memory

Base class for creating a graph checkpointer.

Checkpointers allow LangGraph agents to persist their state within and across multiple interactions.

When a checkpointer is configured, you should pass a thread_id in the config when invoking the graph:

config = {"configurable": {"thread_id": "my-thread"}}
graph.invoke(inputs, config)

The thread_id is the primary key used to store and retrieve checkpoints. Without it, the checkpointer cannot save state, resume from interrupts, or enable time-travel debugging.

How you choose thread_id depends on your use case:

• Single-shot workflows: Use a unique ID (e.g., uuid4) for each run when executions are independent.
• Conversational memory: Reuse the same thread_id across invocations to accumulate state (e.g., chat history) within a conversation.

State snapshot at a given point in time.

Metadata associated with a checkpoint.

A tuple containing a checkpoint and its associated data.

Protocol for serialization and deserialization of objects.

• dumps_typed: Serialize an object to a tuple (type, bytes).
• loads_typed: Deserialize an object from a tuple (type, bytes).

Valid implementations include the pickle, json and orjson modules.

An in-memory checkpoint saver.

This checkpoint saver stores checkpoints in memory using a defaultdict.