## Summary - Ports the langgraph API checkpointer fix to the OSS Postgres checkpoint. - The `'b'` (seed-blob) branch of `_build_delta_stage2_sql`'s `UNION ALL` was missing column aliases (`AS _kind`, `AS checkpoint_id`, `AS task_id`, `AS idx`). - In PostgreSQL, `UNION ALL` column names are taken from the **first** `SELECT`. When `channels_with_chain` is empty but `channels_with_seed` is not (e.g. very first run of a DeltaChannel graph, or `snapshot_frequency=1`), the `'b'` branch becomes the first `SELECT`, so columns got default names (`text`, `null`) instead of the expected aliases — causing `KeyError: '_kind'` in `_build_delta_channels_writes_history`. ## Test plan - [ ] Existing `checkpoint-postgres` delta channel tests pass (`make test` in `libs/checkpoint-postgres`) - [ ] Manually verified fix matches the correction suggested in the upstream API PR review comment 🤖 Generated with [Claude Code](https://claude.com/claude-code)
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]).
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
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
PostgresSaverorAsyncPostgresSaver, make sure to includeautocommit=Trueandrow_factory=dict_row(from psycopg.rows import dict_row). See a full example in this how-to guide.Why these parameters are required:
autocommit=True: Required for the.setup()method to properly commit the checkpoint tables to the database. Without this, table creation may not be persisted.row_factory=dict_row: Required because the PostgresSaver implementation accesses database rows using dictionary-style syntax (e.g.,row["column_name"]). The defaulttuple_rowfactory returns tuples that only support index-based access (e.g.,row[0]), which will causeTypeErrorexceptions when the checkpointer tries to access columns by name.Example of incorrect usage:
# ❌ This will fail with TypeError during checkpointer operations with psycopg.connect(DB_URI) as conn: # Missing autocommit=True and row_factory=dict_row checkpointer = PostgresSaver(conn) checkpointer.setup() # May not persist tables properly # Any operation that reads from database will fail with: # TypeError: tuple indices must be integers or slices, not str
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": 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.postgres.aio import AsyncPostgresSaver
async with AsyncPostgresSaver.from_conn_string(DB_URI) 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)]