Pitwall — Trustable AI Racing Coach

Tests Smoke Routes ADRs Agents PWA design
Python Platform Field test License Explainer

→ Project Explainer — architecture, cue distribution, Sonoma corner doctrine, team.

A real-time, on-device coaching system for track-day drivers. Runs on a Pixel 10 via Termux: ingests CAN telemetry over USB from the car's OBD-II port, makes coaching decisions with on-device Gemma 4 (via litert-lm), and pairs with a Vue PWA (pitwall-web, sibling repo, fully designed in [docs/vue/](docs/vue/README.md), implementation pending) for presentation. Built for the May 23, 2026 Sonoma Raceway field test — no cloud dependency for the core coaching loop.

Three LLM tiers, all on-device:

Tier	Model	Runtime	When
Hot path	—	`sonic_model` + canonical phrases	In-drive, < 50 ms
Warm path	Gemma 4 E2B	`litert_lm.Engine` (in-process)	In-drive brief cues, < 100 ms
Paddock	Gemma 4 E4B	`lit serve` + 18 ADK agents	Pre-brief, debrief, Q&A, 2–15 s

Table of contents

Status
What this is / what this isn't
Repo layout
Quick start
Architecture
ADK multi-agent coaching
Performance budget
Hardware
Data privacy & residency
Key documentation
Test status
Roadmap
Frozen artefacts
Team 2 (Intermediate, BMW M3)
Acknowledgements
Contributing
Code style
Changelog
License

The architecture is documented across 21 ADRs. The four most recent focus on the ADK paddock backend: ADR-018 (field-readiness + pedagogy tuning from the 2026-04-29 Team 2 review), ADR-019 (ADK multi-agent plan), ADR-020 (7 structural fixes: PitwallOrchestrator, SequentialAgent/ParallelAgent pipelines, SQL safety, output_key pattern), and ADR-021 (second audit: Runner API, KV cache via persistent sessions, PitwallTracingPlugin + DuckDB agent telemetry).

What this is / what this isn't

What this is: an in-cabin AI race coach for solo track-day drivers, running offline on a Pixel + USB-CAN. Hot-path coaching cues at < 50 ms (sonic_model + canonical phrase library, no LLM), warm-path verbal coaching from on-device Gemma 4 E2B (paddock pre-brief + post-session debrief, via litert-lm), and a full 18-agent ADK paddock coaching system backed by Gemma 4 E4B. Coach avatar emotion (12-state taxonomy) is Gemma-controlled — the LLM emits an [EMOTION: ...] tag with each reply, surfaced to the PWA so the sprite plays the matching animation. Telemetry sinks into local DuckDB (including agent traces); analytics run client-side; no cloud is required for the core coaching loop.

What this isn't: a Garmin Catalyst (post-session debrief, fixed heuristics), an AiM Solo (pure logger, no coaching), or a cloud-only LLM tool. The differentiator is real-time coaching that works without cell coverage, grounded in published pedagogy (Ross Bentley) and adapted to driver skill level.

Status

Bridge: shipped. 56 HTTP endpoints, 358 tests passing, 0 skipped, smoke-tested end-to-end against a real 8273-frame Sonoma VBO with 51 assertions green.
CAN pipeline: shipped. python-can reader + simulator + DBC; 6 round-trip tests on interface='virtual'. USB-CAN device enumeration via pyserial — adapter VID:PID lookup table covers CANable, Macchina M2, Korlan USB2CAN, PEAK, Kvaser, FTDI ELM327, CH340.
Termux foreground service: shipped. Drop-in install package in [deploy/termux/](deploy/termux/INSTALL.md).
Three-tier coach architecture (ADR-017): shipped. In-drive cues are canonical phrases (no LLM); paddock brief + debrief are Gemma-via-litert-lm; cloud Gemini removed entirely.
Field-readiness blockers + pedagogy tuning (ADR-018): shipped 2026-04-30. LLM friction sink, audio ducker, 1D Kalman dead-reckoning, intermediate-driver pedagogy refit.
ADK multi-agent paddock backend (ADR-019–021): shipped 2026-05-01. 18 agents, 15 tools, PitwallOrchestrator(BaseAgent), DebriefPipeline with ParallelAgent, BriefPipeline, Runner + persistent sessions for KV cache reuse, PitwallTracingPlugin + agent_traces DuckDB table, AgentMetaAgent, multi-turn Q&A (/coach/ask). All phases shipped ahead of original post-Sonoma schedule.
**pitwall-web Vue PWA**: design-only. 54 markdown files in [docs/vue/](docs/vue/README.md) — 38 screens specced, foundation
- systems + sprite spec + character bible + Gemma-controlled emotion taxonomy + god navigation map. Code lives in a future sibling repo; implementation hasn't started.
Sonoma field test: May 23, 2026.

