-policy-controlling-reachy-mini-with-openshell.md index 66eada02..4fb2362f 100644 --- a/docs/dev-notes/posts/2026-07-13-policy-controlling-reachy-mini-with-openshell.md +++ b/docs/dev-notes/posts/2026-07-13-policy-controlling-reachy-mini-with-openshell.md @@ -370,47 +370,22 @@ effect. --- -## What We Learned Bringing It Onto the Robot - -Moving from a dev machine to a small onboard computer forced several assumptions -into the open. - -**A persistent product needs a persistent sandbox.** Starting the sandbox with a -one-shot command made the container exit and restart. The final image stays -alive with `sleep infinity`, and the Reachy lifecycle starts and stops only the -agent process inside it. - -**A defined service is not a healthy service.** The audio route could exist -before the sandbox listener was ready. The native app now starts the listener, -checks that it is healthy, and only then brings up the OpenShell service route. - -**Cold starts on edge hardware need real timeouts.** Loading and starting the -audio stack took about 41 seconds on the robot we tested. A 120-second health -window covers the first start without masking a process that never comes up. - -**Storage needs room to install, not just room to run.** The compressed archive, -the expanded image, the Docker layers, the OpenShell install, and the Reachy -Apps Python environment can all sit on disk at once for a while. The robot needs -several gigabytes free even though the final image is only about 339 MB. - -**The policy check is cheap next to the model round-trip.** Each robot request -adds one local policy check on the same host as the agent and daemon (a match on -binary, destination, port, method, and path), which is tiny next to the network -round-trip to the Realtime model. The latency that mattered in practice was cold -start, not the check itself. - -It is easy to write these off as deployment details. On an edge product they are -part of the architecture, because they decide whether the security boundary -survives normal starts, updates, failures, and operator workflows. - ---- - ## Conclusion None of this is specific to Reachy. The same approach fits inspection robots, -smart cameras, lab instruments, field vehicles, building gateways, and kiosks. In each one, the agent can read sensors and describe what it sees, while -anything with a real consequence has to be approved by a policy first: moving an actuator, -changing a setpoint, or sending raw data off the device. We see this as a pattern for using OpenShell to bring security and trust to +smart cameras, lab instruments, field vehicles, building gateways, and kiosks. In +each one, the agent can read sensors and describe what it sees, while anything +with a real consequence has to be approved by policy first: moving an actuator, +changing a setpoint, or sending raw data off the device. + +The main result from putting this on Reachy is that the whole OpenShell stack, +the gateway and the sandbox, runs on the device's own computer. The isolation and +the policy do not depend on the network or a cloud service, so the device keeps +enforcing its boundary even if the network drops or the model is unreachable. +Running the full stack on device is what gives complete isolation and control at +the edge. + +We see this as a pattern for using OpenShell to bring security and trust to autonomous edge systems. Key resources: From be515c9c2684e1e3febec058f1a9e0e90da16a72 Mon Sep 17 00:00:00 2001 From: Kirit93 Date: Fri, 17 Jul 2026 12:53:58 -0700 Subject: [PATCH 35/45] more blog edits --- ...-controlling-reachy-mini-with-openshell.md | 201 +++++------------- 1 file changed, 56 insertions(+), 145 deletions(-) diff --git a/docs/dev-notes/posts/2026-07-13-policy-controlling-reachy-mini-with-openshell.md b/docs/dev-notes/posts/2026-07-13-policy-controlling-reachy-mini-with-openshell.md index 4fb2362f..32bb6c19 100644 --- a/docs/dev-notes/posts/2026-07-13-policy-controlling-reachy-mini-with-openshell.md +++ b/docs/dev-notes/posts/2026-07-13-policy-controlling-reachy-mini-with-openshell.md @@ -44,13 +44,13 @@ watching. This creates a problem. When an agent can change itself and act on its own, a guardrail that lives inside the same process is easy for it to bypass. OpenShell is the agent runtime for autonomous fleets of agents, and it solves -this problem by moving the control point outside the agent. It runs the agent in +this problem by moving the point of control outside the agent. It runs the agent in a sandbox and sits in the path of everything the agent does. A policy layer, configured separately from the agent, governs each -interaction: which files it can read or write, which processes it can start, -which hosts and ports it can reach, and which models it can call. +interaction: which processes it can start, which hosts and ports it can reach, which models it can call, other services it needs to invoke along its network path. -The boundary is also programmable. Because every request passes through the -runtime, you can do more there than allow or deny. For privacy, you +We recognize that everyone has different criteria and needs for an agent runtime, that's why we made OpenShell extensible. You can pick +your isolation backend, add enterprise specific checks for policy updates, and deploy middleware services that are invoked when any traffic egresses +the sandbox. With this, there's more you can do than just allow or deny requests. For privacy, you can run outbound requests through a filter that redacts or drops sensitive data, such as faces in a camera frame, before it leaves the device. For routing, you can point a model call at an on-device endpoint, a cloud provider, or a @@ -61,47 +61,38 @@ a stronger credential instead of passing on the model's say-so. For enterprise control, you can sign a policy and have the device verify that signature before it loads, so it only enforces rules an operator actually approved, and push those signed policies across a fleet. So OpenShell is more than a sandbox around the -agent. - -If the model is prompt-injected, a tool is compromised, or the agent rewrites its -own workflow, it still cannot give itself a permission the runtime did not grant. +agent, it's a complete runtime. At the edge, this problem gets physical. An agent can watch people and places, read microphones, cameras, and sensors, and take actions that move machines or -change local systems. A failure is no longer just a bad shell command or a -leaked credential. It can leak data that was supposed to stay on-site, or move +change local systems. A corrupted agent can leak data that was supposed to stay on-site, or move something in the real world. -That creates two rules. Some data should never leave the device or the site +Two requirements come out of this - some data should never leave the device or the site where it was produced. Some actions should never be possible in a given -deployment, even if a model, prompt, tool, skill, or update asks for them. To -enforce both, the control point has to sit on the device with the agent. It has -to be deterministic, set up separately from the agent, and checked locally -before any data leaves or any action reaches the hardware. +deployment, even if a model, prompt, tool, skill, or update asks for them. We run the entire OpenShell stack on the edge +to bring deterministic policy enforcement and security to edge devices. -We used Reachy Mini to see what that looks like in practice. The pattern keeps -the agent in an on-device OpenShell sandbox, keeps hardware ownership in a small -trusted process, and checks policy locally before any request reaches the rest -of the device. +We used Reachy Mini to see what that looks like in practice. We run a small chat application connected to an Open AI endpoint within the OpenShell +Runtime, all on the Reachy Mini's onboard Raspberry Pi. - -This post walks through the design behind that architecture. Reachy makes the -result easy to see: the camera works and the head does not move. The same -boundaries apply to lab instruments, industrial gateways, vehicles, kiosks, and -other AI-enabled edge systems. + -The copy-and-run installation procedure lives separately in the -[onboard setup tutorial](https://github.com/NVIDIA/OpenShell-Research/blob/kirit93/reachy-implementation/projects/reachy-mini-openshell/ONBOARD_SETUP.md). +This post talks about how we approached this and what it means for agent security at the edge. If +you just want to try this for yourself, check out our tutorial [here](https://github.com/NVIDIA/OpenShell-Research/blob/kirit93/reachy-implementation/projects/reachy-mini-openshell/ONBOARD_SETUP.md). --- -## Trust Has to Move with the Agent +## Bring Privacy and Trust to the Edge + +The way we approach privacy for edge devices and traditional software applications changes. At the edge, you can have +devices that can see you, hear you, and talk to you. These devices can be in your home, your office, even your schools and +you need to make sure these devices see and hear only things they really need to, and keep that data private. You also need to make sure +these devices can only do the things you really want them to. For a home assistant robot, that could be only allowing a robot to clean but never allowing +it to open a door. -The same agent might run in a factory, a lab, a warehouse, a store, or a home. -Each of those places has different data to protect, different physical risks, -different operators, and different actions it should allow. So the controls have -to live where the device runs, not only where the model is hosted. +Let's think about how OpenShell's core principles can apply here: **Stop private data before it leaves.** A camera can analyze a scene on the device but be blocked from sending raw video off-site. A microphone can drive a @@ -123,14 +114,6 @@ prompt or the tool code breaks the moment any of those change, so you have to re-check it after every update. A guarantee that lives in policy outside the agent does not. You can change the agent without touching it. -None of this means OpenShell understands what an image shows or what a motor -command will do. It means the agent is boxed into set filesystem and network -limits, and that anything device-specific has to go through a narrow trusted -interface that policy can allow or deny. OpenShell decides whether the agent may -call a capability at all. The trusted adapter decides what that call is allowed -to ask for. The device controller enforces the hardware limits as it runs, such -as joint ranges, speed caps, and emergency stop. - The Reachy demo talks to the OpenAI Realtime API over one allowed WebSocket endpoint, so the conversation audio and the requested camera frame go to that approved service. A deployment with strict data-residency rules could allow a @@ -139,45 +122,24 @@ derived data. Local policy decides what leaves, no matter where the model runs. --- -## An Edge Agent Is Not Just a Smaller Deployment - -The obvious approach is to run the agent on the device and hand it the local SDK -or REST API. That works for a prototype: the agent calls the model, invokes a -tool, and the hardware responds. - -It breaks once two things are true: the agent can change itself, and what it does -has real-world consequences. An agent that only answers questions can be trusted -to stay in bounds. One that rewrites its own prompts, adds its own tools, and -drives a motor cannot, because the code enforcing the limits is the same code -that keeps changing. That is when security starts to matter. +## Give Each Job Its Own Boundary -At that point the obvious fixes do not hold. Take device access away and the -agent cannot do its job. Gate every capture and movement on human approval and -you lose the autonomy that made it useful. Leave it with full access and a -self-changing process is policing itself. Keeping capability, autonomy, and -controls the agent cannot rewrite means the enforcement has to sit outside the -agent. +The simplest way to build this is to run the agent on the device and give it the +robot's SDK. That works for a quick demo, but it puts two things that should be +separate into a single process. -Handing the agent the SDK directly also packs two separate concerns into one -process. +**The agent gets more than it needs.** A robot SDK exposes motors, raw targets, +camera settings, recorded motions, app management, and system state. An agent +that only needs a few fixed head moves should not inherit all of that. -**Too much access.** A robot SDK exposes motors, raw targets, camera settings, -recorded motions, app management, and system state. An agent that needs a few -fixed head moves should not inherit all of it. +**The decision happens too far from the effect.** A remote model can pick which +tool to call, but it should not be the final say on whether a local motor +actually moves. That call belongs on the device, right before the request reaches +the controller. -**The decision sits too far from the effect.