Praxis CI
c28f5113c5
4-layer verification of Phase 1 (Operator Foundation — Postgres + Auth +
VC migration + Bootstrap CLI). All layers pass.
---ci---
phase: 1
milestone: v0.4
status: verify
requirements:
covered: [REQ-MT-01, REQ-AUTH-01, REQ-NFR-AUTH-01, REQ-NFR-MT-01, REQ-MT-02]
partial: []
grill_musts:
honored: [G-008, G-011, G-027, G-031]
deferred_to_p2: [G-038, G-041]
tests:
passed: 272
skipped: 33
failed: 0
p0_fixes_applied: 0
p1_plus_flagged: 4
- argon2id blocking event loop (R-AUTH-02 accepted, offload if frequency grows)
- rate limit 429 not tested in mock path (tested in PG integration)
- no PRAXIS_COOKIE_SECRET length validation (add >=32 check)
- set_credential_status no enum validation (add CHECK constraint)
lessons:
- SessionMiddleware kwargs are https_only/same_site (not secure/samesite) — fix 0a95102 was correct
- IssuerKeyStore runtime_checkable Protocol cleanly duck-types both PraxisStore + PgStore
- R-VC-MIG-01 archive-before-activate ordering is explicitly tested via instrumentation
- Graceful degradation verified empirically: voice loop unaffected by Postgres absence
---/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.