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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. -->
This commit is contained in:
Nuno Campos
GitHub
commit
0638f7b83a
@ -21,7 +21,6 @@ from langchain.callbacks.manager import (
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Callbacks,
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)
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from langchain.load.dump import dumpd
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from langchain.load.serializable import Serializable
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from langchain.pydantic_v1 import (
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BaseModel,
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Field,
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@ -30,7 +29,7 @@ from langchain.pydantic_v1 import (
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validator,
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)
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from langchain.schema import RUN_KEY, BaseMemory, RunInfo
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from langchain.schema.runnable import Runnable, RunnableConfig
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from langchain.schema.runnable import RunnableConfig, RunnableSerializable
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logger = logging.getLogger(__name__)
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@ -39,7 +38,7 @@ def _get_verbosity() -> bool:
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return langchain.verbose
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class Chain(Serializable, Runnable[Dict[str, Any], Dict[str, Any]], ABC):
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class Chain(RunnableSerializable[Dict[str, Any], Dict[str, Any]], ABC):
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"""Abstract base class for creating structured sequences of calls to components.
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Chains should be used to encode a sequence of calls to components like
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@ -14,7 +14,7 @@ from langchain.schema.runnable import RunnableConfig
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class FakeListLLM(LLM):
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"""Fake LLM for testing purposes."""
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responses: List
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responses: List[str]
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sleep: Optional[float] = None
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i: int = 0
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@ -15,11 +15,10 @@ from typing import (
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from typing_extensions import TypeAlias
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from langchain.load.serializable import Serializable
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from langchain.schema.messages import AnyMessage, BaseMessage, get_buffer_string
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from langchain.schema.output import LLMResult
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from langchain.schema.prompt import PromptValue
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from langchain.schema.runnable import Runnable
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from langchain.schema.runnable import RunnableSerializable
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from langchain.utils import get_pydantic_field_names
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if TYPE_CHECKING:
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@ -54,7 +53,7 @@ LanguageModelOutput = TypeVar("LanguageModelOutput")
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class BaseLanguageModel(
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Serializable, Runnable[LanguageModelInput, LanguageModelOutput], ABC
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RunnableSerializable[LanguageModelInput, LanguageModelOutput], ABC
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):
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"""Abstract base class for interfacing with language models.
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@ -16,7 +16,6 @@ from typing import (
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from typing_extensions import get_args
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from langchain.load.serializable import Serializable
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from langchain.schema.messages import AnyMessage, BaseMessage, BaseMessageChunk
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from langchain.schema.output import (
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ChatGeneration,
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@ -25,12 +24,12 @@ from langchain.schema.output import (
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GenerationChunk,
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)
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from langchain.schema.prompt import PromptValue
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from langchain.schema.runnable import Runnable, RunnableConfig
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from langchain.schema.runnable import RunnableConfig, RunnableSerializable
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T = TypeVar("T")
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class BaseLLMOutputParser(Serializable, Generic[T], ABC):
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class BaseLLMOutputParser(Generic[T], ABC):
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"""Abstract base class for parsing the outputs of a model."""
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@abstractmethod
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@ -63,7 +62,7 @@ class BaseLLMOutputParser(Serializable, Generic[T], ABC):
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class BaseGenerationOutputParser(
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BaseLLMOutputParser, Runnable[Union[str, BaseMessage], T]
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BaseLLMOutputParser, RunnableSerializable[Union[str, BaseMessage], T]
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):
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"""Base class to parse the output of an LLM call."""
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@ -121,7 +120,9 @@ class BaseGenerationOutputParser(
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)
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class BaseOutputParser(BaseLLMOutputParser, Runnable[Union[str, BaseMessage], T]):
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class BaseOutputParser(
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BaseLLMOutputParser, RunnableSerializable[Union[str, BaseMessage], T]
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):
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"""Base class to parse the output of an LLM call.
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Output parsers help structure language model responses.
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@ -7,15 +7,14 @@ from typing import Any, Callable, Dict, List, Mapping, Optional, Union
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import yaml
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from langchain.load.serializable import Serializable
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from langchain.pydantic_v1 import BaseModel, Field, create_model, root_validator
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from langchain.schema.document import Document
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from langchain.schema.output_parser import BaseOutputParser
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from langchain.schema.prompt import PromptValue
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from langchain.schema.runnable import Runnable, RunnableConfig
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from langchain.schema.runnable import RunnableConfig, RunnableSerializable
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class BasePromptTemplate(Serializable, Runnable[Dict, PromptValue], ABC):
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class BasePromptTemplate(RunnableSerializable[Dict, PromptValue], ABC):
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"""Base class for all prompt templates, returning a prompt."""
