feat(voice): complete Spike 2 voice pipeline with quality-tested prompt engine
Spike 2 delivers the full voice pipeline: queue → worker pool → sr-voice
child process (stdio JSONL) → cache → disk. Three rounds of quality testing
with Paula, Mellanie, and Gestalt produced iterative prompt improvements.
Prompt engine (prompt_builder.rs):
- Example-based epistemic marker integration (not keyword lists)
- Length-aware Angry tell variant (preserves facts on long content)
- Double-prompt technique: REMEMBER block repeats constraints near OUTPUT:
- Imperative injection framing (composition engine controls frequency)
- Anti-invention constraint ("do not add information not in the input")
- Universal RULES cleaned: worldbuilding moved to culture personas
Worker pool (worker.rs):
- Output post-processor strips after first newline (prevents prompt leakage)
- Watchdog poll loop (1s ticks) replaces blocking sleep for cancel
- Child health check before writing (try_wait)
Test infrastructure:
- voice_pipeline.rs: end-to-end test, auto-detects real sr-voice or mock
- voice_quality_batch.rs: 39 edge-case prompts for quality review
- mock-stdio.sh: Python JSONL mock for CI (no model needed)
- Makefile targets: test-voice-mock, test-voice-real
Quality results (Gemma 2B Q4_K_M, CPU ~13 t/s):
- Epistemic markers: naturally integrated (round 1 comma-lists fixed)
- Tell differentiation: 3/5 working (Nervous, Guarded, Angry)
- Information preservation: ~90% (up from ~70%)
- Prompt leakage: eliminated
- Open: Friendly/RoutineDeviation tells inert (#651), Factual bypass (#650)
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
jpmschweitzerandClaude Opus 4.6
9f34d030d7