LangGraph Persistence & Memory

To save and recall LangGraph states, use state checkpointing with backends like MemorySaver or PostgresSaver. This persists the graph's state at each super-step, enabling durable execution and allowing recovery and replay across invocations.

Conversation history isolation in LangGraph works through thread management. By assigning a unique thread_id to each invocation, the checkpointer isolates individual conversation histories and states, ensuring each chat session maintains its own distinct context and memory.

Yes, you can store user preferences across different LangGraph conversations by utilizing a long-term memory Store. This mechanism maintains cross-thread information, allowing your application to recall user data even when switching between isolated thread_ids.

Yes, LangGraph persistence works with PostgresSaver as a checkpointer backend. This allows your application to save graph states and conversation histories into a PostgreSQL database, providing durable state management and recovery capabilities for production deployments.

Thread-based state in LangGraph isolates conversation history within a specific thread_id using a checkpointer, while long-term memory uses a Store to maintain cross-thread information like user preferences. Thread state is session-specific, whereas long-term memory persists across all threads.