Ryan Chen
c95800e65d
Give the LangChain agent a save_user_memory tool so users can ask it to remember preferences and personal facts. Memories are stored per-user in a new user_memories table and injected into the system prompt on each conversation turn. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
20 lines
812 B
Python
20 lines
812 B
Python
from .models import UserMemory
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async def get_memories_for_user(user_id: str) -> list[str]:
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"""Return all memory content strings for a user, ordered by most recently updated."""
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memories = await UserMemory.filter(user_id=user_id).order_by("-updated_at")
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return [m.content for m in memories]
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async def save_memory(user_id: str, content: str) -> str:
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"""Save a new memory or touch an existing one (exact-match dedup)."""
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existing = await UserMemory.filter(user_id=user_id, content=content).first()
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if existing:
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existing.updated_at = None # auto_now=True will refresh it on save
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await existing.save(update_fields=["updated_at"])
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return "Memory already exists (refreshed)."
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await UserMemory.create(user_id=user_id, content=content)
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return "Memory saved."
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