Upgrade intent model to qwen2.5:7b, simplify intent prompt rules
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>
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@@ -100,14 +100,16 @@ Rules:
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- "read", "open", "show me", "what does X say", "display", "pull up" a specific note → use get_note with query=<note name>.
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- "list my notes", "show notes", "recent notes", "browse notes", "notes tagged X" → use list_notes (with optional q or tags).
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- "tag X with Y", "add tag Y to X", "untag Y from X", "remove tag Y from X" → use update_note with tags=[Y] and tag_mode="add" or "remove".
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- search_web: user wants a quick web search to answer a factual question
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("search for X", "look up X", "what is the latest version of X", "find X online",
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"google X", "what is X" for quick factual answers — NOT when they want a comprehensive note)
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- research_topic: user wants to research a topic and create a comprehensive note from web sources
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("research X", "Research: X", "research X and make a note", "compile notes on X", "write a report on X",
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"deep dive into X", "find everything about X", "comprehensive guide to X",
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"research where to buy X", "research how to X", "research X and ship to me" — the topic
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is everything after "Research:" or "research")
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- search_web: user wants a quick factual answer retrieved from the web, without creating a note.
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Use for brief lookups where a short summary suffices (current version numbers, quick facts,
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"what is X", "look up X"). Do NOT use when the user wants a detailed written reference.
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- research_topic: user wants a comprehensive, multi-section research note created from web sources.
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Use whenever the user wants to deeply understand, learn about, or get a full written reference
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on any subject — regardless of how they phrase it. The topic can be anything: technical subjects,
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shopping decisions, comparisons, how things work, historical topics, etc.
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The "topic" argument should capture the full subject matter of the request.
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Prefer this over search_web when the user's request implies wanting thorough coverage rather than
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a quick answer.
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- "ack": one short, natural sentence confirming the action (tool path only). Vary phrasing — do not always start with "Let me". Omit (null) for chat-only responses.
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- Do NOT wrap the JSON in markdown code fences."""
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