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.