Instead of a recursive SQL CTE, collect the ancestor checkpoint ID chain in
Python by fetching all (checkpoint_id, parent_checkpoint_id) for the thread
in one query, then fetch writes with a plain WHERE checkpoint_id = ANY(...).
Simpler, avoids recursive query planner overhead, and uses well-indexed lookups.
DeltaChannel.checkpoint() now returns a zero-byte DeltaChannelSentinel
instead of duplicating delta data in checkpoint_blobs. Reconstruction
walks the parent checkpoint chain via checkpoint_writes (which already
holds per-step writes) and replays them through the operator.
In-memory benchmark (100 turns, ~20K tokens):
storage: 10.2 MB → 40.5 KB (251x reduction)
read: 0.6ms → 7.9ms (reconstruction cost, amortized by storage savings)
InMemorySaver and PostgresSaver override get_channel_writes() with
efficient implementations (Python dict walk and recursive CTE respectively).
The base class fallback uses self.list() with a thread-local recursion guard.
Rely on the runtime raise in DeltaChannel.from_checkpoint() instead of
a compile-time boolean flag. Savers that assemble DeltaChainValue inside
_load_blobs work transparently; savers that don't will pass through a raw
DeltaValue and hit a clear ValueError on first reload.
Removes: BaseCheckpointSaver.supports_delta_channels, the attribute on
InMemorySaver / PostgresSaver / AsyncPostgresSaver, the compile-time
UserWarning in StateGraph.compile(), and the associated test.
Fixes a critical deadlock that occurs when _load_diff_chains calls self._cursor()
from within _load_blobs while the outer _load_checkpoint_tuple already holds
self._cursor(). On bare (non-pool) connections, the threading.Lock is not
reentrant, causing a deadlock.
Solution: Pass the cursor as a parameter to _load_diff_chains and _load_blobs
instead of acquiring a new cursor within those methods. Updated _load_checkpoint_tuple
to acquire a cursor once at the top level and pass it through the call chain.
Changes:
- Updated _load_blobs signature to accept optional cur parameter
- Updated _load_diff_chains signature (base and implementations) to accept optional cur parameter
- Modified _load_checkpoint_tuple in PostgresSaver to acquire cursor and pass it
- Modified _load_checkpoint_tuple_async to acquire cursor only when diff_payloads exist
- Removed nested self._cursor() calls in _load_diff_chains and _load_diff_chains_async
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Add `_load_diff_chains_async` to `AsyncPostgresSaver` and override
`_load_checkpoint_tuple` to inline blob-parsing and diff-chain
resolution via async point-lookup traversal, mirroring the sync
`PostgresSaver._load_diff_chains` implementation. Add integration test
`test_diff_channel_chain_reconstruction` that skips gracefully when
`langgraph` core is not installed.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Thank you for contributing to LangGraph! Follow these steps to mark your
pull request as ready for review. **If any of these steps are not
completed, your PR will not be considered for review.**
- [x] **PR title**: Follows the format: {TYPE}({SCOPE}): {DESCRIPTION}
- Examples:
- feat(core): add multi-tenant support
- fix(cli): resolve flag parsing error
- docs(openai): update API usage examples
- Allowed `{TYPE}` values:
- feat, fix, docs, style, refactor, perf, test, build, ci, chore,
revert, release
- Allowed `{SCOPE}` values (optional):
- langgraph, docs, cli, checkpoint, checkpoint-postgres,
checkpoint-sqlite, prebuilt, scheduler-kafka, sdk-py
- Once you've written the title, please delete this checklist item; do
not include it in the PR.
- **Description:** Azure Postgres SQL server has a limitation when doing
create extension vector is not exists, even though it manually created
before on a schema.
- **Issue:** Even though `CREATE EXTENSION vector` is executed manually
before, the permission issue arises. Putting it in an if else block
solves the issue and its not a breaking change.
```
Because vector isn't a trusted extension, only members of "azure_pg_admin" are allowed to use CREATE EXTENSION vector
HINT: to learn how to allow an extension or see the list of allowed extensions, please refer to https://go.microsoft.com/fwlink/?linkid=2301063
```
Co-authored-by: Josh Rogers <josh@langchain.dev>
## Summary
Replace f-string SQL formatting with parameterized queries to prevent
potential SQL injection in checkpoint migration code.
## Changes
Updated the migration version tracking INSERT statements in all
checkpoint saver classes to use parameterized queries instead of
f-string formatting:
- `PostgresSaver`
(libs/checkpoint-postgres/langgraph/checkpoint/postgres/__init__.py:100)
- `AsyncPostgresSaver`
(libs/checkpoint-postgres/langgraph/checkpoint/postgres/aio.py:104-106)
- `ShallowPostgresSaver`
(libs/checkpoint-postgres/langgraph/checkpoint/postgres/shallow.py:255)
- `AsyncShallowPostgresSaver`
(libs/checkpoint-postgres/langgraph/checkpoint/postgres/shallow.py:617-619)
**Before (vulnerable to SQL injection):**
```python
cur.execute(f"INSERT INTO checkpoint_migrations (v) VALUES ({v})")
```
**After (using parameterized query):**
```python
cur.execute("INSERT INTO checkpoint_migrations (v) VALUES (%s)", (v,))
```
## Risk Assessment
The practical risk is low since `v` is an integer loop variable
controlled by the codebase. However, using string formatting in SQL
queries is a well-known anti-pattern that can lead to SQL injection
vulnerabilities, especially if the code is later refactored or copied to
other contexts.
