ab4bbf2fb2
Opt-in persistent cross-session user modeling via Honcho. Reads ~/.honcho/config.json as single source of truth (shared with Claude Code, Cursor, and other Honcho-enabled tools). Zero impact when disabled or unconfigured. - honcho_integration/ package (client, session manager, peer resolution) - Host-based config resolution matching claude-honcho/cursor-honcho pattern - Prefetch user context into system prompt per conversation turn - Sync user/assistant messages to Honcho after each exchange - query_user_context tool for mid-conversation dialectic reasoning - Gated activation: requires ~/.honcho/config.json with enabled=true
103 lines
3.2 KiB
Python
103 lines
3.2 KiB
Python
"""Honcho tool for querying user context via dialectic reasoning.
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Registers ``query_user_context`` -- an LLM-callable tool that asks Honcho
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about the current user's history, preferences, goals, and communication
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style. The session key is injected at runtime by the agent loop via
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``set_session_context()``.
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"""
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import json
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import logging
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logger = logging.getLogger(__name__)
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# ── Module-level state (injected by AIAgent at init time) ──
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_session_manager = None # HonchoSessionManager instance
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_session_key: str | None = None # Current session key (e.g., "telegram:123456")
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def set_session_context(session_manager, session_key: str) -> None:
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"""Register the active Honcho session manager and key.
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Called by AIAgent.__init__ when Honcho is enabled.
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"""
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global _session_manager, _session_key
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_session_manager = session_manager
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_session_key = session_key
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def clear_session_context() -> None:
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"""Clear session context (for testing or shutdown)."""
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global _session_manager, _session_key
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_session_manager = None
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_session_key = None
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# ── Tool schema ──
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HONCHO_TOOL_SCHEMA = {
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"name": "query_user_context",
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"description": (
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"Query Honcho to retrieve relevant context about the user based on their "
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"history and preferences. Use this when you need to understand the user's "
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"background, preferences, past interactions, or goals. This helps you "
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"personalize your responses and provide more relevant assistance."
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),
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"parameters": {
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"type": "object",
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"properties": {
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"query": {
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"type": "string",
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"description": (
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"A natural language question about the user. Examples: "
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"'What are this user's main goals?', "
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"'What communication style does this user prefer?', "
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"'What topics has this user discussed recently?', "
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"'What is this user's technical expertise level?'"
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),
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}
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},
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"required": ["query"],
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},
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}
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# ── Tool handler ──
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def _handle_query_user_context(args: dict, **kw) -> str:
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"""Execute the Honcho context query."""
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query = args.get("query", "")
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if not query:
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return json.dumps({"error": "Missing required parameter: query"})
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if not _session_manager or not _session_key:
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return json.dumps({"error": "Honcho is not active for this session."})
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try:
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result = _session_manager.get_user_context(_session_key, query)
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return json.dumps({"result": result})
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except Exception as e:
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logger.error("Error querying Honcho user context: %s", e)
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return json.dumps({"error": f"Failed to query user context: {e}"})
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# ── Availability check ──
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def _check_honcho_available() -> bool:
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"""Tool is only available when Honcho is active."""
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return _session_manager is not None and _session_key is not None
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# ── Registration ──
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from tools.registry import registry
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registry.register(
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name="query_user_context",
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toolset="honcho",
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schema=HONCHO_TOOL_SCHEMA,
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handler=_handle_query_user_context,
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check_fn=_check_honcho_available,
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)
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