mirror of https://github.com/hwchase17/langchain
Create new RunnableSerializable base class in preparation for configurable runnables (#11279)
- Also move RunnableBranch to its own file <!-- Thank you for contributing to LangChain! Replace this entire comment with: - **Description:** a description of the change, - **Issue:** the issue # it fixes (if applicable), - **Dependencies:** any dependencies required for this change, - **Tag maintainer:** for a quicker response, tag the relevant maintainer (see below), - **Twitter handle:** we announce bigger features on Twitter. If your PR gets announced, and you'd like a mention, we'll gladly shout you out! Please make sure your PR is passing linting and testing before submitting. Run `make format`, `make lint` and `make test` to check this locally. See contribution guidelines for more information on how to write/run tests, lint, etc: https://github.com/langchain-ai/langchain/blob/master/.github/CONTRIBUTING.md If you're adding a new integration, please include: 1. a test for the integration, preferably unit tests that do not rely on network access, 2. an example notebook showing its use. It lives in `docs/extras` directory. If no one reviews your PR within a few days, please @-mention one of @baskaryan, @eyurtsev, @hwchase17. -->pull/11294/head^2
commit
0638f7b83a
@ -0,0 +1,235 @@
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from typing import (
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Any,
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Awaitable,
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Callable,
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List,
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Mapping,
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Optional,
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Sequence,
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Tuple,
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Type,
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Union,
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cast,
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)
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from langchain.load.dump import dumpd
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from langchain.pydantic_v1 import BaseModel
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from langchain.schema.runnable.base import (
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Runnable,
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RunnableLike,
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RunnableSerializable,
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coerce_to_runnable,
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)
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from langchain.schema.runnable.config import (
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RunnableConfig,
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ensure_config,
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get_callback_manager_for_config,
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patch_config,
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)
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from langchain.schema.runnable.utils import Input, Output
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class RunnableBranch(RunnableSerializable[Input, Output]):
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"""A Runnable that selects which branch to run based on a condition.
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The runnable is initialized with a list of (condition, runnable) pairs and
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a default branch.
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When operating on an input, the first condition that evaluates to True is
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selected, and the corresponding runnable is run on the input.
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If no condition evaluates to True, the default branch is run on the input.
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Examples:
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.. code-block:: python
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from langchain.schema.runnable import RunnableBranch
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branch = RunnableBranch(
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(lambda x: isinstance(x, str), lambda x: x.upper()),
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(lambda x: isinstance(x, int), lambda x: x + 1),
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(lambda x: isinstance(x, float), lambda x: x * 2),
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lambda x: "goodbye",
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)
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branch.invoke("hello") # "HELLO"
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branch.invoke(None) # "goodbye"
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"""
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branches: Sequence[Tuple[Runnable[Input, bool], Runnable[Input, Output]]]
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default: Runnable[Input, Output]
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def __init__(
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self,
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*branches: Union[
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Tuple[
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Union[
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Runnable[Input, bool],
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Callable[[Input], bool],
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Callable[[Input], Awaitable[bool]],
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],
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RunnableLike,
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],
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RunnableLike, # To accommodate the default branch
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],
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) -> None:
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"""A Runnable that runs one of two branches based on a condition."""
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if len(branches) < 2:
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raise ValueError("RunnableBranch requires at least two branches")
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default = branches[-1]
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if not isinstance(
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default, (Runnable, Callable, Mapping) # type: ignore[arg-type]
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):
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raise TypeError(
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"RunnableBranch default must be runnable, callable or mapping."
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)
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default_ = cast(
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Runnable[Input, Output], coerce_to_runnable(cast(RunnableLike, default))
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)
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_branches = []
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for branch in branches[:-1]:
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if not isinstance(branch, (tuple, list)): # type: ignore[arg-type]
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raise TypeError(
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f"RunnableBranch branches must be "
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f"tuples or lists, not {type(branch)}"
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)
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if not len(branch) == 2:
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raise ValueError(
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f"RunnableBranch branches must be "
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f"tuples or lists of length 2, not {len(branch)}"
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)
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condition, runnable = branch
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condition = cast(Runnable[Input, bool], coerce_to_runnable(condition))
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runnable = coerce_to_runnable(runnable)
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_branches.append((condition, runnable))
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super().__init__(branches=_branches, default=default_)
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class Config:
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arbitrary_types_allowed = True
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@classmethod
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def is_lc_serializable(cls) -> bool:
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"""RunnableBranch is serializable if all its branches are serializable."""