** A remote model can pick which tool -to call, but it should not be the final say on whether a local motor actually -moves. That decision belongs on the device, right before the request reaches the -controller. - ---- - -## An Edge Agent as a System of Boundaries - -Both problems come from the same thing: one process holds the access and makes -the decisions, instead of splitting those jobs apart. The fix is to give each -responsibility its own part. Reasoning, policy, hardware ownership, and device -execution become four separate boundaries, each with one job. +Both come from the same place: one process holds all the access and makes all the +decisions. So we split the work into separate parts, each with one job. Reasoning, +policy, hardware ownership, and device execution each become their own boundary. 1. **The model reasons.** It reads the conversation and picks from the tools the app offers. It can be remote or local. @@ -210,31 +172,25 @@ authority stays outside the agent. --- -## Design Principles Behind OpenShell at the Edge +## How We Built It -With that in place, here are the principles that shaped the Reachy build. +These were the main choices behind the build. ### Run OpenShell entirely on device -On Reachy, all core parts of OpenShell run on the onboard computer. The gateway is -the control plane: it creates the sandbox, resolves the policy, and manages the -sandbox lifecycle. The agent runs inside the sandbox. - -So when the agent tries to move the robot, OpenShell intercepts the request on -the device and decides whether it reaches the daemon. A denial stops right there. -It does not wait for the remote model to withdraw the tool call. - -OpenShell's policy also enforces what leaves the sandbox. Every outbound connection -goes through it, and it can allow the request, route it to another destination, -or deny it. So a deployment can allow one approved remote model, route model -traffic through a local service, or block remote models and use an on-device -endpoint instead. The model can sit in the cloud, but the gateway and the sandbox -both run on the device, so the power to move local data and use local hardware -stays local. +We run all of OpenShell on Reachy's onboard computer. The gateway is the control +plane: it creates the sandbox, holds the policy, and manages the sandbox +lifecycle. The agent runs inside the sandbox. When the agent tries to move the +robot, OpenShell checks the request on the device and decides whether it reaches +the daemon. A denial stops right there. It does not wait for the remote model to +withdraw the call. The same check controls what leaves the sandbox: every +outbound connection can be allowed, routed somewhere else, or denied. The model +can sit in the cloud, but the gateway and the sandbox both run on the device, so +the power to move local data and use local hardware stays local. ### Expose capabilities, not complete APIs -The agent gets three robot tools: +We give the agent three tools: - `move_head(directions)` accepts `left`, `right`, `up`, `down`, and `front`. - `stop_motion()` stops active movements. @@ -271,58 +227,13 @@ audio over a local WebSocket and exposes one camera route with no arguments: frame. It never gets the camera handle, the device choice, the resolution controls, or a file path. -### Provision once, operate many times - -Setup happens once. You install OpenShell on the robot and create the sandbox a -single time. That one step fixes the operator decisions: the image, the provider, -the credentials, the filesystem and network policy, and the CPU and memory -limits. The model credential is part of it too. It is attached to the sandbox -through the OpenShell provider at creation, not baked into the Docker image, the -policy file, or the native controller. - -After that, the sandbox stays up and the Reachy App only manages the conversation -process inside it. `reachy-agent-control start|stop|status` starts and stops the -agent, never the sandbox. Starting the Reachy App checks that the sandbox is -ready, starts the agent, opens the audio route, and connects media. Stopping it -closes media and stops the agent. The sandbox, its policy, and its credentials -are left in place, ready for the next start. - -We would rather have folded sandbox creation into starting the app, so setup was -one step instead of two. Reachy's app lifecycle did not allow that. - -### Treat resource constraints as design inputs - -The Reachy we tested had 3.7 GiB of usable RAM, 2 GiB of swap, and a 14 GiB root -partition. We capped the sandbox at 2 CPUs and 2 GiB of memory, and we built the -image on a dev machine instead of spending the robot's CPU, memory, and microSD -write budget on it. - -The runtime image uses a slim Python base, a throwaway wheel-building stage, a -REST-only dependency list, and an install with `--no-deps`. That keeps the -Reachy SDK, MuJoCo, OpenCV, the simulator, the dance stack, and local vision out -of the sandbox. The final ARM64 image came to 339,495,096 bytes, about 339 MB, -and still includes the networking tools OpenShell needs. - -### Design for both remote and local models - -The Realtime model in the demo is remote. The conversation, policy, device -adapter, and robot controller all still run on Reachy. That matters, because edge -does not have to mean fully offline, and local enforcement does not need a local -model. - -The same setup can later use an on-device model. Only the model endpoint changes. -The sandbox, the trusted adapter, and the local action boundary stay the same. - -Today's policy allows the chat app to reach one OpenAI Realtime endpoint. It does -not inspect the content for privacy yet, but it sets up the egress boundary you -would need to add that. - -A privacy-focused deployment could block direct model access and make an -OpenShell Middleware service the only model destination the sandbox can reach. -Privacy Guard, which is on the OpenShell roadmap, could use that service to spot -sensitive camera, microphone, or sensor data and decide whether to block it, -redact it, handle it locally, or send it to an approved model. The agent could -not get around that by connecting straight to another model endpoint. +### Use a remote or local model + +The model in our demo is remote, an OpenAI Realtime endpoint. Everything else, +the conversation, the policy, the adapter, and the controller, runs on Reachy. +Edge does not have to mean fully offline, and enforcing policy on the device does +not need a local model. If you later want an on-device model, only the endpoint +changes. The sandbox, the adapter, and the boundary stay the same. --- From ada471a6419d8f4193a84341d9d0536d50bc1b77 Mon Sep 17 00:00:00 2001 From: Kirit93 Date: Fri, 17 Jul 2026 12:59:46 -0700 Subject: [PATCH 36/45] Updated flow --- ...-controlling-reachy-mini-with-openshell.md | 20 ++++++------------- 1 file changed, 6 insertions(+), 14 deletions(-) diff --git a/docs/dev-notes/posts/2026-07-13-policy-controlling-reachy-mini-with-openshell.md b/docs/dev-notes/posts/2026-07-13-policy-controlling-reachy-mini-with-openshell.md index 32bb6c19..b74c0fec 100644 --- a/docs/dev-notes/posts/2026-07-13-policy-controlling-reachy-mini-with-openshell.md +++ b/docs/dev-notes/posts/2026-07-13-policy-controlling-reachy-mini-with-openshell.md @@ -53,7 +53,7 @@ your isolation backend, add enterprise specific checks for policy updates, and d the sandbox. With this, there's more you can do than just allow or deny requests. For privacy, you can run outbound requests through a filter that redacts or drops sensitive data, such as faces in a camera frame, before it leaves the device. For routing, you -can point a model call at an on-device endpoint, a cloud provider, or a +can point an agent call at an on-device endpoint, a cloud provider, or a middleware service in between, and change that choice per deployment without touching the agent. For authorization, you can require an extra check before a sensitive request goes through, so an action waits for an operator's approval or @@ -68,19 +68,11 @@ read microphones, cameras, and sensors, and take actions that move machines or change local systems. A corrupted agent can leak data that was supposed to stay on-site, or move something in the real world. -Two requirements come out of this - some data should never leave the device or the site -where it was produced. Some actions should never be possible in a given -deployment, even if a model, prompt, tool, skill, or update asks for them. We run the entire OpenShell stack on the edge -to bring deterministic policy enforcement and security to edge devices. +Two core problems that stand out to us with edge deployments are - privacy of data captured at the edge, and restricting physical actions a robot or +similar device can take depending on it's deployment scenario. We used Reachy Mini to see what that looks like in practice. We run a small chat application connected to an Open AI endpoint within the OpenShell Runtime, all on the Reachy Mini's onboard Raspberry Pi. We use OpenShell to restrict what actions the model can take. Our next step is to +route sensitive data to approved models but more on that in a follow on post! -We used Reachy Mini to see what that looks like in practice. We run a small chat application connected to an Open AI endpoint within the OpenShell -Runtime, all on the Reachy Mini's onboard Raspberry Pi. - - - - -This post talks about how we approached this and what it means for agent security at the edge. If -you just want to try this for yourself, check out our tutorial [here](https://github.com/NVIDIA/OpenShell-Research/blob/kirit93/reachy-implementation/projects/reachy-mini-openshell/ONBOARD_SETUP.md). +If you just want to try this for yourself, check out our tutorial [here](https://github.com/NVIDIA/OpenShell-Research/blob/kirit93/reachy-implementation/projects/reachy-mini-openshell/ONBOARD_SETUP.md). --- @@ -103,7 +95,7 @@ approved service may process, and what may leave. That rule is what OpenShell enforces, and it holds no matter what the agent is told to do. **Enforce safety before the action, not after.** An inspection robot may use its -camera everywhere but move only inside a controlled workcell. That workcell +camera everywhere but move only inside a controlled environment. That environment limit lives in the policy an operator applies at deployment, not in the image or the agent's code, so the same build can ship to a test bench where movement is open and to a production line where it is denied. From 069696b0a28ffd0cd77e1e043a532f81b9cec3e2 Mon Sep 17 00:00:00 2001 From: Kirit93 Date: Fri, 17 Jul 2026 19:31:26 -0700 Subject: [PATCH 37/45] docs(dev-note): finalize Reachy OpenShell edge post Restructure around the two problems (action restriction, privacy), tighten the intro and boundary sections, and add the privacy-routing middleware diagram. --- .../diagrams/privacy-routing.svg | 66 ++++++++ ...-controlling-reachy-mini-with-openshell.md | 143 +++++++----------- 2 files changed, 117 insertions(+), 92 deletions(-) create mode 100644 docs/assets/reachy-mini-openshell/diagrams/privacy-routing.svg diff --git a/docs/assets/reachy-mini-openshell/diagrams/privacy-routing.svg b/docs/assets/reachy-mini-openshell/diagrams/privacy-routing.svg new file mode 100644 index 00000000..a486b2e0 --- /dev/null +++ b/docs/assets/reachy-mini-openshell/diagrams/privacy-routing.svg @@ -0,0 +1,66 @@ + + + + + + + + + + + + + + PRIVACY ROUTING WITH MIDDLEWARE + + + + Sandboxed agent + on the Reachy + + + + OPENSHELL MIDDLEWARE + + Router + detects data type + + + + + IMAGE DATA + Approved image model + cleared for sensitive images + + + + Frontier model + in the cloud + + + + all traffic + + + + image data + + + + everything else + + Policy forces all sandbox traffic through the middleware, so the agent cannot route around it. + diff --git a/docs/dev-notes/posts/2026-07-13-policy-controlling-reachy-mini-with-openshell.md b/docs/dev-notes/posts/2026-07-13-policy-controlling-reachy-mini-with-openshell.md index b74c0fec..06ae19c6 100644 --- a/docs/dev-notes/posts/2026-07-13-policy-controlling-reachy-mini-with-openshell.md +++ b/docs/dev-notes/posts/2026-07-13-policy-controlling-reachy-mini-with-openshell.md @@ -38,87 +38,31 @@ card_tags: -AI agents can now run for a long time, pursue -goals, call tools, learn new skills, write code, and keep working while no one is -watching. This creates a problem. When an agent can change itself and act on its -own, a guardrail that lives inside the same process is easy for it to bypass. - -OpenShell is the agent runtime for autonomous fleets of agents, and it solves -this problem by moving the point of control outside the agent. It runs the agent in -a sandbox and sits in the path of everything the agent does. A policy layer, configured separately from the agent, governs each -interaction: which processes it can start, which hosts and ports it can reach, which models it can call, other services it needs to invoke along its network path. - -We recognize that everyone has different criteria and needs for an agent runtime, that's why we made OpenShell extensible. You can pick -your isolation backend, add enterprise specific checks for policy updates, and deploy middleware services that are invoked when any traffic