AJ Isaacs
b918ba51a8
- Use LLM_ESCALATION_* env vars for better profile generation - Fall back to joining permanent memories if profile_update is null Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
90 lines
2.9 KiB
Python
90 lines
2.9 KiB
Python
"""One-time migration: convert existing timestamped UserNotes into profile summaries.
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Run with: python scripts/migrate_notes_to_profiles.py
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Requires .env with DB_CONNECTION_STRING and LLM env vars.
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"""
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import asyncio
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import os
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import sys
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sys.path.insert(0, os.path.dirname(os.path.dirname(__file__)))
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from dotenv import load_dotenv
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load_dotenv()
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from utils.database import Database
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from utils.llm_client import LLMClient
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async def main():
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db = Database()
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if not await db.init():
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print("Database not available.")
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return
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# Use escalation model for better profile generation
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llm = LLMClient(
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base_url=os.getenv("LLM_ESCALATION_BASE_URL", os.getenv("LLM_BASE_URL", "")),
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model=os.getenv("LLM_ESCALATION_MODEL", os.getenv("LLM_MODEL", "gpt-4o-mini")),
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api_key=os.getenv("LLM_ESCALATION_API_KEY", os.getenv("LLM_API_KEY", "not-needed")),
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)
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states = await db.load_all_user_states()
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migrated = 0
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for state in states:
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notes = state.get("user_notes", "")
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if not notes or not notes.strip():
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continue
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# Check if already looks like a profile (no timestamps)
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if not any(line.strip().startswith("[") for line in notes.split("\n")):
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print(f" User {state['user_id']}: already looks like a profile, skipping.")
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continue
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print(f" User {state['user_id']}: migrating notes...")
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print(f" Old: {notes[:200]}")
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# Ask LLM to summarize notes into a profile
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result = await llm.extract_memories(
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conversation=[{"role": "user", "content": f"Here are observation notes about a user:\n{notes}"}],
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username="unknown",
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current_profile="",
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)
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if not result:
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print(f" LLM returned no result, keeping existing notes.")
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continue
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# Use profile_update if provided, otherwise build from permanent memories
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profile = result.get("profile_update")
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if not profile:
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permanent = [m["memory"] for m in result.get("memories", []) if m.get("expiration") == "permanent"]
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if permanent:
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profile = " ".join(permanent)
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if profile:
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print(f" New: {profile[:200]}")
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await db.save_user_state(
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user_id=state["user_id"],
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offense_count=state["offense_count"],
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immune=state["immune"],
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off_topic_count=state["off_topic_count"],
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baseline_coherence=state.get("baseline_coherence", 0.85),
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user_notes=profile,
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warned=state.get("warned", False),
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last_offense_at=state.get("last_offense_at"),
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)
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migrated += 1
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else:
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print(f" No profile generated, keeping existing notes.")
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await llm.close()
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await db.close()
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print(f"\nMigrated {migrated}/{len(states)} user profiles.")
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if __name__ == "__main__":
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asyncio.run(main())
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