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input_variables: List[str]
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@ -6,9 +6,8 @@ from inspect import signature
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from typing import TYPE_CHECKING, Any, Dict, List, Optional
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from langchain.load.dump import dumpd
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from langchain.load.serializable import Serializable
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from langchain.schema.document import Document
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from langchain.schema.runnable import Runnable, RunnableConfig
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from langchain.schema.runnable import RunnableConfig, RunnableSerializable
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if TYPE_CHECKING:
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from langchain.callbacks.manager import (
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@ -18,7 +17,7 @@ if TYPE_CHECKING:
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)
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class BaseRetriever(Serializable, Runnable[str, List[Document]], ABC):
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class BaseRetriever(RunnableSerializable[str, List[Document]], ABC):
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"""Abstract base class for a Document retrieval system.
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A retrieval system is defined as something that can take string queries and return
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@ -2,13 +2,14 @@ from langchain.schema.runnable._locals import GetLocalVar, PutLocalVar
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from langchain.schema.runnable.base import (
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Runnable,
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RunnableBinding,
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RunnableBranch,
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RunnableLambda,
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RunnableMap,
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RunnableSequence,
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RunnableWithFallbacks,
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RunnableSerializable,
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)
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from langchain.schema.runnable.branch import RunnableBranch
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from langchain.schema.runnable.config import RunnableConfig, patch_config
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from langchain.schema.runnable.fallbacks import RunnableWithFallbacks
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from langchain.schema.runnable.passthrough import RunnablePassthrough
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from langchain.schema.runnable.router import RouterInput, RouterRunnable
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@ -19,6 +20,7 @@ __all__ = [
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"RouterInput",
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"RouterRunnable",
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"Runnable",
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"RunnableSerializable",
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"RunnableBinding",
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"RunnableBranch",
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"RunnableConfig",
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@ -11,8 +11,7 @@ from typing import (
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Union,
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)
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from langchain.load.serializable import Serializable
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from langchain.schema.runnable.base import Input, Output, Runnable
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from langchain.schema.runnable.base import Input, Output, RunnableSerializable
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from langchain.schema.runnable.config import RunnableConfig
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from langchain.schema.runnable.passthrough import RunnablePassthrough
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@ -104,7 +103,7 @@ class PutLocalVar(RunnablePassthrough):
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class GetLocalVar(
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Serializable, Runnable[Input, Union[Output, Dict[str, Union[Input, Output]]]]
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RunnableSerializable[Input, Union[Output, Dict[str, Union[Input, Output]]]]
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):
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key: str
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"""The key to extract from the local state."""
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@ -36,6 +36,9 @@ if TYPE_CHECKING:
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CallbackManagerForChainRun,
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)
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from langchain.callbacks.tracers.log_stream import RunLogPatch
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from langchain.schema.runnable.fallbacks import (
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RunnableWithFallbacks as RunnableWithFallbacksT,
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)
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from langchain.load.dump import dumpd
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@ -119,6 +122,24 @@ class Runnable(Generic[Input, Output], ABC):
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self.__class__.__name__ + "Output", __root__=(root_type, None)
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)
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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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class _Config:
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arbitrary_types_allowed = True
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include = include or []
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return create_model( # type: ignore[call-overload]
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self.__class__.__name__ + "Config",
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__config__=_Config,
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**{
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field_name: (field_type, None)
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for field_name, field_type in RunnableConfig.__annotations__.items()
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if field_name in include
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},
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)
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def __or__(
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self,
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other: Union[
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@ -437,7 +458,9 @@ class Runnable(Generic[Input, Output], ABC):
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fallbacks: Sequence[Runnable[Input, Output]],
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*,
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exceptions_to_handle: Tuple[Type[BaseException], ...] = (Exception,),
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) -> RunnableWithFallbacks[Input, Output]:
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) -> RunnableWithFallbacksT[Input, Output]:
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from langchain.schema.runnable.fallbacks import RunnableWithFallbacks
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return RunnableWithFallbacks(
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runnable=self,
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fallbacks=fallbacks,
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@ -812,462 +835,11 @@ class Runnable(Generic[Input, Output], ABC):
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await run_manager.on_chain_end(final_output, inputs=final_input)
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class RunnableBranch(Serializable, Runnable[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(self, input: Input, config: Optional[RunnableConfig] = None) -> 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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)
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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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)
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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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|
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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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|
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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,
|
||||
callbacks=run_manager.get_child(tag=f"branch:{idx + 1}"),
|
||||
),
|
||||
**kwargs,
|
||||
)
|
||||
break
|
||||
else:
|
||||
output = await self.default.ainvoke(
|
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input,
|
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config=patch_config(
|
||||
config, callbacks=run_manager.get_child(tag="branch:default")
|
||||
),
|
||||
**kwargs,
|
||||
)
|
||||
except Exception as e:
|
||||
run_manager.on_chain_error(e)
|
||||
raise
|
||||
run_manager.on_chain_end(dumpd(output))
|
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return output
|
||||
class RunnableSerializable(Serializable, Runnable[Input, Output]):
|
||||
pass
|
||||
|
||||
|
||||
class RunnableWithFallbacks(Serializable, Runnable[Input, Output]):
|
||||
"""
|
||||
A Runnable that can fallback to other Runnables if it fails.
