manage-conversation-db

Stateless conversation persistence is handled by an async service using SQLModel and SQLAlchemy to create and load conversations by ID. This ensures context continuity across requests without relying on in-memory state.

You can save user and assistant messages with roles and metadata asynchronously by using an async database service. This non-blocking approach allows scalable performance while storing conversation history chronologically for agent input.

Yes, the conversation persistence service exposes async database queries using SQLAlchemy and SQLModel. This non-blocking operation ensures scalable performance when creating, loading, or retrieving conversation history.

You can fetch conversation history in chronological order by using the conversation service's history retrieval function. This retrieves stored messages sequentially, providing the exact context needed for agent input across stateless requests.

Yes, conversations are tied to a specific user_id to ensure privacy and isolation. This allows the stateless persistence service to securely load existing conversations by ID without cross-user data leakage.