Implements robust, database-persisted conversation tracking for stateless AI agents using PostgreSQL.
This skill provides a comprehensive framework for managing AI conversation history in stateless server environments, ensuring seamless continuity across restarts. It automates the creation of message-role architectures, enforces strict role ordering (system-user-assistant), and maintains multi-tenant security through user-scoped isolation. By bridging the gap between stateless API requests and persistent chat contexts, it enables developers to build scalable, reliable AI agents that remember past interactions without relying on ephemeral in-memory storage.
주요 기능
01Multi-tenant user isolation to ensure private and secure conversation access
02Efficient history retrieval patterns for resuming sessions after server restarts
031 GitHub stars
04Automated SQLModel data definitions for users, conversations, and messages
05Strict role sequence validation (System → User ↔ Assistant) to prevent LLM errors
06Stateless request cycle management using Neon PostgreSQL persistence
사용 사례
01Building scalable chat applications where server instances are interchangeable
02Implementing persistent memory for AI agents across multiple user sessions
03Migrating in-memory chat prototypes to production-ready database-backed systems