egresses -the sandbox. With this, there's more you can do than just allow or deny requests. For privacy, you -can run outbound requests through a filter that redacts or drops sensitive data, -such as faces in a camera frame, before it leaves the device. For routing, you -can point an agent call at an on-device endpoint, a cloud provider, or a -middleware service in between, and change that choice per deployment without -touching the agent. For authorization, you can require an extra check before a -sensitive request goes through, so an action waits for an operator's approval or -a stronger credential instead of passing on the model's say-so. For enterprise -control, you can sign a policy and have the device verify that signature before -it loads, so it only enforces rules an operator actually approved, and push those -signed policies across a fleet. So OpenShell is more than a sandbox around the -agent, it's a complete runtime. - -At the edge, this problem gets physical. An agent can watch people and places, -read microphones, cameras, and sensors, and take actions that move machines or -change local systems. A corrupted agent can leak data that was supposed to stay on-site, or move -something in the real world. - -Two core problems that stand out to us with edge deployments are - privacy of data captured at the edge, and restricting physical actions a robot or -similar device can take depending on it's deployment scenario. We used Reachy Mini to see what that looks like in practice. We run a small chat application connected to an Open AI endpoint within the OpenShell Runtime, all on the Reachy Mini's onboard Raspberry Pi. We use OpenShell to restrict what actions the model can take. Our next step is to -route sensitive data to approved models but more on that in a follow on post! - -If you just want to try this for yourself, check out our tutorial [here](https://github.com/NVIDIA/OpenShell-Research/blob/kirit93/reachy-implementation/projects/reachy-mini-openshell/ONBOARD_SETUP.md). +AI agents can now run for a long time, pursue goals, call tools, learn new skills, write code, and keep working while no one is watching. How do you give autonomy to such a highly capable agent? ---- +OpenShell is the secure agent runtime for autonomous agents. It solves this problem by moving the security layer outside the agent. OpenShell runs your agent in a sandbox and sits in the path of everything the agent does. A policy layer, configured separately from the agent, governs what processes the agent can start, which hosts and ports it can reach, which models it can call, and which other services it needs to invoke along its network path. + +Every OpenShell deployment has different needs, so we made OpenShell extensible. You are not locked into a fixed set of behaviors. You can swap the isolation backend, add your own checks on policy updates, and plug in middleware services that run on traffic as it leaves the sandbox. + +The combination of autonomous agents and edge devices like robots brings the digital concerns of traditional software deployments into the physical world. Imagine a home assistant robot that is only supposed to clean. It suffers a prompt injection and starts unlocking the doors instead. At the edge, a compromised agent does not just leak data or crash a process. It can let a stranger into your home, or send what it sees and hears somewhere it should never go. + +OpenShell makes an autonomous agent safe to run at the edge by solving two problems: -## Bring Privacy and Trust to the Edge - -The way we approach privacy for edge devices and traditional software applications changes. At the edge, you can have -devices that can see you, hear you, and talk to you. These devices can be in your home, your office, even your schools and -you need to make sure these devices see and hear only things they really need to, and keep that data private. You also need to make sure -these devices can only do the things you really want them to. For a home assistant robot, that could be only allowing a robot to clean but never allowing -it to open a door. - -Let's think about how OpenShell's core principles can apply here: - -**Stop private data before it leaves.** A camera can analyze a scene on the -device but be blocked from sending raw video off-site. A microphone can drive a -local interaction while the recording stays put. A lab instrument can hand back -a result while its raw measurements never leave the building. Each case needs a -hard rule about where sensitive data can go: what stays on the device, what an -approved service may process, and what may leave. That rule is what OpenShell -enforces, and it holds no matter what the agent is told to do. - -**Enforce safety before the action, not after.** An inspection robot may use its -camera everywhere but move only inside a controlled environment. That environment -limit lives in the policy an operator applies at deployment, not in the image or -the agent's code, so the same build can ship to a test bench where movement is -open and to a production line where it is denied. - -**Controls have to outlast changes to the agent.** Models get swapped, prompts -get tuned, tools get added, code gets upgraded. A guarantee that lives in the -prompt or the tool code breaks the moment any of those change, so you have to -re-check it after every update. A guarantee that lives in policy outside the -agent does not. You can change the agent without touching it. - -The Reachy demo talks to the OpenAI Realtime API over one allowed WebSocket -endpoint, so the conversation audio and the requested camera frame go to that -approved service. A deployment with strict data-residency rules could allow a -local model instead, or an approved on-device preprocessing service, or only -derived data. Local policy decides what leaves, no matter where the model runs. +- **Restrict what the device can do.** Deterministic policy decides what the agent can actually make the device do, and it is enforced on the device. +- **Keep the data private.** Sensitive data stays local, and only approved services ever see it. + +We used the HuggingFace Reachy Mini to see what that looks like in practice. We run a small chat application connected to an OpenAI endpoint within the OpenShell runtime, all on the Reachy Mini's onboard Raspberry Pi. We use OpenShell to restrict what actions the model can take. Our next step is to route sensitive data to approved models, but more on that in a follow-up post. + +If you just want to try this for yourself, check out our tutorial [here](https://github.com/NVIDIA/OpenShell-Research/blob/kirit93/reachy-implementation/projects/reachy-mini-openshell/ONBOARD_SETUP.md). --- ## Give Each Job Its Own Boundary -The simplest way to build this is to run the agent on the device and give it the -robot's SDK. That works for a quick demo, but it puts two things that should be -separate into a single process. +Start with the first problem: restricting what the device can do. The simplest +way to build this is to run the agent on the device and give it the robot's SDK. +That works for a quick demo, but it puts two things that should be separate into +a single process. **The agent gets more than it needs.** A robot SDK exposes motors, raw targets, camera settings, recorded motions, app management, and system state. An agent @@ -130,16 +74,14 @@ actually moves. That call belongs on the device, right before the request reache the controller. Both come from the same place: one process holds all the access and makes all the -decisions. So we split the work into separate parts, each with one job. Reasoning, -policy, hardware ownership, and device execution each become their own boundary. +decisions. So we split the work into separate parts, each with one job. -1. **The model reasons.** It reads the conversation and picks from the tools the - app offers. It can be remote or local. +1. **The model reasons.** It listens to what the user says and picks from the + tools the app offers. The model can be remote or local. 2. **The sandboxed agent turns that choice into a concrete request.** It owns the conversation state and the tool logic, but it does not own the hardware. 3. **OpenShell decides whether the request may leave the sandbox.** It checks the - request on the device against the calling binary, destination, port, HTTP - method, path, and query. + tool call request against the OpenShell policy. 4. **A trusted adapter exposes one narrow capability.** It owns the native device objects and turns an approved request into a single bounded operation. 5. **The device controller does the work.** Motors, sensors, and cameras are @@ -150,12 +92,6 @@ policy, hardware ownership, and device execution each become their own boundary.
    Reasoning, policy enforcement, hardware ownership, and device execution are separated into distinct boundaries. The local OpenShell policy decision is the control point, evaluated on the device before a request can leave the sandbox.
    -Each boundary now has one thing to enforce and one thing to test. You can change -the model without touching the robot adapter. You can change the policy without -rebuilding the image. You can restart the app without recreating credentials or -resource limits. And you can test the allowed camera path on its own, separate -from the denied movement path. - The sandbox starts with deny-by-default policy instead of inheriting everything the host can do. When Reachy hits a denied action, the agent gets a clear error it can explain out loud, rather than quietly working around it. An operator can @@ -174,11 +110,8 @@ We run all of OpenShell on Reachy's onboard computer. The gateway is the control plane: it creates the sandbox, holds the policy, and manages the sandbox lifecycle. The agent runs inside the sandbox. When the agent tries to move the robot, OpenShell checks the request on the device and decides whether it reaches -the daemon. A denial stops right there. It does not wait for the remote model to -withdraw the call. The same check controls what leaves the sandbox: every -outbound connection can be allowed, routed somewhere else, or denied. The model -can sit in the cloud, but the gateway and the sandbox both run on the device, so -the power to move local data and use local hardware stays local. +the daemon. The same check controls what leaves the sandbox: every outbound +connection can be allowed, routed somewhere else, or denied. ### Expose capabilities, not complete APIs @@ -233,7 +166,7 @@ changes. The sandbox, the adapter, and the boundary stay the same.
    Request flow on Reachy. The person speaks to the trusted native Reachy App, which streams PCM audio into the OpenShell sandbox, where the conversation agent exchanges policy-checked audio with the OpenAI Realtime API. Robot requests from the agent pass through the OpenShell gateway, which allows the POST /camera/capture path to the one-frame camera adapter and denies the POST /api/move/goto path to the Reachy daemon and motors. -
    The same OpenShell gateway sits in front of both physical capabilities. It allows the camera capture path (green) and denies the movement path (red), so the camera works and the head does not move, enforced by policy rather than by the application choosing to refuse.
    +
    Every request to the hardware passes through OpenShell first. The OpenShell policy allows the camera capture path (green) and denies the movement path (red), so the camera works and the head does not move, enforced by policy rather than by the application choosing to refuse.
    There is no laptop, browser, or Gradio page in the runtime path. The full @@ -273,6 +206,32 @@ effect. --- +## Keeping Data Private + +The demo above covers action restriction, the first of the two problems. The +second is privacy, and at the edge it matters more than usual, because these +devices can see and hear the room they are in. A camera should be able to +describe a scene without sending raw video off the device, and a microphone +should be able to drive a conversation while the recording stays local. The +device should capture only what it needs, and anything sensitive should leave +only when it has to. + +The next piece for Reachy is to add privacy routing. We use OpenShell's +middleware service, which hooks into OpenShell's sandbox proxy. The middleware service is built to detect +what type of data is leaving the sandbox. We keep things simple here: if it's image data, we route it to a model approved to +handle image data, which may be sensitive. If it's not image data, it goes to a frontier model in the cloud. This is just an +example, but the benefit of middleware is its flexibility. You can build in whatever routing logic you want, and use any tool you +want for PII redaction or replacement. + +
    + Privacy routing with middleware. OpenShell's policy forces the sandboxed agent's outbound traffic through an OpenShell middleware service. A router in the middleware detects the data type: image data goes to a model approved to handle sensitive images, and everything else goes to a frontier model in the cloud. +
    Privacy routing.
