### Description
Adds Redis as a supported cache backend for LangGraph node-level
caching, enabling distributed caching across multiple processes/servers.
This implementation follows the same patterns as existing InMemoryCache
and SqliteCache.
### Key changes
- New RedisCache class implementing the BaseCache interface
- Support for TTL-based expiration and batch operations
- Worker-specific cache prefixes for parallel test isolation
### Dependencies
- redis package (already included in dev dependencies)
### Test Plan
- Unit tests: Added Redis cache tests covering basic operations, TTL,
batch operations, and error handling
- Integration tests: Redis cache integrated into existing LangGraph test
suite, tested with all checkpointer combinations
Reproduces:
https://github.com/langchain-ai/langgraph/issues/5249#issuecomment-3156519635
Caused after this change:
https://github.com/langchain-ai/langgraph/pull/4843
Fix to allow emitting messages from subgraphs if the subgraphs
explicitly used a stream mode "messages".
```python
def node_in_parent(...):
# subgraph was called as a function.
# messages are explicitly requested.
for event in subgraph.stream(..., stream_mode="messages"):
# something is done with `event`
return ...
# subgraphs = False!
parent_graph.invoke(..., subgraphs=False)
```
The code above should continue to work correctly regardless of the value
of subgraphs as streaming messages was requested explicitly in the
parent node!
---------
Co-authored-by: Sydney Runkle <54324534+sydney-runkle@users.noreply.github.com>
- This makes prepare_next_tasks constant on number of nodes in all
cases, whereas before we were falling back to node iteration when
resuming from an existing checkpoint
`MessageGraph` is deprecated, to be removed in v2.
A `StateGraph` with a `messages` key should be used instead.
Alternatively, folks can use `Annotated[list[AnyMessage], add_messages]` as their state schema.
Reverts https://github.com/langchain-ai/langgraph/pull/5562
I anticipate that we want to do another pass at a refactor here in the
short term, but this makes it easier to adapt to new langchain core
message types for v0.4 support in the short term.
Fixes https://github.com/langchain-ai/langgraph/issues/5784
* Removes usage of `is_last_step`, no longer needed with
`remaining_steps`
* Make `remaining_steps` `NotRequired` so that json schema doesn't
suggest need for user input
* Move `PregelScratchpad` to shared utils file to prevent circular
import issue (it's used from `channels/managed` and other pregel files).
* Ensures that managed values wrapped in `NotRequired` or `Required` are
still recognized!
Fixes: #5787
Ensures that if `config` is not typed as one of `RunanbleConfig` or
`Optional[RunnableConfig]` a warning is raised to help developers avoid
unexpected results at invocation time.
---------
Co-authored-by: open-swe[bot] <open-swe@users.noreply.github.com>
Co-authored-by: Sydney Runkle <sydneymarierunkle@gmail.com>
Fixes#5781
Fixes the incorrect import statement in the Python documentation
tutorial.
- Changed import from `MemorySaver` to `InMemorySaver`
- Ensures consistency between import statement and class instantiation
- Verified through formatting and linting checks
The documentation now correctly reflects the proper import for the
InMemorySaver class.
---------
Co-authored-by: open-swe[bot] <open-swe@users.noreply.github.com>
Fixes https://github.com/langchain-ai/langgraph/issues/5795
* Must use `category=None` on decorator so that we get type checking
support but no dupe warning
* Fixed tuple on `confix_type` warning causing false warning
I suppose that the code snippets are intended to run each on its own. To
guarantee this the snippet for the example:
"Write long-temr memory from tools"
needs to include `RunnableConfig`
Same also for the second commit of this pull request.
The other commits are about similar issues, where imports are missing to
make a snippet executable on its own.
---------
Signed-off-by: Kai Wendel <kai.wendel@iws.uni-stuttgart.de>
Co-authored-by: Eugene Yurtsev <eugene@langchain.dev>
Co-authored-by: Lauren Hirata Singh <lauren@langchain.dev>
open-swe[bot]