From b9207b437aa7ac4e31e5822f1111170b60fd41d3 Mon Sep 17 00:00:00 2001 From: Johnny Greco Date: Wed, 24 Jun 2026 17:32:46 +0000 Subject: [PATCH 01/22] Add Reachy Mini OpenShell research scaffold --- projects/README.md | 2 + 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, 577 insertions(+) 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 index 165208cb..6363ca58 100644 --- a/projects/README.md +++ b/projects/README.md @@ -8,3 +8,5 @@ Current projects: - `python-project-template`: Minimal, production-ready Python project scaffold managed with uv. +- `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 d2d9bc240fbd9dccd561a7dcc3e637390010c74b Mon Sep 17 00:00:00 2001 From: Johnny Greco Date: Wed, 24 Jun 2026 17:41:20 +0000 Subject: [PATCH 02/22] Address Reachy scaffold review findings --- README.md | 4 +- 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(+), 10 deletions(-) create mode 100644 projects/reachy-mini-openshell/tests/test_reachy_constructors.py diff --git a/README.md b/README.md index d30c3344..4d4540b7 100644 --- a/README.md +++ b/README.md @@ -12,8 +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 projects and a reusable Python - project template. +- `projects/` contains self-contained research projects, including the reusable + Python template and Reachy Mini OpenShell application. - `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 d106850778f424e5884b371e00ae62232d47a48e Mon Sep 17 00:00:00 2001 From: Johnny Greco Date: Wed, 24 Jun 2026 17:50:49 +0000 Subject: [PATCH 03/22] Tighten Reachy runtime defaults --- 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 +++++++++---------- 9 files changed, 29 insertions(+), 29 deletions(-) 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 7215d5e914e78ac52494758649bd002e90c77209 Mon Sep 17 00:00:00 2001 From: Johnny Greco Date: Wed, 24 Jun 2026 17:14:57 -0400 Subject: [PATCH 04/22] 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 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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 + 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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 dc0cae1349af841c97e57036a42084f19d8c5aff Mon Sep 17 00:00:00 2001 From: Johnny Greco Date: Wed, 24 Jun 2026 17:50:36 -0400 Subject: [PATCH 05/22] 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 a94321b80ff0491a5895c7ed0cb18a477dba4ac2 Mon Sep 17 00:00:00 2001 From: Johnny Greco Date: Wed, 24 Jun 2026 18:33:49 -0400 Subject: [PATCH 06/22] Fix Reachy Mini dependency sync --- README.md | 2 +- projects/README.md | 4 +- projects/reachy-mini-openshell/README.md | 236 +- projects/reachy-mini-openshell/pyproject.toml | 9 +- projects/reachy-mini-openshell/uv.lock | 2949 +++++++++++++++++ 5 files changed, 3180 insertions(+), 20 deletions(-) create mode 100644 projects/reachy-mini-openshell/uv.lock diff --git a/README.md b/README.md index 4d4540b7..90daf0cf 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 projects, including the reusable - Python template and Reachy Mini OpenShell application. + Python template and 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 6363ca58..472bc3aa 100644 --- a/projects/README.md +++ b/projects/README.md @@ -8,5 +8,5 @@ Current projects: - `python-project-template`: Minimal, production-ready Python project scaffold managed with uv. -- `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 8a0b2a4595fba67a5f19754f03eeb161dcfc4f2d Mon Sep 17 00:00:00 2001 From: Johnny Greco Date: Wed, 24 Jun 2026 23:17:09 -0400 Subject: [PATCH 08/22] 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 822a144753e799b6373df3e211c03c527b230cfe Mon Sep 17 00:00:00 2001 From: Johnny Greco Date: Wed, 24 Jun 2026 23:17:53 -0400 Subject: [PATCH 09/22] 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 527cb052d03efb31c23b4923afd0ca1bd479a87e Mon Sep 17 00:00:00 2001 From: Johnny Greco Date: Thu, 25 Jun 2026 19:10:16 +0000 Subject: [PATCH 11/22] 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 fcf4fb9344b06cf341d6c47c6836794787ec476e Mon Sep 17 00:00:00 2001 From: Johnny Greco Date: Thu, 25 Jun 2026 19:14:52 +0000 Subject: [PATCH 12/22] 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 "$@" From 253b5e23eba6af32178b8fd8d0fa2546b436aef9 Mon Sep 17 00:00:00 2001 From: Johnny Greco Date: Thu, 25 Jun 2026 22:41:57 +0000 Subject: [PATCH 13/22] Add Riva STT microphone mode --- projects/reachy-mini-openshell/.env.example | 15 + projects/reachy-mini-openshell/README.md | 49 +- projects/reachy-mini-openshell/pyproject.toml | 11 + .../reachy_mini_conversation_app/config.py | 1 + .../src/reachy_mini_conversation_app/main.py | 20 +- .../openai_realtime.py | 125 ++- .../reachy_mini_conversation_app/riva_asr.py | 202 ++++ .../tests/test_openai_realtime.py | 72 +- projects/reachy-mini-openshell/uv.lock | 919 ++++++++++-------- 9 files changed, 951 insertions(+), 463 deletions(-) create mode 100644 projects/reachy-mini-openshell/src/reachy_mini_conversation_app/riva_asr.py diff --git a/projects/reachy-mini-openshell/.env.example b/projects/reachy-mini-openshell/.env.example index 42515c10..2a82e724 100644 --- a/projects/reachy-mini-openshell/.env.example +++ b/projects/reachy-mini-openshell/.env.example @@ -2,6 +2,21 @@ OPENAI_API_KEY=${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 54b398c88ce8336c473ba12a0836921246fa123b Mon Sep 17 00:00:00 2001 From: Johnny Greco Date: Thu, 25 Jun 2026 23:20:55 +0000 Subject: [PATCH 15/22] 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 = "onnxruntime", version = "1.27.0", source = { registry = "https://pypi.org/simple" }, marker = "(python_full_version >= '3.11' and 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 == 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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 b798e35c5641ea7419f8baba3e00e06c9cafa634 Mon Sep 17 00:00:00 2001 From: Johnny Greco Date: Fri, 26 Jun 2026 16:07:11 -0400 Subject: [PATCH 16/22] 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

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