## Testing
- ✅ All 216 tests passing on PostgreSQL 15 and 16
- ✅ Linting and type checking passing
- ✅ No functional changes to behavior
- **Description:** The final migration for the postgres checkpointer is
not currently idempotent. That presents problems when migrating from one
checkpointer to another or if migrations otherwise get applied twice.
This makes the final migration idempotent to avoid this problem.
- **Issue:** N/A
- **Dependencies:** N/A
- **Twitter handle:** N/A
Issue
Support for `Checkpoint.metadata.writes` was dropped in `langgraph`
v0.5.x.
In `langgraph-checkpoint-postgres` v2.0.23, metadata was serialized with
`BasePostgresSaver._dump_metadata` -> `JsonPlusSerializer.dumps` which
handles `pydantic.BaseModel`.
In v2.0.23, metadata is serialized with `psycopg.types.json.Jsonb`,
which raises `TypeError: Object of type AIMessage is not JSON
serializable` when trying to serialize `writes`.
Solution
- Add `BaseCheckpointSaver.get_serializable_checkpoint_metadata` which
pops the `writes` key.
- Log deprecation warning when strange version combinations are used
Solves https://github.com/langchain-ai/langgraph/issues/5769
---------
Co-authored-by: Alex Kondratev <56111142+soapun@users.noreply.github.com>
### Description
https://github.com/langchain-ai/langgraph/issues/6137 and
https://github.com/langchain-ai/langgraph/issues/5677 reported issues
where older checkpoints read by AsyncPostgresSaver/PostgresSaver from
`langgraph-checkpoint-postgres==2.0.19` fail to read channel values,
throwing `NoneType object is not a mapping`. This was due to a bug in
how `channel_values` is assembled:
```python
"channel_values": {
**value["checkpoint"].get("channel_values"), # <--- if channel_values doesn't exist (old checkpoint), **None errors
**self._load_blobs(value["channel_values"]),
},
```
This bug was observed for checkpoints generated by
`langgraph-checkpoint-postgres<=2.0.19`.
Fixed by providing a fallback to
`value["checkpoint"].get("channel_values")`:
```python
**value["checkpoint"],
"channel_values": {
**(
value["checkpoint"].get("channel_values") or {}
), # 'or {}' needed for backwards compat with v3 checkpoints and below, as v4 introduced channel_values key
**self._load_blobs(value["channel_values"]),
},
```
### Tests
Added test for AsyncPostgresSaver and test for PostgresSaver, using
monkeypatch to remove `channel_values` before CheckpointTuple is
assembled in `_load_checkpoint_tuple`.
### Solves
https://github.com/langchain-ai/langgraph/issues/6137 and
https://github.com/langchain-ai/langgraph/issues/5677
---------
Co-authored-by: Shahrukh Shaik <144558473+shahrukh-shaik@users.noreply.github.com>
This PR updates the dependencies in all Python packages using `uv lock
--upgrade`.
This is an automated PR created by the UV Lock Upgrade workflow.
To make tests pass:
* linting fixes
* whitespace fixes in snapshots
---------
Co-authored-by: sydney-runkle <54324534+sydney-runkle@users.noreply.github.com>
Co-authored-by: Sydney Runkle <sydneymarierunkle@gmail.com>
### Description
Export PoolConfig from langgraph.store.postgres.__init__ so the
documented import from langgraph.store.postgres import
AsyncPostgresStore, PoolConfig works as shown in the AsyncPostgresStore
examples. This resolves a docs vs. code inconsistency without changing
behavior.
### Issue
N/A
### Dependencies:
None
---------
Co-authored-by: William FH <13333726+hinthornw@users.noreply.github.com>
Co-authored-by: Sydney Runkle <54324534+sydney-runkle@users.noreply.github.com>
- Replaces checkpoint_during: bool
- checkpoint_during is deprecated but still respected
- We implement three durability modes (from least to most durable):
- "exit" - save checkpoint only when the graph exits (equivalent to
checkpoint_during=False)
- "async" - save checkpoint asynchronously while the next step executes
(the default, equivalent to old checkpoint_during=True)
- "sync" - save checkpoint synchronously before the next step starts
(new mode, slower but most durable)
Co-authored-by: Sydney Runkle <54324534+sydney-runkle@users.noreply.github.com>
- Channels containing primitive values don't need to be stored in separate rows in blobs table, as the overhead of a separate row will usually be higher than the size of the value
- This applies for instance to all internal channels used to manage edges, so it has a big impact just from that. It can also apply to user-managed channels depending on their values
- The same channel may switch storage between versions without any issue
Prepare langgraph-checkpoint for 0.5
- Given we have no upper bound on langgraph-checkpoint dep need to undo all changes in langgraph-checkpoint that might break previous versions of langgraph
- This has been superseded by saving the individual writes of each task through put_writes()
- Removing this speeds up checkpoint operations as it was duplicating data saved elsewhere already
- Instead store sends in a Topic channel, removing the need to fetch sends as writes against the parent checkpoint
- Remove deprecated/unused functions in langgraph-checkpoint (will require bumping min range for langgraph-checkpoint in langgraph lib)
- Implement migration of old pending sends in langgraph-checkpoint-postgres
- Ensure parent config of `checkpoint_during=False` checkpoints always points to checkpoints that were also saved
* Migrate to `uv`
* Format `pyproject.toml` files properly
* Remove upper bounds on dependencies, and bounds on dev dependencies
(we should be using latest)
* Move to hatch for packaing
In the future we should:
* Set up dependabot / automate lockfile updates and tests
* Add tests for min compatible versions (I'll do this right after merge)
* Use dynamic versioning
* Bump `pydantic` to v2.11.4 in the lockfile, we have some tests failing
Sydney Runkle