Praxis CI f04b9b3588 feat(P01): SLICE-01+02 — Dockerfile, .dockerignore, docker-compose.yml, FastAPI StaticFiles, PRAXIS_DB_PATH env (G-102 fix)
SLICE-01 (lead-developer): multi-stage Dockerfile (node:22-slim→python:3.12-slim),
  .dockerignore (excludes secrets/node_modules/.git), docker-compose.yml
  (port 8789, SQLite volume, env injection for all voice-service vars)
SLICE-02 (backend-engineer+data-engineer): FastAPI mounts client/dist as
  StaticFiles at / after API routes (D-023, REQ-DEPLOY-13).
  G-102 MUST fix: db/store.py + db/migrate.py now read PRAXIS_DB_PATH
  from env so the Docker volume mount persists SQLite data.
G-105 FIX: Dockerfile copies pyproject.toml before source (pip install
  layer cached, source changes don't invalidate).

REQ-DEPLOY-01, 02, 13, 16 covered.

---ci---
project: praxis
phase: 1
milestone: v0.2
status: execute
slice: 01-02
wave: 1
---/ci---
2026-08-01 14:16:39 +00:00

Praxis — v0.1 Foundation

Voice-first AI apprenticeship platform. v0.1 is a tech-validation harness (per G-008) for the minimal viable voice loop: a single learner speaks to an AI tutor playing a Customer Service role-play scenario, hears a <600ms-latency response, receives an end-of-session coaching debrief, and has the session logged to SQLite.

Status

Phase 1 (minimal viable voice loop) — code-complete, pending live API keys for runtime verification.

Stack

  • Orchestration: Pipecat (D-017) with Silero VAD + interruptibility
  • ASR: Deepgram Nova-3 streaming (D-013)
  • LLM: Ollama Cloud direct API (D-020) — gemma4:cloud (role-play) + deepseek-v4-flash:cloud no-think (debrief)
  • TTS: Cartesia Sonic (primary, D-014) / Piper (self-hosted, R4 mitigation) — behind an interface
  • Client: React + Vite + WebRTC (Pipecat client SDK, D-015)
  • State: SQLite praxis.db (D-007, single hardcoded learner, no auth)

Layout

server/      Pipecat pipeline, services (TTS/LLM/Guardrail interfaces), scenario runtime, adapters
client/      React + Vite + WebRTC learner surface
scenarios/   YAML scenario definitions (D-018)
db/          SQLite schema, migrations, async store
scripts/     Latency probes (R1-R4), e2e smoke
tests/       Unit + e2e
docs/        Latency report, debrief templates

Quickstart

  1. Copy .env.example.env, fill in DEEPGRAM_API_KEY, CARTESIA_API_KEY, OLLAMA_API_KEY.
  2. Install server deps: pip install -e ".[dev]"
  3. Install client deps: cd client && npm install
  4. Run probes: python scripts/probe_deepgram.py (etc.)
  5. Run server: python -m server
  6. Run client: cd client && npm run dev

See docs/latency-report.md for the R1-R4 spike status and TTS decision.

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