Repo layout

pitwall/
├── src/pitwall/                      # Pitwall Backend (Flask API)
│   ├── __main__.py                   # Application entrypoint
│   └── features/                     # Feature-Sliced Design domains
│       ├── telemetry/                # can_reader, signals API
│       ├── session/                  # vbo_parser, analytics, profiles, debrief API
│       ├── coaching/                 # ADK agents, coach engine, TTS, LiteRT
│       ├── track/                    # sonoma lore, track loaders, track API
│       └── realtime/                 # Live cue streaming via SSE
├── src/simulator/                    # Standalone HTTP Clients
│   ├── simulator.py                  # VBO-driven simulation runner
│   ├── pitwall_app.py                # Standalone replay TUI
│   └── vbo_client.py                 # Standalone VBO parser for clients
├── scripts/                          # Utility scripts
│   ├── best_sonoma_lap.py            # S/F line projection utility
│   ├── import_sonoma_real_gps.py     # OSM Overpass import
│   └── generate_sample_vbo.py        # Synthetic VBO generation
├── data/
│   ├── dbc/pitwall.dbc               # synthetic DBC (29 signals)
│   ├── registry/obd2_pids.json       # signal registry seed (54 entries)
│   ├── tracks/sonoma.json + sonoma_real_gps.json
│   ├── reference/                    # gold-standard lap traces
│   └── markers/sonoma/               # marker thumbnails
├── deploy/
│   └── termux/                       # foreground-service install package
│       ├── INSTALL.md
│       ├── service/pitwall-bridge/{run, log/run}
│       └── boot/start-pitwall
├── docs/
│   ├── api.md                        # 56-endpoint reference
│   ├── adk-agent-architecture.md     # ADK 18-agent topology, tools, KV cache, tracing
│   ├── adk-implementation-plan.md    # as-built status + remaining backlog
│   ├── internal_architecture.md      # post-2026-04-28 backend topology
│   ├── vue/                          # CANONICAL pitwall-web design — 54 files
│   │   ├── README.md                 #   index of the journey
│   │   ├── screens/                  #   38 screen docs
│   │   └── …
│   ├── adr/                          # 21 ADRs (019–021 cover ADK)
│   └── …                             # pedagogy, telemetry-pipeline, etc.
├── tests/                            # 424 tests passing, modularised in tests/features/
├── android/  +  android-app/         # FROZEN v1 native; deletes post-PWA
├── .claude/commands/adk.md           # /adk slash command — ADK reference + audit tool
├── mkdocs.yml
├── CHANGELOG.md
└── README.md

Quick start

Install

pip install flask duckdb requests python-can cantools pyserial

On-device LLM coach — Gemma 4 E2B (warm path, in-drive):

pip install litert-lm

# Download the model (~2.4 GB, public HuggingFace repo, no token needed):
litert-lm import \
    --from-huggingface-repo litert-community/gemma-4-E2B-it-litert-lm \
    gemma-4-E2B-it.litertlm gemma-4-e2b
# Lands at ~/.litert-lm/models/gemma-4-e2b/model.litertlm

ADK multi-agent paddock backend — Gemma 4 E4B (pre-brief, debrief, Q&A):

pip install google-adk

# Download E4B (~4 GB) and start the server:
lit pull gemma-4-e4b
lit serve --port 8001   # run in a separate terminal before starting the bridge

Both backends fall back silently when unavailable — the hot-path canonical phrase coach always works.

