We are building a customer support bot using LangGraph and need it to remember user interactions over several days. What is the most efficient way to implement checkpointers for thread-level persistence? I want to make sure the state is saved securely without causing significant latency.
3 answers
The most common approach is using the SqliteSaver for local development or a Postgres-backed checkpointer for production environments. Persistence works by saving a snapshot of the graph state after every node execution. This allows you to resume a conversation by simply passing a thread_id in the configuration. You should ensure your state schema is JSON-serializable to avoid errors during the saving process. Also, consider implementing a cleanup strategy for old threads to manage your database size effectively as your user base grows over time.
Does using a persistent checkpointer impact the execution speed of the nodes significantly when dealing with large state objects?
You just need to initialize the graph with a memory saver to enable the "thread" functionality for your users.
True, but for production, you definitely want something more robust than the in-memory version so data isn't lost on restart.
It adds a small IO overhead since it writes to the DB after each step. If your state contains huge images or files, it's better to store those in S3 and just keep the URIs in your graph state to keep it lightweight.