    +
    + +We will publish more on this as a follow-up. + +--- + ## Conclusion None of this is specific to Reachy. The same approach fits inspection robots, From dae9006d40d644fa450b3a40a1aaf2ee953049ef Mon Sep 17 00:00:00 2001 From: Kirit93 Date: Fri, 17 Jul 2026 19:40:06 -0700 Subject: [PATCH 38/45] Update blog --- ...026-07-13-policy-controlling-reachy-mini-with-openshell.md | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/docs/dev-notes/posts/2026-07-13-policy-controlling-reachy-mini-with-openshell.md b/docs/dev-notes/posts/2026-07-13-policy-controlling-reachy-mini-with-openshell.md index 06ae19c6..c84e4fd4 100644 --- a/docs/dev-notes/posts/2026-07-13-policy-controlling-reachy-mini-with-openshell.md +++ b/docs/dev-notes/posts/2026-07-13-policy-controlling-reachy-mini-with-openshell.md @@ -223,12 +223,12 @@ handle image data, which may be sensitive. If it's not image data, it goes to a example, but the benefit of middleware is its flexibility. You can build in whatever routing logic you want, and use any tool you want for PII redaction or replacement. +Keep an eye on this repo for more details on privacy routing! +
    Privacy routing with middleware. OpenShell's policy forces the sandboxed agent's outbound traffic through an OpenShell middleware service. A router in the middleware detects the data type: image data goes to a model approved to handle sensitive images, and everything else goes to a frontier model in the cloud. -
    Privacy routing.
    -We will publish more on this as a follow-up. --- From 7da597f071916ef97dfc0b648f731d853206978e Mon Sep 17 00:00:00 2001 From: Kirit93 Date: Fri, 17 Jul 2026 19:44:50 -0700 Subject: [PATCH 39/45] Updated title --- ...026-07-13-policy-controlling-reachy-mini-with-openshell.md | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/docs/dev-notes/posts/2026-07-13-policy-controlling-reachy-mini-with-openshell.md b/docs/dev-notes/posts/2026-07-13-policy-controlling-reachy-mini-with-openshell.md index c84e4fd4..8abe165e 100644 --- a/docs/dev-notes/posts/2026-07-13-policy-controlling-reachy-mini-with-openshell.md +++ b/docs/dev-notes/posts/2026-07-13-policy-controlling-reachy-mini-with-openshell.md @@ -1,5 +1,5 @@ --- -title: "Designing OpenShell for the Edge: Why Policy Has to Live Next to the Action" +title: "Bringing Privacy and Security to the Edge with OpenShell" date: 2026-07-13 updated: 2026-07-13 description: "Edge agents handle sensitive data and make decisions with physical consequences. Reachy Mini shows why privacy and safety controls must be deterministic and local." @@ -20,7 +20,7 @@ card_tags: - policy --- -# Designing OpenShell for the Edge: Why Policy Has to Live Next to the Action +# Bringing Privacy and Security to the Edge with OpenShell From bd74cc829d8569586bb720e439697340bdf2f779 Mon Sep 17 00:00:00 2001 From: Kirit93 Date: Mon, 20 Jul 2026 09:46:09 -0700 Subject: [PATCH 40/45] Updated blog --- ...-controlling-reachy-mini-with-openshell.md | 26 ++++++++++++------- .../reachy-mini-openshell/ONBOARD_SETUP.md | 8 +++--- 2 files changed, 20 insertions(+), 14 deletions(-) diff --git a/docs/dev-notes/posts/2026-07-13-policy-controlling-reachy-mini-with-openshell.md b/docs/dev-notes/posts/2026-07-13-policy-controlling-reachy-mini-with-openshell.md index 8abe165e..6166cdf4 100644 --- a/docs/dev-notes/posts/2026-07-13-policy-controlling-reachy-mini-with-openshell.md +++ b/docs/dev-notes/posts/2026-07-13-policy-controlling-reachy-mini-with-openshell.md @@ -38,11 +38,11 @@ card_tags: -AI agents can now run for a long time, pursue goals, call tools, learn new skills, write code, and keep working while no one is watching. How do you give autonomy to such a highly capable agent? +Useful AI agents now run for long periods of time, taking on critical tasks to accomplish goals. They call tools, learn new skills, write code, and keep working while no one is watching. How do you give autonomy to such a highly capable agent? -OpenShell is the secure agent runtime for autonomous agents. It solves this problem by moving the security layer outside the agent. OpenShell runs your agent in a sandbox and sits in the path of everything the agent does. A policy layer, configured separately from the agent, governs what processes the agent can start, which hosts and ports it can reach, which models it can call, and which other services it needs to invoke along its network path. +OpenShell is the secure runtime for autonomous agents. It solves this problem by moving the security layer outside the agent. OpenShell runs your agent in a sandbox and sits in the path of everything the agent does. A policy layer, configured separately from the agent, governs what processes the agent can start, which hosts and ports it can reach, which models it can call, and which other services it needs to invoke along its network path. -Every OpenShell deployment has different needs, so we made OpenShell extensible. You are not locked into a fixed set of behaviors. You can swap the isolation backend, add your own checks on policy updates, and plug in middleware services that run on traffic as it leaves the sandbox. +Every OpenShell deployment has different needs, and different agents want different things, so we made OpenShell extensible. You are not locked into a fixed set of behaviors. You can swap the isolation backend, add your own checks on policy updates, and plug in middleware services that run on traffic as it leaves the sandbox. The combination of autonomous agents and edge devices like robots brings the digital concerns of traditional software deployments into the physical world. Imagine a home assistant robot that is only supposed to clean. It suffers a prompt injection and starts unlocking the doors instead. At the edge, a compromised agent does not just leak data or crash a process. It can let a stranger into your home, or send what it sees and hears somewhere it should never go. @@ -51,7 +51,7 @@ OpenShell makes an autonomous agent safe to run at the edge by solving two probl - **Restrict what the device can do.** Deterministic policy decides what the agent can actually make the device do, and it is enforced on the device. - **Keep the data private.** Sensitive data stays local, and only approved services ever see it. -We used the HuggingFace Reachy Mini to see what that looks like in practice. We run a small chat application connected to an OpenAI endpoint within the OpenShell runtime, all on the Reachy Mini's onboard Raspberry Pi. We use OpenShell to restrict what actions the model can take. Our next step is to route sensitive data to approved models, but more on that in a follow-up post. +We used the HuggingFace Reachy Mini to see what that looks like in practice. We run a small chat application connected to an OpenAI endpoint within the OpenShell runtime, all on the Reachy Mini's onboard Raspberry Pi. Running the whole stack on a Raspberry Pi is part of the point: OpenShell holds up on the small, resource-constrained hardware that real edge devices ship with, not just a workstation. We use OpenShell to restrict what actions the model can take. Our next step is to route sensitive data to approved models, but more on that in a follow-up post. If you just want to try this for yourself, check out our tutorial [here](https://github.com/NVIDIA/OpenShell-Research/blob/kirit93/reachy-implementation/projects/reachy-mini-openshell/ONBOARD_SETUP.md). @@ -93,10 +93,12 @@ decisions. So we split the work into separate parts, each with one job. The sandbox starts with deny-by-default policy instead of inheriting everything -the host can do. When Reachy hits a denied action, the agent gets a clear error -it can explain out loud, rather than quietly working around it. An operator can -change the policy without rebuilding the app, and the power to grant new -authority stays outside the agent. +the host can do. When OpenShell blocks an action, it returns a natural-language +message explaining why, along with examples of what is allowed. The agent can +tell the person what happened and look for a safe way to do the same task, +instead of quietly working around the limit. An operator can change the policy +without rebuilding the app, and the power to grant new authority stays outside +the agent. --- @@ -247,8 +249,12 @@ enforcing its boundary even if the network drops or the model is unreachable. Running the full stack on device is what gives complete isolation and control at the edge. -We see this as a pattern for using OpenShell to bring security and trust to -autonomous edge systems. +This is a repeatable pattern for edge and robotics. Agents are going to run +everywhere: in homes, factories, vehicles, and hospitals, with more and more of +them running side by side and working together. You cannot govern that many +agents, in that many places, by writing a guardrail into each app. It takes one +deterministic boundary you can put on any device and trust the same way every +time. That is the pattern we are building with OpenShell. Key resources: diff --git a/projects/reachy-mini-openshell/ONBOARD_SETUP.md b/projects/reachy-mini-openshell/ONBOARD_SETUP.md index fa9abbcc..382c04d4 100644 --- a/projects/reachy-mini-openshell/ONBOARD_SETUP.md +++ b/projects/reachy-mini-openshell/ONBOARD_SETUP.md @@ -250,7 +250,7 @@ openshell/policy-camera-enabled-motion-disabled.yaml openshell/policy-head-motion-enabled.yaml ``` -Both allow: +All three allow: ```text GET /api/daemon/status @@ -273,7 +273,7 @@ POST /camera/capture That camera policy still blocks `POST /api/move/goto`. The base `policy-motion-disabled.yaml` blocks both camera capture and motion start. -Neither policy allows `/api/move/set_target`, `/api/motors/**`, +None of the three policies allow `/api/move/set_target`, `/api/motors/**`, `/api/apps/**`, raw movement WebSockets, wake/sleep, or recorded motions. The permitted binary is `/opt/venv/bin/python`. A denial seen with `curl` could @@ -728,14 +728,14 @@ definition. | Symptom | First checks | | --- | --- | -| `docker load` is silent | In another SSH session run `ps -eo pid,etime,stat,%cpu,%mem,cmd | grep '[d]ocker load'`, `df -h /`, and `sudo journalctl -u docker -n 30 --no-pager`. Slow microSD extraction is normal. | +| `docker load` is silent | In another SSH session run `ps -eo pid,etime,stat,%cpu,%mem,cmd \| grep '[d]ocker load'`, `df -h /`, and `sudo journalctl -u docker -n 30 --no-pager`. Slow microSD extraction is normal. | | Sandbox enters `ContainerRestarting` | Inspect the image command. It must be `sleep infinity`; do not append `/bin/true` to `sandbox create`. | | `reachy-agent failed to become healthy` | Retry with the 120-second timeout and inspect `/sandbox/logs/reachy-agent.log`. A cold start took about 41 seconds. | | Audio URL says `Service endpoint is not available` | Confirm the inner agent is `running`, then recreate or expose `audio` and check `/health`. The target listener must exist before the route is usable. | | Audio bridge reports `Name or service not known` | Verify controller version `0.2.0`. It preserves the virtual routing hostname while connecting the socket to `127.0.0.1:17670`. | | Reachy says it cannot take a picture | Test `POST http://127.0.0.1:8042/camera/capture`, then test the same path from the sandbox with `/opt/venv/bin/python`. If both work, inspect the model/tool logs and session instructions. | | Local wheel install is rejected by `/api/apps/install` | This endpoint does not accept `source_kind: local`; install