Note: earlier docs referenced mediapipe + .task files. We use litert-lm (cross-platform macOS / Linux / Termux) with .litertlm format. Per ADR-017.

Run the bridge

# HTTP-only (no live CAN, no E4B server needed for basic operation)
python3 -m src.pitwall --track src/pitwall/features/track/sonoma.json
# →  ✓  sonic_model loaded
#    ✓  Track: Sonoma Raceway (12 corners)
#    ✓  ADK coach_orchestrator loaded — 18 agents (LiteRT-LM E4B)   ← if lit serve running
#    🏁  Pitwall Bridge v2 on http://127.0.0.1:8765

curl -s http://127.0.0.1:8765/health | python3 -m json.tool

Live CAN ingest

# Dev/test (virtual bus, no hardware needed)
python3 -m src.pitwall --can-channel pitwall_dev

# Replay a VBO file as CAN frames
python3 src/simulator/can_simulator.py \
    --vbo "/path/Sonoma Intermediate - 1_47.5.vbo" \
    --channel pitwall_dev --speed 2.0

# Production — USB-CAN on Pixel via Termux
python3 -m src.pitwall \
    --can-interface slcan --can-channel /dev/ttyACM0 \
    --can-dbc data/dbc/pitwall.dbc

Run the test suite

python3 -m pytest tests/ -q
# → 424 passed, 0 skipped

python3 tests/test_endpoints_smoke.py --keep-db
# Ingests 8273-frame Sonoma VBO → exercises 56 endpoints → 51 assertions

ADK paddock Q&A

# Start a session, run a debrief, ask a question:
curl -X POST http://127.0.0.1:8765/session/start \
  -H 'Content-Type: application/json' \
  -d '{"driver": "taha", "track": "sonoma"}'

curl -X POST http://127.0.0.1:8765/coach/debrief \
  -H 'Content-Type: application/json' \
  -d '{"session_id": "<sid>", "driver_id": "taha"}'

curl -X POST http://127.0.0.1:8765/coach/ask \
  -H 'Content-Type: application/json' \
  -d '{"driver_id": "taha", "session_id": "<sid>", "question": "Why was lap 4 faster than lap 2?"}'

# Discover available agents:
curl http://127.0.0.1:8765/coach/agents | python3 -m json.tool

Architecture

┌──────────────────────────── Pixel 10 (in cabin) ─────────────────────────┐
│                                                                          │
│  USB-CAN adapter (CANable Pro / Macchina M2)                             │
│        │  slcan @ 500 kbps                                               │
│        ▼                                                                 │
│  ┌─────────────────────────────────────────────────────────────────────┐ │
│  │  Termux foreground service (deploy/termux/)                         │ │
│  │                                                                     │ │
│  │  ┌──────────────┐                                                   │ │
│  │  │ can_reader   │  python-can + cantools DBC decode                 │ │
│  │  └──────┬───────┘                                                   │ │
│  │         ▼                                                           │ │
│  │  ┌─────────────────────────────────────────────────────────────┐   │ │
│  │  │ DuckDB (pitwall_sessions.duckdb)                             │   │ │
│  │  │  telemetry · laps · coaching_notes · driver_events          │   │ │
│  │  │  llm_friction · conversations · agent_traces                │   │ │
│  │  └──────────────────────────────┬──────────────────────────────┘   │ │
│  │                                 ▼                                   │ │
│  │  ┌──────────────────────────────────────────────────────────────┐  │ │
│  │  │ HOT PATH  <50ms                                              │  │ │
│  │  │   sonic_model + RuleCoach + canonical phrase library         │  │ │
│  │  ├──────────────────────────────────────────────────────────────┤  │ │
│  │  │ WARM PATH  <100ms                                            │  │ │
│  │  │   LitertCoach (Gemma 4 E2B, litert_lm.Engine in-process)    │  │ │
│  │  ├──────────────────────────────────────────────────────────────┤  │ │
│  │  │ PADDOCK  2–15s                                               │  │ │
│  │  │   PitwallOrchestrator → 18 ADK agents → Gemma 4 E4B         │  │ │
│  │  │   (lit serve --port 8001, Tensor G5 NPU)                    │  │ │
│  │  │   brief · debrief · Q&A · voice scripts · agent telemetry   │  │ │
│  │  └──────────────────────────────┬───────────────────────────────┘  │ │
│  │                                 ▼                                   │ │
│  │  ┌──────────────────────────────────────────────────────────────┐  │ │
│  │  │ Flask HTTP server  127.0.0.1:8765  (56 endpoints)            │  │ │
│  │  │   GET  /cues/stream          → live coaching cues (SSE)      │  │ │
│  │  │   GET  /notifications        → async inbox (SSE)             │  │ │
│  │  │   POST /coach/brief          → pre-session brief             │  │ │
│  │  │   POST /coach/debrief        → post-session debrief          │  │ │
│  │  │   POST /coach/ask            → multi-turn Q&A                │  │ │
│  │  │   GET  /coach/agents         → agent registry (PWA)          │  │ │
│  │  │   GET  /session/<sid>/export.parquet                         │  │ │
│  │  └──────────────────────────────────────────────────────────────┘  │ │
│  └────────────────────────────┬────────────────────────────────────────┘ │
│                               │                                          │
│                               ▼                                          │
│  ┌────────────────────────────────────────────────────────────────────┐  │
│  │ pitwall-web (Vue 3 PWA)             — IN DESIGN —                  │  │
│  │ 38 screens specced in docs/vue/                                    │  │
│  └────────────────────────────────────────────────────────────────────┘  │
└──────────────────────────────────────────────────────────────────────────┘

