LangGraph Checkpoint
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Quick Install
uv add langgraph-checkpoint
🤔 What is this?
This library defines the base interface for LangGraph checkpointers. Checkpointers provide a persistence layer for LangGraph: they save graph state at every superstep, enabling human-in-the-loop, memory between interactions, durable execution, and more.
📖 Documentation
For full documentation, see the API reference. For conceptual guides on persistence and memory, see the LangGraph Docs.
Key concepts
Checkpoint
Checkpoint is a snapshot of the graph state at a given point in time. Checkpoint tuple refers to an object containing checkpoint and the associated config, metadata and pending writes.
Thread
Threads enable the checkpointing of multiple different runs, making them essential for multi-tenant chat applications and other scenarios where maintaining separate states is necessary. A thread is a unique ID assigned to a series of checkpoints saved by a checkpointer. When using a checkpointer, you must specify a thread_id and optionally checkpoint_id when running the graph.
thread_idis simply the ID of a thread. This is always required.checkpoint_idcan optionally be passed. This identifier refers to a specific checkpoint within a thread. This can be used to kick off a run of a graph from some point halfway through a thread.
You must pass these when invoking the graph as part of the configurable part of the config, e.g.
{"configurable": {"thread_id": "1"}} # valid config
{
"configurable": {
"thread_id": "1",
"checkpoint_id": "0c62ca34-ac19-445d-bbb0-5b4984975b2a",
}
} # also valid config
Serde
langgraph-checkpoint also defines protocol for serialization/deserialization (serde) and provides a default implementation (langgraph.checkpoint.serde.jsonplus.JsonPlusSerializer) that handles a wide variety of types, including LangChain and LangGraph primitives, datetimes, enums and more.
Pending writes
When a graph node fails mid-execution at a given superstep, LangGraph stores pending checkpoint writes from any other nodes that completed successfully at that superstep, so that whenever we resume graph execution from that superstep we don't re-run the successful nodes.
Interface
Each checkpointer should conform to langgraph.checkpoint.base.BaseCheckpointSaver interface and must implement the following methods:
.put- Store a checkpoint with its configuration and metadata..put_writes- Store intermediate writes linked to a checkpoint (i.e. pending writes)..get_tuple- Fetch a checkpoint tuple using for a given configuration (thread_idandcheckpoint_id)..list- List checkpoints that match a given configuration and filter criteria..delete_thread()- Delete all checkpoints and writes associated with a thread..get_next_version()- Generate the next version ID for a channel.
If the checkpointer will be used with asynchronous graph execution (i.e. executing the graph via .ainvoke, .astream, .abatch), checkpointer must implement asynchronous versions of the above methods (.aput, .aput_writes, .aget_tuple, .alist). Similarly, the checkpointer must implement .adelete_thread() if asynchronous thread cleanup is desired. The base class provides a default implementation of .get_next_version() that generates an integer sequence starting from 1, but this method should be overridden for custom versioning schemes.
Usage
from langgraph.checkpoint.memory import InMemorySaver
write_config = {"configurable": {"thread_id": "1", "checkpoint_ns": ""}}
read_config = {"configurable": {"thread_id": "1"}}
checkpointer = InMemorySaver()
checkpoint = {
"v": 4,
"ts": "2024-07-31T20:14:19.804150+00:00",
"id": "1ef4f797-8335-6428-8001-8a1503f9b875",
"channel_values": {"my_key": "meow", "node": "node"},
"channel_versions": {"__start__": 2, "my_key": 3, "start:node": 3, "node": 3},
"versions_seen": {
"__input__": {},
"__start__": {"__start__": 1},
"node": {"start:node": 2},
},
}
# store checkpoint
checkpointer.put(write_config, checkpoint, {}, {})
# load checkpoint
checkpointer.get(read_config)
# list checkpoints
list(checkpointer.list(read_config))
📕 Releases & Versioning
See our Releases and Versioning policies.
💁 Contributing
As an open-source project in a rapidly developing field, we are extremely open to contributions, whether it be in the form of a new feature, improved infrastructure, or better documentation.
For detailed information on how to contribute, see the Contributing Guide.
1 maintainer
Metadata
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Release files for langgraph-checkpoint 4.3.0
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Source distribution (sdist)
| File | Size | Uploaded | |
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| langgraph_checkpoint-4.3.0.tar.gz | 182.7 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| langgraph_checkpoint-4.3.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 240.7 kB
Release files / langgraph_checkpoint-4.3.0.tar.gz
| Download URL | langgraph_checkpoint-4.3.0.tar.gz |
|---|---|
| Size | 182.7 kB |
| Tags | Source |
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| Download URL | langgraph_checkpoint-4.3.0-py3-none-any.whl |
|---|---|
| Size | 58.1 kB |
| Tags | Python 3 |
|
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