e095d9c41a
DeltaChannel reconstructs its value by replaying ancestor writes through the reducer. Every saver ordered a checkpoint's writes by (task_id, idx), but live execution applies them in task-path order: apply_writes sorts a super-step's tasks by task_path_str(task.path[:3]) before calling channel.update. task_id is a hash of the path, so the two orders are unrelated, and two or more tasks writing one DeltaChannel in a single super-step replayed in an arbitrary permutation. Reducers are only required to be batching-invariant, not order-invariant, so the permutation changes the value: get_state disagreed with what invoke returned, and continuing the thread persisted the reordered replay as the base for later writes. Replay now orders by (task_path, task_id, idx), following the precedent already set for the Send channel by SELECT_PENDING_SENDS_SQL. InMemorySaver and the postgres savers already persisted task_path and only needed the sort key; sqlite accepted task_path on put_writes and dropped it, so the writes table gains the column plus a probe-guarded ALTER for databases created by earlier versions. Writes stored without a task_path sort first within their checkpoint, which is where live execution applies the task-less input writes that carry "". The graph-level regression tests run against the full async_checkpointer matrix (memory, sqlite, postgres in three pool modes) because each saver reconstructs delta channels through its own override; 20 of the 25 cases fail on main, and the 5 that pass are the sequential control. Co-authored-by: ErenAta16 <149434812+ErenAta16@users.noreply.github.com> Co-authored-by: ragnarok268 <58264829+ragnarok268@users.noreply.github.com>
LangGraph SQLite Checkpoint
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Quick Install
uv add langgraph-checkpoint-sqlite
🤔 What is this?
This library provides a SQLite implementation of LangGraph's checkpoint saver, with both sync and async support via aiosqlite. Use it when you want LangGraph state persistence backed by SQLite for local development, testing, or lightweight deployments.
📖 Documentation
For full documentation, see the API reference. For conceptual guides on persistence and memory, see the LangGraph Docs.
Security
Important
Set
LANGGRAPH_STRICT_MSGPACK=trueor pass an explicitallowed_msgpack_moduleslist when creating your checkpointer. This restricts checkpoint deserialization to known-safe types, preventing code execution if the database is compromised. See the langgraph-checkpoint README for details.
Usage
from langgraph.checkpoint.sqlite import SqliteSaver
write_config = {"configurable": {"thread_id": "1", "checkpoint_ns": ""}}
read_config = {"configurable": {"thread_id": "1"}}
with SqliteSaver.from_conn_string(":memory:") as checkpointer:
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))
Async
from langgraph.checkpoint.sqlite.aio import AsyncSqliteSaver
async with AsyncSqliteSaver.from_conn_string(":memory:") as checkpointer:
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
await checkpointer.aput(write_config, checkpoint, {}, {})
# load checkpoint
await checkpointer.aget(read_config)
# list checkpoints
[c async for c in checkpointer.alist(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.