the wheel into `/venvs/apps_venv` with `/opt/uv/uv pip install`. | -| Root filesystem is almost full | Run `docker system df` and `sudo du -sh /var/lib/docker /venvs/apps_venv`. Remove transferred archives, obsolete images, failed layers, and old wheel versions—but not the active image or `/venvs/mini_daemon`. | +| Root filesystem is almost full | Run `docker system df` and `sudo du -sh /var/lib/docker /venvs/apps_venv`. Remove transferred archives, obsolete images, failed layers, and old wheel versions, but not the active image or `/venvs/mini_daemon`. | ## Development checks From 522ff7937e642d2f42167acb6d14d5ae395bcb1e Mon Sep 17 00:00:00 2001 From: Kirit93 Date: Mon, 20 Jul 2026 12:25:51 -0700 Subject: [PATCH 41/45] updated note date --- ...licy-controlling-reachy-mini-with-openshell.md} | 14 +++++++++----- 1 file changed, 9 insertions(+), 5 deletions(-) rename docs/dev-notes/posts/{2026-07-13-policy-controlling-reachy-mini-with-openshell.md => 2026-07-20-policy-controlling-reachy-mini-with-openshell.md} (98%) diff --git a/docs/dev-notes/posts/2026-07-13-policy-controlling-reachy-mini-with-openshell.md b/docs/dev-notes/posts/2026-07-20-policy-controlling-reachy-mini-with-openshell.md similarity index 98% rename from docs/dev-notes/posts/2026-07-13-policy-controlling-reachy-mini-with-openshell.md rename to docs/dev-notes/posts/2026-07-20-policy-controlling-reachy-mini-with-openshell.md index 6166cdf4..14535992 100644 --- a/docs/dev-notes/posts/2026-07-13-policy-controlling-reachy-mini-with-openshell.md +++ b/docs/dev-notes/posts/2026-07-20-policy-controlling-reachy-mini-with-openshell.md @@ -1,7 +1,7 @@ --- title: "Bringing Privacy and Security to the Edge with OpenShell" -date: 2026-07-13 -updated: 2026-07-13 +date: 2026-07-20 +updated: 2026-07-20 description: "Edge agents handle sensitive data and make decisions with physical consequences. Reachy Mini shows why privacy and safety controls must be deterministic and local." categories: - Edge AI @@ -24,9 +24,13 @@ card_tags: -
    -

    Author

    -
    +
    +

    + Field note + + Edge AI +

    +
    From 2be6923001de7df15aaa6ddadd50b652de16975d Mon Sep 17 00:00:00 2001 From: Kirit93 Date: Mon, 20 Jul 2026 12:26:33 -0700 Subject: [PATCH 42/45] Updated dev notes --- ...-06-04-bootstrapping-openshell-research.md | 60 ------------------- .../2026-06-05-making-dev-notes-repeatable.md | 49 --------------- 2 files changed, 109 deletions(-) delete mode 100644 docs/dev-notes/posts/2026-06-04-bootstrapping-openshell-research.md delete mode 100644 docs/dev-notes/posts/2026-06-05-making-dev-notes-repeatable.md diff --git a/docs/dev-notes/posts/2026-06-04-bootstrapping-openshell-research.md b/docs/dev-notes/posts/2026-06-04-bootstrapping-openshell-research.md deleted file mode 100644 index fd1121ee..00000000 --- a/docs/dev-notes/posts/2026-06-04-bootstrapping-openshell-research.md +++ /dev/null @@ -1,60 +0,0 @@ ---- -title: Bootstrapping OpenShell Research -date: 2026-06-04 -updated: 2026-06-05 -description: Initial setup for OpenShell Research documentation and Dev Notes. -card_variant: launch -categories: - - Runtime -tags: - - openshell - - research-engineering - - docs - - ci -authors: - - johnnygreco - - zredlined -card_tags: - - openshell - - docs - - ci ---- - -# Bootstrapping OpenShell Research - - - -
    -

    - Field note - - Runtime -

    -
    - - - - Johnny Greco - OpenShell Team @ NVIDIA - - - - - - Alex Watson - OpenShell Team @ NVIDIA - - -
    -
    - - -OpenShell Research starts as a shared engineering home for applications that -turn current research into working systems on the OpenShell runtime. - - - -The first version of this repository establishes the documentation structure, -the Dev Notes section, and CI verification for the generated Zensical site. The -next useful step is to add the first runnable application skeleton and document -the runtime assumptions it depends on. diff --git a/docs/dev-notes/posts/2026-06-05-making-dev-notes-repeatable.md b/docs/dev-notes/posts/2026-06-05-making-dev-notes-repeatable.md deleted file mode 100644 index 7dfb71de..00000000 --- a/docs/dev-notes/posts/2026-06-05-making-dev-notes-repeatable.md +++ /dev/null @@ -1,49 +0,0 @@ ---- -title: Making Dev Notes Repeatable -date: 2026-06-05 -updated: 2026-06-05 -description: A repeatable author and post workflow keeps Dev Notes easy to extend as the research log grows. -categories: - - Process -tags: - - dev-notes - - authors - - workflow -authors: - - kirit93 -card_tags: - - dev-notes - - authors - - workflow ---- - -# Making Dev Notes Repeatable - - - -
    -

    - Field note - - Process -

    -
    - - - - Kirit Thadaka - OpenShell Team @ NVIDIA - - -
    -
    - - -The Dev Notes section should stay easy to grow: add a post, name its authors, -and let the documentation build keep the landing page and navigation aligned. - - - -This pass makes author metadata reusable across posts and keeps generated -elements inside clearly marked regions. The goal is to make each new update feel -like writing a note, not maintaining a miniature website by hand. From 71498c3b230b12e33880ab751f338ea38fead0c8 Mon Sep 17 00:00:00 2001 From: Kirit93 Date: Mon, 20 Jul 2026 12:42:17 -0700 Subject: [PATCH 43/45] Updated blog image --- docs/assets/reachy-mini-openshell/hero.svg | 70 +++++++++++++++++++ docs/dev-notes/index.md | 4 +- ...-controlling-reachy-mini-with-openshell.md | 2 + docs/projects/index.md | 2 +- .../reachy-mini-openshell-demo-tutorial.md | 2 +- .../projects/reachy-mini-openshell-sandbox.md | 2 +- docs/projects/reachy-mini-openshell/index.md | 4 +- .../reachy-mini-openshell/ONBOARD_SETUP.md | 2 +- projects/reachy-mini-openshell/README.md | 2 +- zensical.toml | 2 +- 10 files changed, 82 insertions(+), 10 deletions(-) create mode 100644 docs/assets/reachy-mini-openshell/hero.svg diff --git a/docs/assets/reachy-mini-openshell/hero.svg b/docs/assets/reachy-mini-openshell/hero.svg new file mode 100644 index 00000000..b219bb76 --- /dev/null +++ b/docs/assets/reachy-mini-openshell/hero.svg @@ -0,0 +1,70 @@ + + + + + + + + + + + + + + + + + + + + + + + + OPENSHELL · EDGE AI + Bringing Privacy and + Security to the Edge + with OpenShell + + Deterministic policy and privacy, enforced on the device. + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/docs/dev-notes/index.md b/docs/dev-notes/index.md index 13cb4dd2..84540c19 100644 --- a/docs/dev-notes/index.md +++ b/docs/dev-notes/index.md @@ -32,10 +32,10 @@ hide: Latest from the team
    - +
    diff --git a/docs/dev-notes/posts/2026-07-20-policy-controlling-reachy-mini-with-openshell.md b/docs/dev-notes/posts/2026-07-20-policy-controlling-reachy-mini-with-openshell.md index 14535992..5fe78317 100644 --- a/docs/dev-notes/posts/2026-07-20-policy-controlling-reachy-mini-with-openshell.md +++ b/docs/dev-notes/posts/2026-07-20-policy-controlling-reachy-mini-with-openshell.md @@ -42,6 +42,8 @@ card_tags:
    +![Bringing Privacy and Security to the Edge with OpenShell: a stylized Reachy Mini robot with two green camera eyes inside an OpenShell boundary ring.](../../assets/reachy-mini-openshell/hero.svg) + Useful AI agents now run for long periods of time, taking on critical tasks to accomplish goals. They call tools, learn new skills, write code, and keep working while no one is watching. How do you give autonomy to such a highly capable agent? OpenShell is the secure runtime for autonomous agents. It solves this problem by moving the security layer outside the agent. OpenShell runs your agent in a sandbox and sits in the path of everything the agent does. A policy layer, configured separately from the agent, governs what processes the agent can start, which hosts and ports it can reach, which models it can call, and which other services it needs to invoke along its network path. diff --git a/docs/projects/index.md b/docs/projects/index.md index 6a86e2bc..facfeb5f 100644 --- a/docs/projects/index.md +++ b/docs/projects/index.md @@ -12,7 +12,7 @@ robot-native audio and camera bridge, fixed REST actions, an optional Gradio diagnostic UI, and OpenShell policy enforcement for physical robot tools. **Want the edge architecture and engineering story?** Read -[Designing OpenShell for the Edge](../dev-notes/posts/2026-07-13-policy-controlling-reachy-mini-with-openshell.md). +[Designing OpenShell for the Edge](../dev-notes/posts/2026-07-20-policy-controlling-reachy-mini-with-openshell.md). **Building it on a robot?** Follow the [project-local onboard setup tutorial](https://github.com/NVIDIA/OpenShell-Research/blob/kirit93/reachy-implementation/projects/reachy-mini-openshell/ONBOARD_SETUP.md). diff --git a/docs/projects/reachy-mini-openshell-demo-tutorial.md b/docs/projects/reachy-mini-openshell-demo-tutorial.md index 2d4780f0..562df5f0 100644 --- a/docs/projects/reachy-mini-openshell-demo-tutorial.md +++ b/docs/projects/reachy-mini-openshell-demo-tutorial.md @@ -3,7 +3,7 @@ The original combined guide has been split into two focused documents: - Read **[Designing OpenShell for the Edge: Why Policy Has to Live Next to the - Action](../dev-notes/posts/2026-07-13-policy-controlling-reachy-mini-with-openshell.md)** + Action](../dev-notes/posts/2026-07-20-policy-controlling-reachy-mini-with-openshell.md)** for the reusable edge architecture, design decisions, challenges, and results. - Follow the **[project-local onboard setup tutorial](https://github.com/NVIDIA/OpenShell-Research/blob/kirit93/reachy-implementation/projects/reachy-mini-openshell/ONBOARD_SETUP.md)** diff --git a/docs/projects/reachy-mini-openshell-sandbox.md b/docs/projects/reachy-mini-openshell-sandbox.md index e11e7894..fb4765c1 100644 --- a/docs/projects/reachy-mini-openshell-sandbox.md +++ b/docs/projects/reachy-mini-openshell-sandbox.md @@ -6,4 +6,4 @@ The canonical tutorial now lives beside the runnable project: For the engineering story and reusable edge architecture, read [Designing OpenShell for the Edge: Why Policy Has to Live Next to the -Action](../dev-notes/posts/2026-07-13-policy-controlling-reachy-mini-with-openshell.md). +Action](../dev-notes/posts/2026-07-20-policy-controlling-reachy-mini-with-openshell.md). diff --git a/docs/projects/reachy-mini-openshell/index.md b/docs/projects/reachy-mini-openshell/index.md index 6f14345a..2751ebdd 100644 --- a/docs/projects/reachy-mini-openshell/index.md +++ b/docs/projects/reachy-mini-openshell/index.md @@ -8,7 +8,7 @@ physical effects on Reachy Mini. ## Start here Read **[Designing OpenShell for the Edge: Why Policy Has to Live Next to the -Action](../../dev-notes/posts/2026-07-13-policy-controlling-reachy-mini-with-openshell.md)** +Action](../../dev-notes/posts/2026-07-20-policy-controlling-reachy-mini-with-openshell.md)** for the reusable edge architecture, implementation decisions, challenges, and demo result. @@ -36,7 +36,7 @@ The tutorial progressively adds: ## Project resources -- [Implementation Dev Note](../../dev-notes/posts/2026-07-13-policy-controlling-reachy-mini-with-openshell.md) +- [Implementation Dev Note](../../dev-notes/posts/2026-07-20-policy-controlling-reachy-mini-with-openshell.md) - [Onboard setup and troubleshooting tutorial](https://github.com/NVIDIA/OpenShell-Research/blob/kirit93/reachy-implementation/projects/reachy-mini-openshell/ONBOARD_SETUP.md) - [Application source and README](https://github.com/NVIDIA/OpenShell-Research/tree/kirit93/reachy-implementation/projects/reachy-mini-openshell) - [Motion-disabled policy](https://github.com/NVIDIA/OpenShell-Research/blob/kirit93/reachy-implementation/projects/reachy-mini-openshell/openshell/policy-motion-disabled.yaml) diff --git a/projects/reachy-mini-openshell/ONBOARD_SETUP.md b/projects/reachy-mini-openshell/ONBOARD_SETUP.md index 382c04d4..48aadddf 100644 --- a/projects/reachy-mini-openshell/ONBOARD_SETUP.md +++ b/projects/reachy-mini-openshell/ONBOARD_SETUP.md @@ -7,7 +7,7 @@ access; and OpenShell independently allows or denies the REST requests that can cause physical actions. For the implementation story, architecture decisions, and lessons from building -the demo, read the [Dev Note](https://github.com/NVIDIA/OpenShell-Research/blob/kirit93/reachy-implementation/docs/dev-notes/posts/2026-07-13-policy-controlling-reachy-mini-with-openshell.md). +the demo, read the [Dev Note](https://github.com/NVIDIA/OpenShell-Research/blob/kirit93/reachy-implementation/docs/dev-notes/posts/2026-07-20-policy-controlling-reachy-mini-with-openshell.md). The commands alternate between a **development machine** and **Reachy**. Build the wheel and ARM64 image on the development machine; install and run the final diff --git a/projects/reachy-mini-openshell/README.md b/projects/reachy-mini-openshell/README.md index 64f92c9d..a7dec086 100644 --- a/projects/reachy-mini-openshell/README.md +++ b/projects/reachy-mini-openshell/README.md @@ -7,7 +7,7 @@ deliberately small REST-controlled action surface. > **Building the OpenShell policy demo with a physical Reachy?