ADK multi-agent coaching

The paddock tier uses Google ADK with 18 specialist agents routed by a deterministic keyword classifier — no LLM routing.

PitwallOrchestrator(BaseAgent)         ← keyword classifier, no LLM routing
├── DebriefPipeline (SequentialAgent)
│     ├── DebriefDataPhase (ParallelAgent)  ← 3 agents run concurrently
│     │     ├── HighlightFinderAgent        output_key=highlights_data
│     │     ├── TelemetryAgent              output_key=telemetry_data
│     │     └── PedagogyAgent               output_key=pedagogy_data
│     └── NarrativeAgentDebrief            reads {highlights_data}
│                                               {telemetry_data}
│                                               {pedagogy_data}
├── BriefPipeline (SequentialAgent)
│     ├── PedagogyAgent                    output_key=pedagogy_data
│     └── NarrativeAgentBrief
└── 15 QA specialist agents  →  GoldLapAgent · WeatherAdaptationAgent
                                SessionPlannerAgent · IncidentReviewAgent
                                RacePaceAgent · GoalSettingAgent
                                MentalMapAgent · VoiceScriptAgent
                                LapComparisonAgent · CornerCoachAgent
                                ProgressTrackerAgent · SetupAdvisorAgent
                                MindsetCoachAgent · AgentMetaAgent
                                TelemetryAgent (default)

Key properties:

All 15 tools query DuckDB read_only=True with LIMIT 500 enforced
PitwallTracingPlugin logs every agent run + tool call to agent_traces DuckDB table
Persistent ADK sessions per driver — lit serve clones KV cache across calls (~30–50% prefill reduction on warm requests)
POST /session/start triggers reset_driver_session() for a clean session baseline

See [docs/adk-agent-architecture.md](docs/adk-agent-architecture.md) for the full topology, tool specs, KV cache design, and agent telemetry schema.

