Skip to main content

Library with a MongoDB implementation of LangGraph checkpoint saver.

Project description

LangGraph Checkpoint MongoDB

Implementation of LangGraph CheckpointSaver that uses MongoDB.

Usage

from langgraph.checkpoint.mongodb import MongoDBSaver

write_config = {"configurable": {"thread_id": "1", "checkpoint_ns": ""}}
read_config = {"configurable": {"thread_id": "1"}}

MONGODB_URI = "mongodb://localhost:27017"
DB_NAME = "checkpoint_example"

with MongoDBSaver.from_conn_string(MONGODB_URI, DB_NAME) as checkpointer:
    checkpoint = {
        "v": 1,
        "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
            }
        },
        "pending_sends": [],
    }

    # store checkpoint
    checkpointer.put(write_config, checkpoint, {}, {})

    # load checkpoint
    checkpointer.get(read_config)

    # list checkpoints
    list(checkpointer.list(read_config))

Async

from langgraph.checkpoint.pymongo import AsyncMongoDBSaver

async with AsyncMongoDBSaver.from_conn_string(MONGODB_URI) as checkpointer:
    checkpoint = {
        "v": 1,
        "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
            }
        },
        "pending_sends": [],
    }

    # 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)]

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

langgraph_checkpoint_mongodb-0.1.2.tar.gz (70.6 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

langgraph_checkpoint_mongodb-0.1.2-py3-none-any.whl (10.6 kB view details)

Uploaded Python 3

File details

Details for the file langgraph_checkpoint_mongodb-0.1.2.tar.gz.

File metadata

File hashes

Hashes for langgraph_checkpoint_mongodb-0.1.2.tar.gz
Algorithm Hash digest
SHA256 a954e70d8b5eaf04607d4828d23c14cc7d0ec222422b6cd7e31ae29c0e4662e8
MD5 2248284a60f6a25091ffc637fe93989b
BLAKE2b-256 db0be4868743c39c777bc2d87aae6ad84f13c81bc2721745aade4ab096570b73

See more details on using hashes here.

File details

Details for the file langgraph_checkpoint_mongodb-0.1.2-py3-none-any.whl.

File metadata

File hashes

Hashes for langgraph_checkpoint_mongodb-0.1.2-py3-none-any.whl
Algorithm Hash digest
SHA256 0b30e50aaba3cbaca06c1073eaef3f1f305335339eaeea2412dd7782caafb8a4
MD5 87eda8c09b02c720e4f7a16f998620db
BLAKE2b-256 35fc2dd9a9fbbe8435d9d3200f8bc7958575ea554c0a91d324e3a20faf59bd6f

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page