|
||||
"""
|
||||
|
||||
runnable: Runnable[Input, Output]
|
||||
fallbacks: Sequence[Runnable[Input, Output]]
|
||||
exceptions_to_handle: Tuple[Type[BaseException], ...] = (Exception,)
|
||||
|
||||
class Config:
|
||||
arbitrary_types_allowed = True
|
||||
|
||||
@property
|
||||
def InputType(self) -> Type[Input]:
|
||||
return self.runnable.InputType
|
||||
|
||||
@property
|
||||
def OutputType(self) -> Type[Output]:
|
||||
return self.runnable.OutputType
|
||||
|
||||
@property
|
||||
def input_schema(self) -> Type[BaseModel]:
|
||||
return self.runnable.input_schema
|
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|
||||
@property
|
||||
def output_schema(self) -> Type[BaseModel]:
|
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return self.runnable.output_schema
|
||||
|
||||
@classmethod
|
||||
def is_lc_serializable(cls) -> bool:
|
||||
return True
|
||||
|
||||
@classmethod
|
||||
def get_lc_namespace(cls) -> List[str]:
|
||||
return cls.__module__.split(".")[:-1]
|
||||
|
||||
@property
|
||||
def runnables(self) -> Iterator[Runnable[Input, Output]]:
|
||||
yield self.runnable
|
||||
yield from self.fallbacks
|
||||
|
||||
def invoke(
|
||||
self, input: Input, config: Optional[RunnableConfig] = None, **kwargs: Any
|
||||
) -> Output:
|
||||
# setup callbacks
|
||||
config = ensure_config(config)
|
||||
callback_manager = get_callback_manager_for_config(config)
|
||||
# start the root run
|
||||
run_manager = callback_manager.on_chain_start(
|
||||
dumpd(self), input, name=config.get("run_name")
|
||||
)
|
||||
first_error = None
|
||||
for runnable in self.runnables:
|
||||
try:
|
||||
output = runnable.invoke(
|
||||
input,
|
||||
patch_config(config, callbacks=run_manager.get_child()),
|
||||
**kwargs,
|
||||
)
|
||||
except self.exceptions_to_handle as e:
|
||||
if first_error is None:
|
||||
first_error = e
|
||||
except BaseException as e:
|
||||
run_manager.on_chain_error(e)
|
||||
raise e
|
||||
else:
|
||||
run_manager.on_chain_end(output)
|
||||
return output
|
||||
if first_error is None:
|
||||
raise ValueError("No error stored at end of fallbacks.")
|
||||
run_manager.on_chain_error(first_error)
|
||||
raise first_error
|
||||
|
||||
async def ainvoke(
|
||||
self,
|
||||
input: Input,
|
||||
config: Optional[RunnableConfig] = None,
|
||||
**kwargs: Optional[Any],
|
||||
) -> Output:
|
||||
# setup callbacks
|
||||
config = ensure_config(config)
|
||||
callback_manager = get_async_callback_manager_for_config(config)
|
||||
# start the root run
|
||||
run_manager = await callback_manager.on_chain_start(
|
||||
dumpd(self), input, name=config.get("run_name")
|
||||
)
|
||||
|
||||
first_error = None
|
||||
for runnable in self.runnables:
|
||||
try:
|
||||
output = await runnable.ainvoke(
|
||||
input,
|
||||
patch_config(config, callbacks=run_manager.get_child()),
|
||||
**kwargs,
|
||||
)
|
||||
except self.exceptions_to_handle as e:
|
||||
if first_error is None:
|
||||
first_error = e
|
||||
except BaseException as e:
|
||||
await run_manager.on_chain_error(e)
|
||||
raise e
|
||||
else:
|
||||
await run_manager.on_chain_end(output)
|
||||
return output
|
||||
if first_error is None:
|
||||
raise ValueError("No error stored at end of fallbacks.")