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return True
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@classmethod
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def get_lc_namespace(cls) -> List[str]:
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"""The namespace of a RunnableBranch is the namespace of its default branch."""
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return cls.__module__.split(".")[:-1]
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@property
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def input_schema(self) -> Type[BaseModel]:
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runnables = (
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[self.default]
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+ [r for _, r in self.branches]
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+ [r for r, _ in self.branches]
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)
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for runnable in runnables:
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if runnable.input_schema.schema().get("type") is not None:
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return runnable.input_schema
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return super().input_schema
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def invoke(
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self, input: Input, config: Optional[RunnableConfig] = None, **kwargs: Any
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) -> Output:
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"""First evaluates the condition, then delegate to true or false branch."""
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config = ensure_config(config)
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callback_manager = get_callback_manager_for_config(config)
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run_manager = callback_manager.on_chain_start(
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dumpd(self),
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input,
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name=config.get("run_name"),
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)
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try:
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for idx, branch in enumerate(self.branches):
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condition, runnable = branch
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expression_value = condition.invoke(
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input,
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config=patch_config(
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config,
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callbacks=run_manager.get_child(tag=f"condition:{idx + 1}"),
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),
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)
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if expression_value:
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output = runnable.invoke(
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input,
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config=patch_config(
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config,
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callbacks=run_manager.get_child(tag=f"branch:{idx + 1}"),
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),
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**kwargs,
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)
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break
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else:
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output = self.default.invoke(
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input,
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config=patch_config(
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config, callbacks=run_manager.get_child(tag="branch:default")
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),
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**kwargs,
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)
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except Exception as e:
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run_manager.on_chain_error(e)
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raise
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run_manager.on_chain_end(dumpd(output))
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return output
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async def ainvoke(
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self, input: Input, config: Optional[RunnableConfig] = None, **kwargs: Any
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) -> Output:
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"""Async version of invoke."""
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config = ensure_config(config)
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callback_manager = get_callback_manager_for_config(config)
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run_manager = callback_manager.on_chain_start(
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dumpd(self),
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input,
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name=config.get("run_name"),
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)
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try:
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for idx, branch in enumerate(self.branches):
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condition, runnable = branch
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expression_value = await condition.ainvoke(
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input,
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config=patch_config(
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config,
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callbacks=run_manager.get_child(tag=f"condition:{idx + 1}"),
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),
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)
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if expression_value:
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output = await runnable.ainvoke(
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input,
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config=patch_config(
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config,
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callbacks=run_manager.get_child(tag=f"branch:{idx + 1}"),
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),
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**kwargs,
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)
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break
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else:
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output = await self.default.ainvoke(
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input,
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config=patch_config(
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config, callbacks=run_manager.get_child(tag="branch:default")
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),
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**kwargs,
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)
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except Exception as e:
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run_manager.on_chain_error(e)
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raise
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run_manager.on_chain_end(dumpd(output))
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return output
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@ -0,0 +1,286 @@
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import asyncio
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from typing import (
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TYPE_CHECKING,
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Any,
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Iterator,
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List,
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Optional,
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Sequence,
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Tuple,
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Type,
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Union,
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)
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from langchain.load.dump import dumpd
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from langchain.pydantic_v1 import BaseModel
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from langchain.schema.runnable.base import Runnable, RunnableSerializable
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from langchain.schema.runnable.config import (
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RunnableConfig,
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ensure_config,
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get_async_callback_manager_for_config,
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get_callback_manager_for_config,
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get_config_list,
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patch_config,
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)
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from langchain.schema.runnable.utils import Input, Output
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if TYPE_CHECKING:
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from langchain.callbacks.manager import AsyncCallbackManagerForChainRun
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class RunnableWithFallbacks(RunnableSerializable[Input, Output]):
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"""
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A Runnable that can fallback to other Runnables if it fails.