** Follow the > [onboard setup tutorial](ONBOARD_SETUP.md). For the architecture, implementation > decisions, and lessons learned, read the -> [Dev Note](../../docs/dev-notes/posts/2026-07-13-policy-controlling-reachy-mini-with-openshell.md). +> [Dev Note](../../docs/dev-notes/posts/2026-07-20-policy-controlling-reachy-mini-with-openshell.md). Commands: diff --git a/zensical.toml b/zensical.toml index bbee679f..c2ab4393 100644 --- a/zensical.toml +++ b/zensical.toml @@ -15,7 +15,7 @@ nav = [ "dev-notes/index.md", {"Posts" = [ # dev-notes:nav:start - {"Bringing Privacy and Security to the Edge with OpenShell" = "dev-notes/posts/2026-07-13-policy-controlling-reachy-mini-with-openshell.md"}, + {"Bringing Privacy and Security to the Edge with OpenShell" = "dev-notes/posts/2026-07-20-policy-controlling-reachy-mini-with-openshell.md"}, {"Making Dev Notes Repeatable" = "dev-notes/posts/2026-06-05-making-dev-notes-repeatable.md"}, {"Bootstrapping OpenShell Research" = "dev-notes/posts/2026-06-04-bootstrapping-openshell-research.md"} # dev-notes:nav:end From 9468bea001ed339c4b8db3117f735cb43f2cd0c2 Mon Sep 17 00:00:00 2001 From: Kirit93 Date: Mon, 20 Jul 2026 13:15:05 -0700 Subject: [PATCH 44/45] Updated hero image layout --- docs/dev-notes/index.md | 77 +------------------ ...-controlling-reachy-mini-with-openshell.md | 1 + docs/development/index.md | 4 +- docs/stylesheets/dev-notes.css | 37 +++++++++ scripts/render-dev-notes.py | 39 ++++++++-- tests/test_render_dev_notes.py | 29 +++++++ zensical.toml | 4 +- 7 files changed, 109 insertions(+), 82 deletions(-) diff --git a/docs/dev-notes/index.md b/docs/dev-notes/index.md index 84540c19..c3b70822 100644 --- a/docs/dev-notes/index.md +++ b/docs/dev-notes/index.md @@ -31,16 +31,14 @@ hide: Latest from the team
    -
    + -
    -
    -

    Recent notes

    - The working archive -
    -
    - - -
    -
    diff --git a/docs/dev-notes/posts/2026-07-20-policy-controlling-reachy-mini-with-openshell.md b/docs/dev-notes/posts/2026-07-20-policy-controlling-reachy-mini-with-openshell.md index 5fe78317..0a9db0f9 100644 --- a/docs/dev-notes/posts/2026-07-20-policy-controlling-reachy-mini-with-openshell.md +++ b/docs/dev-notes/posts/2026-07-20-policy-controlling-reachy-mini-with-openshell.md @@ -3,6 +3,7 @@ title: "Bringing Privacy and Security to the Edge with OpenShell" date: 2026-07-20 updated: 2026-07-20 description: "Edge agents handle sensitive data and make decisions with physical consequences. Reachy Mini shows why privacy and safety controls must be deterministic and local." +hero_image: "../../assets/reachy-mini-openshell/hero.svg" categories: - Edge AI tags: diff --git a/docs/development/index.md b/docs/development/index.md index 32e171ec..ae97f624 100644 --- a/docs/development/index.md +++ b/docs/development/index.md @@ -28,7 +28,9 @@ defined in `docs/dev-notes/authors.json`. Use a dated filename such as The renderer uses `categories[0]` as the card topic and `card_tags` as its tags, falling back to `tags`. An optional `card_variant` must have matching card and -artwork CSS modifiers in `docs/stylesheets/dev-notes.css`. +artwork CSS modifiers in `docs/stylesheets/dev-notes.css`. Set `hero_image` to +an image path relative to the post when its card should use the post's hero +instead of generated artwork. Hero images must live under `docs/`. Do not edit content inside these generated marker pairs: diff --git a/docs/stylesheets/dev-notes.css b/docs/stylesheets/dev-notes.css index db1e987f..fdf3985e 100644 --- a/docs/stylesheets/dev-notes.css +++ b/docs/stylesheets/dev-notes.css @@ -479,6 +479,19 @@ body:has(.openshell-home-page) .md-path { border-bottom: 1px solid var(--openshell-rule); } +.dev-note-card--featured.dev-note-card--has-image .dev-note-card__link { + grid-template-columns: 1fr; +} + +.dev-note-card--featured.dev-note-card--has-image .dev-note-card__visual { + min-height: 0; + aspect-ratio: 1200 / 630; +} + +.dev-note-card--featured.dev-note-card--has-image .dev-note-card__copy { + border-left: 1px solid var(--openshell-rule); +} + .dev-note-card__visual { position: relative; display: block; @@ -525,6 +538,26 @@ body:has(.openshell-home-page) .md-path { transition: transform 400ms ease; } +.dev-note-card__visual--image { + background: var(--openshell-paper-deep); +} + +.dev-note-card__visual--image::before, +.dev-note-card__visual--image::after { + display: none; +} + +.dev-note-card__visual-image { + position: absolute; + inset: 0; + display: block; + width: 100%; + height: 100%; + object-fit: cover; + object-position: center; + transition: transform 300ms ease; +} + .dev-note-card__visual--runtime, .dev-note-card__visual--launch { background: @@ -703,6 +736,10 @@ body:has(.openshell-home-page) .md-path { transform: translate(-50%, -50%) rotate(-27deg); } +.dev-note-card__link:hover .dev-note-card__visual-image { + transform: scale(1.015); +} + .dev-note-card__link:hover .dev-note-card__read::after { transform: translate(0.15rem, -0.15rem); } diff --git a/scripts/render-dev-notes.py b/scripts/render-dev-notes.py index 4f9cdb66..3f4232dd 100644 --- a/scripts/render-dev-notes.py +++ b/scripts/render-dev-notes.py @@ -199,12 +199,39 @@ def card_visual_class(post: dict[str, Any]) -> str: return slug or "research" -def render_card_visual(post: dict[str, Any]) -> str: +def card_hero_image_url(post: dict[str, Any]) -> str | None: + """Resolve an optional post-relative hero image for the Dev Notes index.""" + raw_path = str(post["metadata"].get("hero_image", "")).strip() + if not raw_path: + return None + + docs_root = (ROOT / "docs").resolve() + hero_path = (post["path"].parent / raw_path).resolve() + try: + docs_relative = hero_path.relative_to(docs_root) + except ValueError as exc: + raise ValueError(f"{post['path']} hero_image must stay inside {docs_root}") from exc + if not hero_path.is_file(): + raise ValueError(f"{post['path']} hero_image does not exist: {hero_path}") + + return (Path("..") / docs_relative).as_posix() + + +def render_card_visual(post: dict[str, Any], *, eager: bool = False) -> str: metadata = post["metadata"] + variant = html.escape(card_visual_class(post), quote=True) + hero_image = card_hero_image_url(post) + if hero_image: + loading = "eager" if eager else "lazy" + priority = ' fetchpriority="high"' if eager else "" + return f""" """ + categories = require_list(metadata, "categories", post["path"]) label = categories[0] if categories else "Research" date_stamp = post["published"].strftime("%Y.%m.%d") - return f"""
    +
    June 5, 2026 / Dev Note / Documentation diff --git a/docs/dev-notes/posts/2026-07-13-policy-controlling-reachy-mini-with-openshell.md b/docs/dev-notes/posts/2026-07-13-policy-controlling-reachy-mini-with-openshell.md new file mode 100644 index 00000000..9d1e1843 --- /dev/null +++ b/docs/dev-notes/posts/2026-07-13-policy-controlling-reachy-mini-with-openshell.md @@ -0,0 +1,548 @@ +--- +title: "Designing OpenShell for the Edge: Why Policy Has to Live Next to the Action" +date: 2026-07-13 +updated: 2026-07-13 +description: "Edge agents handle sensitive data and make decisions with physical consequences. Reachy Mini shows why privacy and safety controls must be deterministic and local." +categories: + - Edge AI +tags: + - reachy-mini + - openshell + - edge-ai + - sandbox + - robotics + - policy +authors: + - kirit93 +card_tags: + - edge-ai + - reachy-mini + - policy +--- + +# Designing OpenShell for the Edge: Why Policy Has to Live Next to the Action + + + +
    +

    Author

    +
    + + + + Kirit Thadaka + OpenShell Team @ NVIDIA + + +
    +
    + + +AI agents are moving from assistants that wait for instructions to long-running +systems that pursue goals, use tools, add skills, write code, and continue +working while the operator is out of the loop. That growing autonomy is the +motivation behind OpenShell: the more an agent can change and act on its own, +the less we can rely on guardrails implemented inside the same process. + +OpenShell moves the control point outside the agent. The agent can remain +capable and autonomous inside a sandbox, while separately configured policy +governs its filesystem, process, network, and inference access. If the model is +prompt-injected, a tool is compromised, or the agent rewrites part of its own +workflow, it still cannot grant itself permissions that the runtime has not +allowed. + +At the edge, the same trust problem gains a physical dimension. An agent may +observe people and places, handle data from microphones, cameras, and sensors, +and make decisions that move machines or change local systems. A failure is no +longer limited to a bad shell command or leaked cloud credential. It can expose +data that was supposed to remain on-site or cause an action with material +real-world consequences. + +That creates two immediate requirements. Some data should never leave the +device or the site where it was produced. Some actions should never be possible +in a particular deployment, even if a model, prompt, tool, skill, or application +update tries to request them. + +Trust at the edge therefore requires the OpenShell control plane to move with +the agent. The boundary must be deterministic, provisioned independently, and +enforced locally before data leaves the device or an action reaches the +hardware. + +We used Reachy Mini to explore what that deployment looks like. The resulting +pattern keeps the agent in an on-device OpenShell sandbox, keeps hardware +ownership in a small trusted native process, and enforces policy locally before +a request can cross into the rest of the device. + + + +This post walks through the design principles behind that architecture. Reachy +makes the result easy to see: the camera works and the head does not move. The +same boundaries apply to cameras, lab instruments, industrial gateways, +vehicles, kiosks, and other AI-enabled edge systems. + +The copy-and-run installation procedure lives separately in the +[onboard setup tutorial](https://github.com/NVIDIA/OpenShell-Research/blob/kirit93/reachy-implementation/projects/reachy-mini-openshell/ONBOARD_SETUP.md). + +--- + +## Trust Has to Move with the Agent + +The same agent might run in a factory, a laboratory, a warehouse, a retail +space, or a home. Each deployment has different data boundaries, physical +risks, operators, and acceptable actions. Security controls therefore have to +be applied where the device is running, not only where the model is hosted. + +**Privacy has to be enforced before egress.