8a7cca456f891ca1a813c5254c53d48d2e90d368
Small local models (qwen2.5-vl-3b, gemma-4-e4b) narrate actions ('Sure,
I'll pause the music') without emitting the tool call once the full
system prompt and 26-tool set are in context. Measured: qwen emitted
tools in 2/8 realistic intents, gemma 5/8; single-tool tests pass 100%,
so this is context-induced drift, not plumbing.
- agent/intent_router.py: deterministic forced-call router for
high-frequency intents — media controls, now_playing/list_library,
'remember that ...' memory saves, explicit YouTube Music searches,
and personal-fact recall (memory_recall/search_notes/skill_recall,
excluded for weather/time questions). Fires only when the tool is
available; guards against how-do-I questions.
- agent.py: generalize _ForcedToolCallStream to any tool; route through
intent_router after the dispatch check. System prompt adds a hard
'call, don't narrate' rule and reconditions 'answer directly'.
- tests/test_intent_router.py: 30 unit tests pinning router behavior.
Verified against the live LLM with the full fidelity harness: combined
forced-or-emitted coverage 8/8 on qwen2.5-vl-3b (was 2/8) and 8/8 on
gemma-4-e4b (was 5/8). Full suite: 79 passed.
Description
Real-time voice assistant: LiveKit + Azure Speech + local Gemma LLM
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