Performance budget

Path	Budget	Notes
Hot path — sonic_model cue	< 50 ms	ADR-002
In-drive canonical phrase (RuleCoach)	< 100 ms	ADR-017
Pre-brief LLM (Gemma 4 E2B, cold)	6–8 s	measured on Apple Silicon CPU
Post-session debrief LLM (E2B)	8–12 s	measured
ADK paddock — cold call (new session)	2–15 s	E4B via `lit serve`, Tensor G5 NPU
ADK paddock — warm call (persistent session)	~30–50% less	KV cache clone; session instructions pre-filled
CAN frame → DuckDB row	< 5 ms	`src/pitwall/features/telemetry/can_reader.py`
Agent trace DuckDB write	< 1 ms	batch drain after `run_adk()`
End-to-end smoke (8273 frames + every endpoint)	~12 s	`tests/test_endpoints_smoke.py`
Parquet export (90-min session)	< 500 ms	`GET /session/<sid>/export.parquet`

Hardware

For the May 23 Sonoma field test:

Item	Role	Notes
Pixel 10	Compute + display + audio gateway	Tensor G5 NPU for E4B + E2B; Termux + bridge + PWA in Chrome
USB-CAN adapter	Reads OBD-II powertrain bus	CANable Pro (~~$60) or Macchina M2 (~~$90)
Powered USB-C OTG hub	Charge passthrough during 4-hour session	needs USB-PD passthrough
OBD-II cable	Connects USB-CAN adapter to car port	standard OBD-II to DB9
Pixel Earbuds	Audio coaching output (TTS)	ANC + tight fit handle cabin noise

Test target: 2003 BMW M3 (E46) at Sonoma Raceway.

Data privacy & residency

All coaching is on-device. Every LLM call goes through litert-lm or lit serve locally — pre-brief, debrief, Q&A, /score. There is no cloud LLM dependency.

All telemetry, lap data, coaching notes, driver profiles, and agent traces live in a local DuckDB on the device running the bridge. The bridge's HTTP server binds to 127.0.0.1 only and is not externally reachable without an explicit tunnel or POST /spectator/token.

The PWA's analytics flow uses GET /session/<sid>/export.parquet to hydrate a client-side DuckDB-Wasm instance — Parquet lives in browser OPFS only, never sent off-device.

Key documentation

Backend / bridge

[docs/api.md](docs/api.md) — every endpoint with request/response shapes
[docs/adk-agent-architecture.md](docs/adk-agent-architecture.md) — ADK topology: 18 agents, 15 tools, PitwallOrchestrator, Runner, KV cache, agent_traces schema
[docs/adk-implementation-plan.md](docs/adk-implementation-plan.md) — as-built status + remaining backlog (SSE streaming, state scopes, LoopAgent)
[docs/internal_architecture.md](docs/internal_architecture.md) — backend topology with mermaid diagrams
[docs/adr/index.md](docs/adr/index.md) — all 21 architecture decisions

Recent ADRs

ADR-019 — ADK multi-agent plan (conversations table, agent roster, Q&A endpoints)
ADR-020 — 7 structural fixes: PitwallOrchestrator, SequentialAgent/ParallelAgent, output_key, SQL safety, save_voice_scripts
ADR-021 — second audit: Runner API, race condition fix, persistent sessions + KV cache, PitwallTracingPlugin + agent_traces
ADR-018 — field-readiness: LLM friction sink, audio ducker, Kalman dead-reckoning, pedagogy refit
ADR-017 — three-tier coach; cloud Gemini removed

Frontend (`pitwall-web`)

[docs/vue/README.md](docs/vue/README.md) — canonical PWA design: 38 screens, emotion taxonomy, navigation map
[docs/vue/10-coach-emotions.md](docs/vue/10-coach-emotions.md) — 12-emotion taxonomy, Gemma prompt contract
[docs/vue/11-navigation-map.md](docs/vue/11-navigation-map.md) — god mermaid + per-screen reference
[docs/ux.md](docs/ux.md) — UX principles: audio-first, silence-is-coaching, fail-open

On-track operators

[deploy/termux/INSTALL.md](deploy/termux/INSTALL.md) — Pixel + Termux foreground service install
[docs/android_parallel_llm_install.md](docs/android_parallel_llm_install.md) — sideload pitwall-parallel + android-llm-service on one device (embedded PWA + on-device LLM)
[docs/hardware.md](docs/hardware.md) — sensor + adapter + cable spec
[docs/sonoma_track_intelligence.md](docs/sonoma_track_intelligence.md) — corner-by-corner reference + danger zones + weather phases