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"""
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runnable: Runnable[Input, Output]
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fallbacks: Sequence[Runnable[Input, Output]]
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exceptions_to_handle: Tuple[Type[BaseException], ...] = (Exception,)
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class Config:
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arbitrary_types_allowed = True
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@property
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def InputType(self) -> Type[Input]:
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return self.runnable.InputType
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@property
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def OutputType(self) -> Type[Output]:
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return self.runnable.OutputType
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@property
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def input_schema(self) -> Type[BaseModel]:
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return self.runnable.input_schema
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@property
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def output_schema(self) -> Type[BaseModel]:
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return self.runnable.output_schema
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def config_schema(
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self, *, include: Optional[Sequence[str]] = None
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) -> Type[BaseModel]:
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return self.runnable.config_schema(include=include)
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@classmethod
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def is_lc_serializable(cls) -> bool:
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return True
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@classmethod
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def get_lc_namespace(cls) -> List[str]:
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return cls.__module__.split(".")[:-1]
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@property
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def runnables(self) -> Iterator[Runnable[Input, Output]]:
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yield self.runnable
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yield from self.fallbacks
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def invoke(
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self, input: Input, config: Optional[RunnableConfig] = None, **kwargs: Any
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) -> Output:
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# setup callbacks
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config = ensure_config(config)
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callback_manager = get_callback_manager_for_config(config)
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# start the root run
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run_manager = callback_manager.on_chain_start(
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dumpd(self), input, name=config.get("run_name")
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)
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first_error = None
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for runnable in self.runnables:
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try:
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output = runnable.invoke(
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input,
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patch_config(config, callbacks=run_manager.get_child()),
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**kwargs,
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)
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except self.exceptions_to_handle as e:
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if first_error is None:
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first_error = e
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except BaseException as e:
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run_manager.on_chain_error(e)
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raise e
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else:
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run_manager.on_chain_end(output)
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return output
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if first_error is None:
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raise ValueError("No error stored at end of fallbacks.")
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run_manager.on_chain_error(first_error)
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raise first_error
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async def ainvoke(
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self,
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input: Input,
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config: Optional[RunnableConfig] = None,
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**kwargs: Optional[Any],
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) -> Output:
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# setup callbacks
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config = ensure_config(config)
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callback_manager = get_async_callback_manager_for_config(config)
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# start the root run
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run_manager = await callback_manager.on_chain_start(
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dumpd(self), input, name=config.get("run_name")
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)
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first_error = None
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for runnable in self.runnables:
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try:
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output = await runnable.ainvoke(
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input,
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patch_config(config, callbacks=run_manager.get_child()),
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**kwargs,
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)
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except self.exceptions_to_handle as e:
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if first_error is None:
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first_error = e
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except BaseException as e:
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await run_manager.on_chain_error(e)
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raise e
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else:
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await run_manager.on_chain_end(output)
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return output
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if first_error is None:
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raise ValueError("No error stored at end of fallbacks.")
