config.py:
- Default OLLAMA_INTENT_MODEL: qwen2.5:1.5b → qwen2.5:7b
- Startup will auto-pull and warm the new model on next container restart
intent.py:
- Replaced phrase-matching examples in search_web and research_topic rules
with semantic descriptions. The 7B model doesn't need example phrases to
understand intent — it can reason from the tool's purpose. Removes implied
usage patterns that caused misclassifications on conversational phrasing
(e.g. "I've been thinking about buying shirts, can you research this?").
- research_topic rule now explicitly covers any subject regardless of phrasing,
including shopping decisions, comparisons, how-things-work questions, etc.
- search_web rule clarified as "short summary, no note" vs research_topic's
"comprehensive written reference"
The 1.5B model required prescriptive phrase examples to route correctly; the
7B model has sufficient language understanding to classify from semantic intent.
Expected improvement: ~1-2s intent calls (vs 0.4-9s for the 1.5B model which
sometimes timed out or misclassified longer/conversational messages).
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
bvandeusenandClaude Sonnet 4.6
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