Pedagogy

[docs/pedagogy.md](docs/pedagogy.md) — Ross Bentley curriculum in the coaching engine
[docs/coaching-engine.md](docs/coaching-engine.md) — rule + LiteRT-LM coach composition

Build the docs site

pip install mkdocs-material
mkdocs serve -a 127.0.0.1:8889

Test status

Suite	Count	Notes
`tests/` (pytest)	424 passed, 0 skipped	Unit + integration; vendored fixtures, no network
`tests/features/telemetry/test_can_pipeline.py`	9 of 424	Round-trip on `interface='virtual'` + ADR-018 dead-reckoner wiring
`tests/features/telemetry/test_dead_reckoning.py`	13 of 424	ADR-018 1D Kalman filter unit suite
`tests/features/coaching/test_coach_engine_litert.py`	8 of 424	Live-Gemma tests; auto-skip when model file is absent
`tests/test_endpoints_smoke.py`	51 assertions, 0 failed	End-to-end against a real 8273-frame Sonoma VBO

python3 -m pytest tests/features/test_api_core.py -q
python3 -m pytest tests/features/telemetry/test_can_pipeline.py -q
python3 -m pytest tests/features/telemetry/test_dead_reckoning.py -q
python3 -m pytest tests/features/coaching/test_coach_engine.py -q
python3 -m pytest tests/features/coaching/test_coach_engine_litert.py -q   # auto-skip without model
python3 -m pytest tests/features/session/test_api_session.py -q
python3 tests/test_endpoints_smoke.py

Roadmap

The May 23, 2026 Sonoma Raceway field test is the load-bearing milestone.

Before Sonoma (3 weeks):

Scaffold pitwall-web — Vue 3 + Vite + Tailwind PWA per [docs/vue/](docs/vue/README.md). MVP: boot path → session loop → 1 analytics screen → tutorial overlay. Bridge contract is complete.
Pre-rendered TTS phrase library — bake canonical phrases per coach into MP3 clips, packaged into pitwall-web/public/audio/coaches/<id>/
Per-car DBC packs — Subaru GR86 next; hardware enumeration table ready to extend

Post-Sonoma:

ADK SSE streaming — POST /coach/ask/stream with RunConfig(streaming_mode=SSE) so the Vue PWA shows tokens as they arrive (critical for 2–15s E4B latency)
ADK state scopes — user: prefix for driver preferences persisting across sessions; app: for shared track conditions
Vue PWA paddock Q&A screen — connects to /coach/ask + /coach/agents
Multi-track support — Laguna Seca and Thunderhill slot ready in data/tracks/
Sprite generation — nano-banana prompts ready in [docs/vue/assets/reference-sheet-source.md](docs/vue/assets/reference-sheet-source.md); ~56 frames for 4 non-T-Rod coaches
Public release + license — TBD post-field-test
Framework refactor — per ADR-018: abstract CoachContext, parameterise LSTM input layer, decouple spatial awareness engine

Frozen artefacts

android/ and android-app/ contain the v1 Flutter + native Kotlin implementation. No longer the active frontend — see ADR-016. Both will be removed once pitwall-web reaches feature parity.

Team 2 (Intermediate, BMW M3)

Role	Person
Tech Lead	Hemanth HM
Edge / Telemetry	Simon Margolis
AGY Pipeline	Taha Bouhsine
Data Reasoning	Vijay Vivekanand
UX / Frontend	Aileen Villanueva

Acknowledgements

Ross Bentley, Performance Driving Illustrated — pedagogical foundation for every coaching rule. Distilled into 9 concepts in coach_engine.match_bentley_concept.
The T-Rod Sonoma transcript — track-specific coaching anchors (the bridge, the K-wall bend, Calamity Corner) that make verbal coaching feel native to Sonoma.
Google ADK — multi-agent orchestration framework. PitwallOrchestrator, SequentialAgent, ParallelAgent, BasePlugin and Runner power the 18-agent paddock backend.
Google AI Edge / litert-lm — on-device Gemma 4 inference, cross-platform. Replaced the original MediaPipe Genai approach.
Racelogic VBO format — canonical telemetry file format consumed by simulator and post-session import.
python-can + cantools — CAN ingest stack.
DuckDB — single-process SQL persistence with first-class Parquet support. Now stores coaching, conversations, and agent traces in one file.
Team 2 architecture review (2026-04-29, "CONDITIONAL PASS") — punch list that became ADR-018: LLM friction logging, audio ducker, Kalman dead-reckoning, intermediate-driver pedagogy refit.

