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Files

T

André MenezesandGitHub 3d394740ce Fix AsyncPostgresStore._cursor row type (#4623 )

`AsyncPostgresStore._cursor` is expected to yield
`AsyncCursor[DictRow]`. In the `else` branch the `row_factory` was not
defined, meaning that it would yield `AsyncCursor[TupleRow]` (default).
This resulted in an error in
[langgraph/store/postgres/aio.py#L249](https://github.com/langchain-ai/langgraph/blob/main/libs/checkpoint-postgres/langgraph/store/postgres/aio.py#L249)
(`TypeError: tuple indices must be integers or slices, not str`).

2025-05-12 13:34:56 +00:00

langgraph

Fix AsyncPostgresStore._cursor row type (#4623 )

2025-05-12 13:34:56 +00:00

tests

Fix text fields naming (#4345 )

2025-04-18 08:21:46 -07:00

Makefile

feat: Add vector search (#2535 )

2024-11-28 04:40:12 +00:00

poetry.lock

version bumps and locks

2025-04-28 17:39:20 -04:00

pyproject.toml

no upper bounds for python

2025-04-25 17:45:54 -07:00

README.md

Update

2025-03-24 07:57:02 -07:00

README.md

LangGraph Checkpoint Postgres

Implementation of LangGraph CheckpointSaver that uses Postgres.

Dependencies

By default langgraph-checkpoint-postgres installs psycopg (Psycopg 3) without any extras. However, you can choose a specific installation that best suits your needs here (for example, psycopg[binary]).

Usage

Important

When using Postgres checkpointers for the first time, make sure to call .setup() method on them to create required tables. See example below.

Important

When manually creating Postgres connections and passing them to PostgresSaver or AsyncPostgresSaver, make sure to include autocommit=True and row_factory=dict_row (from psycopg.rows import dict_row). See a full example in this how-to guide.

from langgraph.checkpoint.postgres import PostgresSaver

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

DB_URI = "postgres://postgres:postgres@localhost:5432/postgres?sslmode=disable"
with PostgresSaver.from_conn_string(DB_URI) as checkpointer:
    # call .setup() the first time you're using the checkpointer
    checkpointer.setup()
    checkpoint = {
        "v": 2,
        "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.postgres.aio import AsyncPostgresSaver

async with AsyncPostgresSaver.from_conn_string(DB_URI) as checkpointer:
    checkpoint = {
        "v": 2,
        "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)]