f04b9b35882cb5b43671650410baa8e471c6ea5c
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---
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:cloudno-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
- Copy
.env.example→.env, fill inDEEPGRAM_API_KEY,CARTESIA_API_KEY,OLLAMA_API_KEY. - Install server deps:
pip install -e ".[dev]" - Install client deps:
cd client && npm install - Run probes:
python scripts/probe_deepgram.py(etc.) - Run server:
python -m server - Run client:
cd client && npm run dev
See docs/latency-report.md for the R1-R4 spike status and TTS decision.
Description
Releases
15
Languages
Python
81.4%
Shell
13.8%
TypeScript
4.3%
CSS
0.3%
Dockerfile
0.2%