Contributing

Pitwall is an internal sprint repository for the May 23, 2026 Sonoma field test. External contributions are not currently accepted.

For team members:

Branch from master; merge via PR. Tests must pass before merge.
Run python3 -m pytest tests/ -q and python3 tests/test_endpoints_smoke.py before opening a PR that touches ingest, lap detection, or the sink.
New endpoints get an entry in [docs/api.md](docs/api.md) plus a test in tests/test_bridge.py.
New ADK agents get an entry in AGENT_REGISTRY in adk_agents.py and a row in the agent catalogue in [docs/adk-agent-architecture.md](docs/adk-agent-architecture.md).
Architectural changes get a new ADR in docs/adr/ (ADR-NNN-slug.md). Update docs/adr/index.md in the same PR.

Code style

Python 3.10+. Type hints encouraged on new code.
Standard PEP 8; 4-space indent; double quotes; f-strings.
Module-level docstrings on every public file; short docstrings on exported functions.
Imports: stdlib → third-party → local, separated by blank lines; no star-imports.
Side effects in if __name__ == "__main__": only.
Tests: real-shape fixtures over mocks; round-trip tests on virtual buses preferred.
New ADK tools: @_adk_tool decorator, SQL safety (LIMIT 500, non-SELECT rejected), file locks for any writes (fcntl.flock).

Changelog

Notable changes by date in CHANGELOG.md. Architecture decisions in [docs/adr/](docs/adr/index.md).

License

TBD — to be added before public release.

Name		Name	Last commit message	Last commit date
.github/workflows		.github/workflows
android-app		android-app
android-llm-service		android-llm-service
android		android
data		data
deploy/termux		deploy/termux
docs		docs
ml		ml
scratch		scratch
scripts		scripts
src		src
tests		tests
.env.example		.env.example
.firebaserc		.firebaserc
.gitignore		.gitignore
.python-version		.python-version
CHANGELOG.md		CHANGELOG.md
README.md		README.md
firebase.json		firebase.json
mkdocs.yml		mkdocs.yml
package-lock.json		package-lock.json
package.json		package.json
pyproject.toml		pyproject.toml
sonoma.svg		sonoma.svg
uv.lock		uv.lock

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Pitwall — Trustable AI Racing Coach

What this is / what this isn't

Status

Repo layout

Quick start

Install

Run the bridge

Live CAN ingest

Run the test suite

ADK paddock Q&A

Architecture

ADK multi-agent coaching

Performance budget

Hardware

Data privacy & residency

Key documentation

Backend / bridge

Recent ADRs

Frontend (`pitwall-web`)

On-track operators

Pedagogy

Build the docs site

Test status

Roadmap

Frozen artefacts

Team 2 (Intermediate, BMW M3)

Acknowledgements

Contributing

Code style

Changelog

License

About

Releases

Packages

Contributors

Languages

Latest commit

History

Folders and files

Repository files navigation

Pitwall — Trustable AI Racing Coach

What this is / what this isn't

Status

Repo layout

Quick start

Install

Run the bridge

Live CAN ingest

Run the test suite

ADK paddock Q&A

Architecture

ADK multi-agent coaching

Performance budget

Hardware

Data privacy & residency

Key documentation

Backend / bridge

Recent ADRs

Frontend (pitwall-web)

On-track operators

Pedagogy

Build the docs site

Test status

Roadmap

Frozen artefacts

Team 2 (Intermediate, BMW M3)

Acknowledgements

Contributing

Code style

Changelog

License

About

Resources

Stars

Watchers

Forks

Releases

Packages

Contributors

Languages

Frontend (`pitwall-web`)