** A camera may be allowed to analyze +a scene locally but prohibited from sending raw video off-site. A microphone may +support an on-device interaction while recordings remain local. A lab instrument +may expose a derived result while its raw measurements and sample metadata never +leave the facility. These devices need deterministic enforcement of where +sensitive data can be handled: what must stay on the device, what approved +services may process, and what may leave the local environment. This is where a +policy runtime such as OpenShell fits: it enforces those boundaries at the edge, +independently of the agent's instructions or behavior. + +**Safety has to be enforced before action.** An inspection robot may use its +camera everywhere but move only inside a controlled workcell. A building agent +may read temperature data but not change a setpoint in a public deployment. A +field device may expose an emergency stop while route changes remain disabled. +The same software image can be paired with different policies for different +operating environments. + +**Controls have to survive agent evolution.** Models change. Prompts are tuned. +Tools are added. Application code is upgraded. A safety or privacy guarantee +that exists only inside one prompt or one version of the tool implementation has +to be re-established after every change. A separately provisioned policy +boundary remains in force while the agent evolves behind it. + +Deterministic enforcement does not mean that OpenShell understands the meaning +of every image, measurement, motor command, or physical environment. It means +the agent is confined to explicit filesystem and network boundaries, and that +device-specific capabilities cross through narrow trusted interfaces that +policy can allow or deny. OpenShell decides whether the agent may call a +capability. The trusted adapter constrains what that call can request, and the +device controller enforces the hardware limits while executing it, such as +joint ranges, speed limits, and emergency-stop behavior. + +The current Reachy demo uses the OpenAI Realtime API through an explicitly +allowed WebSocket endpoint, so its conversation audio and requested camera frame +are sent to that approved service. A deployment with strict data-residency +requirements could instead permit a local model endpoint, an approved on-device +preprocessing service, or only derived data. The important point is that the +egress decision is made by local policy; it is not implied by where the model +happens to run. + +--- + +## An Edge Agent Is Not Just a Smaller Deployment + +The straightforward approach is to take an existing agent, run it on the +device, and give it access to the local SDK or REST API. That is enough for an +early prototype. The agent can call the model, invoke a tool, and make the +hardware respond. + +Simply removing device access is not a solution because the agent can no longer +do the job. Requiring a person to approve every camera capture or movement +makes the system safer, but gives up the autonomy that made the agent useful. +Giving the agent full local access preserves capability and autonomy, but leaves +a long-running, evolving process responsible for policing itself. + +The goal is to preserve all three properties: useful device capabilities, +meaningful autonomy, and controls the agent cannot rewrite. That requires an +enforcement layer outside the agent process. + +The direct-SDK approach also collapses several different kinds of authority +into one process. + +**The agent gets more device access than it needs.** A robot SDK may expose +motors, raw targets, camera configuration, recorded motions, application +management, and system state. A conversational agent that needs five fixed head +directions should not inherit that entire surface. + +**Policy is too far from the effect.** A remote model provider can decide which +tool to call, but it should not be the final authority on whether a local motor, +camera, or actuator is used. That decision belongs on the device, immediately +before the request reaches the controller. + +**The product lifecycle and the agent lifecycle are different.** Operators +choose credentials, images, resource limits, and policy. Users start and stop +an application. Recreating the security boundary every time the app starts +mixes those responsibilities and gives the runtime more provisioning authority +than it needs. + +**Edge resources change the architecture.** Disk, memory, cold-start time, +networking, and hardware ownership are not deployment footnotes on a small +device. They determine which processes can run, which dependencies belong in +the sandbox, and how the application should recover. + +These are not problems with robots or language models. They come from treating +an edge agent as a conventional application that happens to run on smaller +hardware. What we needed was a clearer system of boundaries. + +--- + +## An Edge Agent as a System of Boundaries + +The shift is to separate reasoning, policy enforcement, hardware ownership, and +device execution into components with focused responsibilities. + +1. **The model reasons.** It interprets the conversation and selects from the + tools the application advertises. The model can be remote or local. +2. **The sandboxed agent turns intent into a concrete request.** It owns the + conversation state and model-facing tool logic, but it does not own the + hardware. +3. **OpenShell decides whether the request may leave the sandbox.** Policy is + evaluated on the edge device using the calling binary, destination, port, + HTTP method, path, and query. +4. **A trusted adapter exposes a narrow capability.** It owns native device + objects and translates an approved request into one bounded operation. +5. **The device controller produces the effect.** Motors, sensors, cameras, or + other local systems are reached only after the preceding boundaries allow + it. + +```text +cloud or local model + ↕ +agent in an on-device OpenShell sandbox + ↓ +local OpenShell policy decision + ↓ +narrow trusted capability adapter + ↓ +physical device, sensor, or local data +``` + +This decomposition gives each boundary something specific to enforce and +something specific to test. We can change the model without changing the robot +adapter. We can change the policy without rebuilding the image. We can restart +the application without recreating credentials or resource limits. And we can +test the allowed camera path independently from the denied movement path. + +The sandbox starts from deny-by-default policy rather than inheriting every +capability available on the host. When Reachy hits a denied action, the agent +receives a structured failure and can explain the constraint instead of silently +bypassing it. An operator can then update the sandbox policy without rebuilding +the application, while the decision to grant new authority remains outside the +agent. + +--- + +## Design Principles Behind OpenShell at the Edge + +With that framing in place, these are the principles that shaped the Reachy +implementation. + +### Put policy next to the data and the effect + +The policy engine runs on the same Reachy onboard computer as the agent and +robot daemon. When the agent attempts a movement request, OpenShell decides +locally whether that request can reach the daemon. A denial stops at the policy +boundary; it does not depend on the remote model deciding to withdraw the tool +call. + +The same boundary controls egress. The sandbox can connect only to destinations +and paths permitted by its policy. A deployment can allow an approved remote +model, route through a local privacy service, or deny remote model access and +use an on-device endpoint instead. + +This is the central edge property. The model may remain a cloud service, but +the authority to move local data and use local capabilities remains local. +Model placement and policy placement are independent choices. + +### Expose capabilities, not complete APIs + +The conversation agent receives three robot tools: + +- `move_head(directions)` accepts `left`, `right`, `up`, `down`, and `front`. +- `stop_motion()` stops active movements. +- `camera(question)` requests one image for the current conversation. + +The model selects one of those tools; it does not construct an HTTP request +itself. Python handlers inside the sandbox translate `move_head` into +`POST /api/move/goto`, `stop_motion` into `POST /api/move/stop`, and `camera` +into `POST /camera/capture`. OpenShell then evaluates the concrete request before +it can leave the sandbox. + +The agent does not discover the complete Reachy API. Fixed tool inputs become +fixed REST requests, making the intended capability visible at the network +boundary. This is easier to reason about than giving an agent a general-purpose +SDK and trying to enumerate every unsafe combination afterward. + +### Keep hardware handles in trusted native code + +Reachy's microphone, speaker, and camera are already managed by its native app +lifecycle. Moving those objects into the sandbox would duplicate hardware +ownership and pull the full Reachy SDK, media stack, and vision dependencies +into the agent image. + +Instead, a small trusted Reachy App owns the native media objects. It forwards +PCM audio through a local WebSocket and exposes one argument-free camera route: +`POST /camera/capture`. The sandbox gets the capability to converse and request +one frame; it does not get the camera handle, device selection, resolution +controls, or a filesystem path. + +### Provision once, operate many times + +Creating a sandbox chooses the image, provider, credentials, filesystem policy, +network policy, CPU limit, and memory limit. Those are operator decisions, so +the native Reachy App does not create or delete the sandbox. + +The model credential is configured through the OpenShell provider and attached +at provisioning time; it is not baked into the Docker image, policy file, or +native controller. The normal Reachy application lifecycle never asks for or +recreates that credential boundary. + +The sandbox remains provisioned while `reachy-agent-control start|stop|status` +manages the conversation process inside it. Starting the Reachy App verifies +the sandbox, starts the agent, exposes the audio route, and connects media. +Stopping the app closes media and stops the agent process. The policy and +provider remain intact for the next start. + +### Treat resource constraints as design inputs + +The tested Reachy had 3.7 GiB usable RAM, 2 GiB swap, and a 14 GiB root +partition. We gave the sandbox a 2 CPU and 2 GiB memory ceiling and built the +image on a development machine rather than consuming the robot's CPU, memory, +and microSD write budget. + +The runtime image uses a slim Python base, a disposable wheel-building stage, +a REST-only dependency list, and an application install with `--no-deps`. That +keeps the Reachy SDK, MuJoCo, OpenCV, simulator, dance, and