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await run_manager.on_chain_error(first_error)
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raise first_error
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def batch(
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self,
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inputs: List[Input],
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config: Optional[Union[RunnableConfig, List[RunnableConfig]]] = None,
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*,
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return_exceptions: bool = False,
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**kwargs: Optional[Any],
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) -> List[Output]:
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from langchain.callbacks.manager import CallbackManager
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if return_exceptions:
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raise NotImplementedError()
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if not inputs:
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return []
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# setup callbacks
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configs = get_config_list(config, len(inputs))
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callback_managers = [
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CallbackManager.configure(
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inheritable_callbacks=config.get("callbacks"),
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local_callbacks=None,
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verbose=False,
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inheritable_tags=config.get("tags"),
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local_tags=None,
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inheritable_metadata=config.get("metadata"),
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local_metadata=None,
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)
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for config in configs
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]
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# start the root runs, one per input
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run_managers = [
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cm.on_chain_start(
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dumpd(self),
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input if isinstance(input, dict) else {"input": input},
|
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name=config.get("run_name"),
|
||||
)
|
||||
for cm, input, config in zip(callback_managers, inputs, configs)
|
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]
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first_error = None
|
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for runnable in self.runnables:
|
||||
try:
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outputs = runnable.batch(
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inputs,
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[
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# each step a child run of the corresponding root run
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patch_config(config, callbacks=rm.get_child())
|
||||
for rm, config in zip(run_managers, configs)
|
||||
],
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return_exceptions=return_exceptions,
|
||||
**kwargs,
|
||||
)
|
||||
except self.exceptions_to_handle as e:
|
||||
if first_error is None:
|
||||
first_error = e
|
||||
except BaseException as e:
|
||||
for rm in run_managers:
|
||||
rm.on_chain_error(e)
|
||||
raise e
|
||||
else:
|
||||
for rm, output in zip(run_managers, outputs):
|
||||
rm.on_chain_end(output)
|
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return outputs
|
||||
if first_error is None:
|
||||
raise ValueError("No error stored at end of fallbacks.")
|
||||
for rm in run_managers:
|
||||
rm.on_chain_error(first_error)
|
||||
raise first_error
|
||||
|
||||
async def abatch(
|
||||
self,
|
||||
inputs: List[Input],
|
||||
config: Optional[Union[RunnableConfig, List[RunnableConfig]]] = None,
|
||||
*,
|
||||
return_exceptions: bool = False,
|
||||
**kwargs: Optional[Any],
|
||||
) -> List[Output]:
|
||||
from langchain.callbacks.manager import AsyncCallbackManager
|
||||
|
||||
if return_exceptions:
|
||||
raise NotImplementedError()
|
||||
|
||||
if not inputs:
|
||||
return []
|
||||
|
||||
# setup callbacks
|
||||
configs = get_config_list(config, len(inputs))
|
||||
callback_managers = [
|
||||
AsyncCallbackManager.configure(
|
||||
inheritable_callbacks=config.get("callbacks"),
|
||||
local_callbacks=None,
|
||||
verbose=False,
|
||||
inheritable_tags=config.get("tags"),
|
||||
local_tags=None,
|
||||
inheritable_metadata=config.get("metadata"),
|
||||
local_metadata=None,
|
||||
)
|
||||
for config in configs
|
||||
]
|
||||
# start the root runs, one per input
|
||||
run_managers: List[AsyncCallbackManagerForChainRun] = await asyncio.gather(
|
||||
*(
|
||||
cm.on_chain_start(
|
||||
dumpd(self),
|
||||
input,
|
||||
name=config.get("run_name"),
|
||||
)
|
||||
for cm, input, config in zip(callback_managers, inputs, configs)
|
||||
)
|
||||
)
|
||||
|
||||
first_error = None
|
||||
for runnable in self.runnables:
|
||||
try:
|
||||
outputs = await runnable.abatch(
|
||||
inputs,
|
||||
[
|
||||
# each step a child run of the corresponding root run
|
||||
patch_config(config, callbacks=rm.get_child())
|
||||
for rm, config in zip(run_managers, configs)
|
||||
],
|
||||
return_exceptions=return_exceptions,
|
||||
**kwargs,
|
||||
)
|
||||
except self.exceptions_to_handle as e:
|
||||
if first_error is None:
|
||||
first_error = e
|
||||
except BaseException as e:
|
||||
await asyncio.gather(*(rm.on_chain_error(e) for rm in run_managers))
|
||||
else:
|
||||
await asyncio.gather(
|
||||
*(
|
||||
rm.on_chain_end(output)
|
||||
for rm, output in zip(run_managers, outputs)
|
||||
)
|
||||
)
|
||||
return outputs
|
||||
if first_error is None:
|
||||
raise ValueError("No error stored at end of fallbacks.")
|
||||
await asyncio.gather(*(rm.on_chain_error(first_error) for rm in run_managers))
|
||||
raise first_error
|
Loading…
Reference in New Issue