"""One-time migration: convert existing timestamped UserNotes into profile summaries.

Run with: python scripts/migrate_notes_to_profiles.py

Requires .env with DB_CONNECTION_STRING and LLM env vars.
"""
import asyncio
import os
import sys

sys.path.insert(0, os.path.dirname(os.path.dirname(__file__)))

from dotenv import load_dotenv
load_dotenv()

from utils.database import Database
from utils.llm_client import LLMClient


async def main():
    db = Database()
    if not await db.init():
        print("Database not available.")
        return

    llm = LLMClient(
        base_url=os.getenv("LLM_BASE_URL", ""),
        model=os.getenv("LLM_MODEL", "gpt-4o-mini"),
        api_key=os.getenv("LLM_API_KEY", "not-needed"),
    )

    states = await db.load_all_user_states()
    migrated = 0

    for state in states:
        notes = state.get("user_notes", "")
        if not notes or not notes.strip():
            continue

        # Check if already looks like a profile (no timestamps)
        if not any(line.strip().startswith("[") for line in notes.split("\n")):
            print(f"  User {state['user_id']}: already looks like a profile, skipping.")
            continue

        print(f"  User {state['user_id']}: migrating notes...")
        print(f"    Old: {notes[:200]}")

        # Ask LLM to summarize notes into a profile
        result = await llm.extract_memories(
            conversation=[{"role": "user", "content": f"Here are observation notes about a user:\n{notes}"}],
            username="unknown",
            current_profile="",
        )

        if result and result.get("profile_update"):
            profile = result["profile_update"]
            print(f"    New: {profile[:200]}")
            await db.save_user_state(
                user_id=state["user_id"],
                offense_count=state["offense_count"],
                immune=state["immune"],
                off_topic_count=state["off_topic_count"],
                baseline_coherence=state.get("baseline_coherence", 0.85),
                user_notes=profile,
                warned=state.get("warned", False),
                last_offense_at=state.get("last_offense_at"),
            )
            migrated += 1
        else:
            print(f"    No profile generated, keeping existing notes.")

    await llm.close()
    await db.close()
    print(f"\nMigrated {migrated}/{len(states)} user profiles.")


if __name__ == "__main__":
    asyncio.run(main())