local vision stacks +out of the sandbox. The resulting ARM64 image was 339,495,096 bytes, or about +339 MB, while retaining the networking tools OpenShell requires. + +### Design for both remote and local models + +The demonstrated Realtime model is remote. The conversation, policy, device +adapter, and robot controller still run on Reachy. This matters because “edge” +does not have to mean “fully offline,” and local enforcement does not require a +local foundation model. + +The same architecture can later use an on-device model. The model endpoint +changes; the sandbox, trusted adapter, and local action boundary do not. + +The current policy explicitly allows the chat application to connect to one +OpenAI Realtime endpoint. It does not provide content-aware privacy enforcement, +but it establishes the egress boundary needed to add it. + +A privacy-focused deployment could deny direct model access and make an +OpenShell Middleware service the sandbox's only permitted model destination. +Privacy Guard, which is on the OpenShell roadmap, could use that service to +detect sensitive camera, microphone, or sensor data and decide whether to block +it, redact it, process it locally, or route it to an approved model. The agent +would not be able to bypass that decision by connecting directly to another +model endpoint. + +--- + +## What This Looks Like on Reachy + +```mermaid +flowchart TB + Human["Person near Reachy"] + + subgraph Robot["Reachy Mini onboard computer"] + Native["Trusted native Reachy App\nmicrophone, speaker, camera"] + Gateway["OpenShell gateway\nand policy engine"] + + subgraph Sandbox["OpenShell sandbox"] + Agent["Conversation agent\nRealtime client and fixed tools"] + Audio["Loopback audio service\n127.0.0.1:8765"] + end + + Daemon["Reachy daemon REST API\n127.0.0.1:8000"] + Camera["One-frame adapter\n127.0.0.1:8042"] + Hardware["Mic, speaker, camera, motors"] + end + + Model["OpenAI Realtime API"] + + Human <-->|"voice"| Hardware + Native <-->|"Reachy media API"| Hardware + Native <-->|"PCM through exposed service"| Gateway + Gateway <--> Audio + Audio <--> Agent + Agent <-->|"policy-checked Realtime WebSocket"| Gateway + Gateway <--> Model + Agent -->|"robot REST action"| Gateway + Gateway -->|"permitted request"| Daemon + Daemon --> Hardware + Agent -->|"POST /camera/capture"| Gateway + Gateway --> Camera + Camera --> Native +``` + +There is no laptop, browser, or Gradio page in the runtime path. The complete +request flow is: + +1. The trusted Reachy App captures microphone audio and streams PCM frames to + the audio service inside the sandbox. +2. The conversation agent sends that audio over its policy-approved WebSocket + connection to the OpenAI Realtime API. The model receives the conversation + together with the fixed `move_head`, `stop_motion`, and `camera` tool + definitions. +3. The model returns response audio or selects a tool. For a tool call, Python + code in the sandbox translates the model's arguments into one of the fixed + REST requests. +4. OpenShell evaluates the destination, port, method, and path. An allowed + request reaches the trusted adapter or Reachy daemon. A denied request returns + a policy error without reaching the hardware. +5. The conversation agent uses the tool result or policy error to continue the + conversation, and response audio travels back through the native Reachy App + to the robot's speaker. + +The active demo policy separates two physical capabilities: + +```text +POST host.openshell.internal:8042/camera/capture allowed +POST host.openshell.internal:8000/api/move/goto denied +``` + +When a person says, “Take a picture of me,” the agent calls `camera`, OpenShell +allows the capture path, the trusted adapter returns one bounded JPEG, and +Reachy describes it aloud. + +When the person says, “Turn right and take a picture,” the agent attempts +`POST /api/move/goto`. OpenShell returns a denial before the request reaches the +Reachy daemon. The robot stays still, and the denial becomes part of Reachy's +spoken response. + +The important distinction is that the application is not simply choosing to +refuse movement. The model-facing process attempts a real action, and a +separately configured policy boundary prevents the physical effect. + +--- + +## Why Narrow Endpoints Matter + +OpenShell's REST policy can match the calling binary, destination, method, +path, and query. It does not currently enforce arbitrary values nested inside a +JSON request body. If a broad endpoint can express many operations, allowing +that path also allows the sandbox to submit any body accepted by that endpoint. + +Reachy's fixed direction-to-pose mapping reduces normal model behavior to five +known poses, but that mapping is application validation rather than OpenShell +policy. The camera path has a stronger boundary because the request has no +model-controlled camera settings. The adapter chooses the already-open camera, +captures one JPEG, limits its size, rate-limits requests, and writes nothing to +disk. + +We intentionally stopped at REST method and path enforcement to keep the demo +small. OpenShell also supports generic JSON-RPC method rules. A next step could +add a small trusted JSON-RPC adapter that exposes semantic methods such as +`reachy.look_up` and `reachy.turn_right`. Policy could then allow or deny those +methods independently instead of treating every head movement as the same +`POST /api/move/goto` capability. + +Generic JSON-RPC policy currently matches the method, not arbitrary values in +`params`. Restrictions on angle, speed, distance, or duration would therefore +remain in the trusted adapter or device controller until OpenShell adds argument +matching. The JSON-RPC adapter would improve action-level policy granularity, +but it would not replace hardware safety validation. + +The same approach applies elsewhere. Rather than expose a broad control API, +an edge integration can define paths such as `/inspection/capture`, +`/instrument/read`, `/vehicle/emergency-stop`, or `/alarm/acknowledge`. The +trusted adapter defines exactly what each operation means, and OpenShell gains +a narrow capability it can allow or deny. + +--- + +## What We Learned Bringing It Onto the Robot + +The move from a development machine to a small onboard computer exposed several +assumptions that the final architecture had to make explicit. + +**A persistent product needs a persistent sandbox.** Starting a sandbox with a +one-shot command caused the container to exit and restart. The final image stays +alive with `sleep infinity`, while the Reachy lifecycle starts and stops only +the inner agent process. + +**A service definition is not the same as a healthy service.** The audio route +could exist before the sandbox listener was ready. The native app now starts +the listener, verifies health, and only then ensures the OpenShell service route +is available. + +**Cold starts on edge hardware need realistic timeouts.** Importing and starting +the audio stack took roughly 41 seconds on the tested robot. A 120-second health +window handles the first start without hiding a process that never becomes +healthy. + +**Storage needs installation headroom, not just runtime headroom.** The +compressed archive, expanded image, Docker extraction layers, OpenShell +installation, and Reachy Apps Python environment can coexist temporarily. The +robot needs several gigabytes free even though the final sandbox image is only +about 339 MB. + +These details are easy to dismiss as deployment issues. On an edge product, +they are part of the architecture because they determine whether the security +boundary survives normal starts, updates, failures, and operator workflows. + +--- + +## What This Pattern Makes Possible + +Reachy is one concrete system, but its components map cleanly to other edge +applications. + +**Industrial inspection.** An agent can read sensors and capture evidence while +policy denies production-line or actuator changes. + +**Smart cameras.** An agent can describe a scene and send an approved alert +while continuous streaming, PTZ movement, and arbitrary upload destinations +remain unavailable. + +**Lab instruments.** An agent can read measurements and prepare a run while +calibration, parameter changes, start, and stop remain separate policy-controlled +operations. + +**Field robots and vehicles.** Telemetry and camera access can remain distinct +from navigation, docking, route changes, and payload controls. + +**Building-control gateways.** Read-only diagnosis can be separated from HVAC +setpoints, doors, alarms, and maintenance actions. + +**Kiosks and local data appliances.** Microphone, speaker, approved peripherals, +local data, and outbound services can each have their own boundary. + +OpenShell does not infer the safety semantics of a motor, valve, instrument, or +door. Each product still needs domain-specific safety engineering and trusted +adapters. What generalizes is the placement of the boundary: the less-trusted +agent runs inside the sandbox, and policy-approved requests cross into narrowly +defined device capabilities. + +--- + +## Summary + +Running autonomous, evolving agents at the edge is a systems problem, not just +a container-build problem. The Reachy implementation reflects seven principles: + +1. Keep the final control point outside the agent process. +2. Put policy on the device, next to the data and actions it controls. +3. Give the agent narrow capabilities rather than a complete hardware API. +4. Keep hardware handles and native SDK objects in a small trusted process. +5. Separate operator provisioning from the product's Start/Stop lifecycle. +6. Treat CPU, memory, disk, networking, and cold-start time as architecture + inputs. +7. Keep model placement independent from the local action boundary. + +The result is more than a policy-controlled robot demo. It is a deployment +pattern in which OpenShell becomes the on-device isolation and policy layer for +autonomous AI-enabled edge systems. As future agent versions gain new models, +prompts, tools, and skills inside the sandbox, those changes do not automatically +widen their authority over the device. Reachy makes the pattern visible: the +same agent can use the camera, attempt movement, be denied locally, and explain +that denial to the person standing in front of it. + +Moving from this reference implementation to production would add fleet-level +policy distribution, signed and attested images, bounded logs, structured audit +correlation, over-the-air updates, explicit offline behavior, and +safety-specific adapters for each class of hardware. Those are the next systems +problems around a boundary that now works on real edge hardware. + +Key resources: + +1. [Onboard Reachy Mini + OpenShell setup](https://github.com/NVIDIA/OpenShell-Research/blob/kirit93/reachy-implementation/projects/reachy-mini-openshell/ONBOARD_SETUP.md) +2. [Reachy Mini OpenShell project source](https://github.com/NVIDIA/OpenShell-Research/tree/kirit93/reachy-implementation/projects/reachy-mini-openshell) +3. [Camera-enabled, motion-disabled policy](https://github.com/NVIDIA/OpenShell-Research/blob/kirit93/reachy-implementation/projects/reachy-mini-openshell/openshell/policy-camera-enabled-motion-disabled.yaml) diff --git a/docs/index.md b/docs/index.md index e4cfba6d..d9e3403c 100644 --- a/docs/index.md +++ b/docs/index.md @@ -14,15 +14,16 @@

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