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Author SHA1 Message Date
Praxis CI 012992c44d feat(P01-03-04): CustomerServiceGuardrail — pluggable ruleset (D-019) 
server/guardrails/customer_service.py implements the Guardrail interface with
the v0.1 Customer Service ruleset (RESEARCH.md safety baseline): blocks
legal/financial/medical advice, real-company impersonation, and a debrief
output filter that blocks recommendations the learner advise legal action
('tell the customer to sue them' → blocked_legal with a coaching redirect).
Session-start disclaimer text defined ('This is an AI practice session…').
Selected via PRAXIS_GUARDRAIL=customer_service (default); swaps in for
NoOpGuardrail with no pipeline change (D-019). server/__main__.py loads the
guardrail and logs the disclaimer as the first AI utterance. 9 unit tests
pass (disclaimer, blocks legal/financial/medical, allows normal coaching,
debrief filter blocks 'sue them', debrief allows coaching, swappable with
NoOp).

---ci---
phase: 1
milestone: v0.1
plan: 03
task: 03-04
status: execute
persona: backend-engineer
requirements:
  covered: [REQ-ORCH-02, REQ-NFR-SAFE-01]
---/ci---
 2026-08-01 13:12:31 +00:00
Praxis CI 30051fdfd6 feat(P01-03-03,P01-03-07): Pipecat Flows wiring + scenario-driven prompt 
server/scenarios/runtime.py — ScenarioRuntime maps a Scenario to a Pipecat
Flows state-machine spec: initial 'conversation' state with the scenario's
system prompt + opening line, branch metadata carried in the spec (v0.1
has no in-flight transitions per G-002 — branching is post-hoc; Phase 2+
can fork without schema change). set_branch() resolves the branch outcome
from the classifier; debrief_focus() returns the per-branch focus.

TASK-03-07: server/pipeline.py build_pipeline() now accepts a scenario_id,
loads the runtime, and uses scenario.setup.system_prompt instead of the
SLICE-02 hardcoded walking-skeleton prompt. Falls back gracefully if the
scenario can't load. server/__main__.py passes
PRAXIS_SCENARIO=customer_service_refund_ca_v01 by default. 7 runtime tests
pass (system prompt, set_branch accept/escalate, unknown-branch error,
debrief_focus per branch, flows spec branches, debrief model config).

---ci---
phase: 1
milestone: v0.1
plan: 03
task: 03-03,03-07
status: execute
persona: backend-engineer
requirements:
  covered: [REQ-SCEN-01, REQ-SCEN-FMT-01, REQ-ORCH-02]
---/ci---
 2026-08-01 13:11:30 +00:00
Praxis CI bba99418df feat(P01-02-04): Pipecat server pipeline — Silero VAD→Deepgram→Ollama→TTS→WebRTC 
server/pipeline.py assembles the Pipecat pipeline (D-017): WebRTC audio in →
Deepgram Nova-3 STT → LLMContextAggregator(user) → OLLamaLLMService
(gemma4:cloud via https://ollama.com/v1 + bearer, R6) → Cartesia/Piper TTS
(selected via PRAXIS_TTS) → WebRTC audio out. Interruptibility via
allow_interruptions=True (D-008 abort-and-yield). Hardcoded single-turn
system prompt (SLICE-03 replaces with scenario YAML). All keys from env;
missing keys log a warning and the pipeline still starts (code structure is
the deliverable). server/__main__.py exposes a FastAPI app with /health
(reports key-provisioning status) and POST /pipecat/webrtc (accepts an SDP
offer, starts a pipeline task, returns the answer). Verified: imports
succeed, /health returns 200, routes wired.

---ci---
phase: 1
milestone: v0.1
plan: 02
task: 02-04
status: execute
persona: backend-engineer
requirements:
  covered: [REQ-VOICE-01, REQ-VOICE-02, REQ-VOICE-04, REQ-ORCH-01]
---/ci---
 2026-08-01 13:04:17 +00:00