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Praxis CI bdcf793db2 feat(P02): complete integration + tech-debt + NFR measurement phase — v0.1.12 tagged
Phase 2 (Integration + Tech-Debt + NFR Measurement) complete.
4 slices, 2 waves, 9 tasks. 4 REQs covered. 60 new tests (469 total).
8 v0.4 P1+ tech-debt findings addressed. Verify: APPROVE_WITH_NOTES.

NFR measurement (p95 latency + guardrail FP/FN), cohort aggregation
assist metrics (5 new metrics, no schema change), assist cost tracking
+ C-3 budget check, tech-debt wave (argon2id offload, cookie-secret
validation, credential enum, f-string SQL, cache persistence, zoneinfo,
audit log, 429 mock).

---ci---
project: praxis
phase: 2
milestone: v0.5
status: complete
requirements:
  covered: [REQ-NFR-ASSIST-01, REQ-IDEATE-04, REQ-IDEATE-06, REQ-IDEATE-07]
  partial: []
---/ci---
2026-08-04 22:11:51 +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.

S
Description
Praxis v0.1 — voice-first AI apprenticeship platform: AI tutor role-play with sub-600ms latency, coaching debriefs, SQLite logging.
Readme 1.7 MiB
2026-08-04 22:36:00 +00:00
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Shell 13.8%
TypeScript 4.3%
CSS 0.3%
Dockerfile 0.2%