- This makes our checkpoint benchmarks more closely resemble the
behavior of our prod checkpointers
- Also found and fixed a bug w multiple subgraphs in same node
accidentally sharing checkpoints
- This makes our checkpoint benchmarks more closely resemble the behavior of our prod checkpointers
- Also found and fixed a bug w multiple subgraphs in same node accidentally sharing checkpoints
- When there are no values in checkpoint no need to run through all the
PULL candidates
- When there are input writes save updated_channels to use on the next
call to prepare_next_tasks
- RunnableCallable: Skip signature checks for internal callables where
we know the signatures ahead of time
- PregelNode: Avoid redoing subgraphs serarch when copying it
- CompiledStateGraph: Avoid copying PregelNode when attaching writers
- RunnableCallable: Skip signature checks for internal callables where we know the signatures ahead of time
- PregelNode: Avoid redoing subgraphs serarch when copying it
- CompiledStateGraph: Avoid copying PregelNode when attaching writers
- When there are no values in checkpoint no need to run through all the PULL candidates
- When there are input writes save updated_channels to use on the next call to prepare_next_tasks
Leverage information about which channels were updated in the previous
step to determine which tasks should be triggered. This can result in
significant speed up in prepare_next_tasks in some situations.
Includes:
- Explicit unsetting of runnable context var
- Weakref for PregelExecutableTask
both to reduce the chance of keeping a reference to an internal object
and preventing garbage collection
## Description
The documentation for working with Pydantic and graph State recommends
to use `AnyMessage` when working with LangChain types, but the code
example uses `BaseMessage`.
Includes:
- Explicit unsetting of runnable context var
- Weakref for PregelExecutableTask
both to reduce the chance of keeping a reference to an internal object and preventing
garbage collection