|
||||
await run_manager.on_chain_error(first_error)
|
||||
raise first_error
|
||||
|
||||
def batch(
|
||||
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 CallbackManager
|
||||
|
||||
if return_exceptions:
|
||||
raise NotImplementedError()
|
||||
|
||||
if not inputs:
|
||||
return []
|
||||
|
||||
# setup callbacks
|
||||
configs = get_config_list(config, len(inputs))
|
||||
callback_managers = [
|
||||
CallbackManager.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 = [
|
||||
cm.on_chain_start(
|
||||
dumpd(self),
|
||||
input if isinstance(input, dict) else {"input": 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 = runnable.batch(
|
||||
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:
|
||||
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)
|
||||
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
|
||||
|
||||
|
||||
class RunnableSequence(Serializable, Runnable[Input, Output]):
|
||||
class RunnableSequence(RunnableSerializable[Input, Output]):
|
||||
"""
|
||||
A sequence of runnables, where the output of each is the input of the next.
|
||||
"""
|
||||
@ -1749,7 +1321,7 @@ class RunnableSequence(Serializable, Runnable[Input, Output]):
|
||||
yield chunk
|
||||
|
||||
|
||||
class RunnableMap(Serializable, Runnable[Input, Dict[str, Any]]):
|
||||
class RunnableMap(RunnableSerializable[Input, Dict[str, Any]]):
|
||||
"""
|
||||
A runnable that runs a mapping of runnables in parallel,
|
||||
and returns a mapping of their outputs.
|
||||
@ -1799,7 +1371,7 @@ class RunnableMap(Serializable, Runnable[Input, Dict[str, Any]]):
|
||||
return create_model( # type: ignore[call-overload]
|
||||
"RunnableMapInput",
|
||||
**{
|
||||
k: (v.type_, v.default)
|
||||
k: (v.annotation, v.default)
|
||||
for step in self.steps.values()
|
||||
for k, v in step.input_schema.__fields__.items()
|
||||
if k != "__root__"
|
||||
@ -2374,7 +1946,7 @@ class RunnableLambda(Runnable[Input, Output]):
|
||||
return await super().ainvoke(input, config)
|
||||
|
||||
|
||||
class RunnableEach(Serializable, Runnable[List[Input], List[Output]]):
|
||||
class RunnableEach(RunnableSerializable[List[Input], List[Output]]):
|
||||
"""
|
||||
A runnable that delegates calls to another runnable
|
||||
with each element of the input sequence.
|
||||
@ -2413,6 +1985,11 @@ class RunnableEach(Serializable, Runnable[List[Input], List[Output]]):
|
||||
),
|
||||
)
|
||||
|
||||
def config_schema(
|
||||
self, *, include: Optional[Sequence[str]] = None
|
||||
) -> Type[BaseModel]:
|
||||
return self.bound.config_schema(include=include)
|
||||
|
||||
@classmethod
|
||||
def is_lc_serializable(cls) -> bool:
|
||||
return True
|
||||
@ -2455,7 +2032,7 @@ class RunnableEach(Serializable, Runnable[List[Input], List[Output]]):
|
||||
return await self._acall_with_config(self._ainvoke, input, config)
|
||||
|
||||
|
||||
class RunnableBinding(Serializable, Runnable[Input, Output]):
|
||||
class RunnableBinding(RunnableSerializable[Input, Output]):
|
||||
"""
|
||||
A runnable that delegates calls to another runnable with a set of kwargs.
|
||||
"""
|
||||
@ -2485,6 +2062,11 @@ class RunnableBinding(Serializable, Runnable[Input, Output]):
|
||||
def output_schema(self) -> Type[BaseModel]:
|
||||
return self.bound.output_schema
|
||||
|
||||
def config_schema(
|
||||
self, *, include: Optional[Sequence[str]] = None
|
||||
) -> Type[BaseModel]:
|
||||
return self.bound.config_schema(include=include)
|
||||
|
||||
@classmethod
|
||||
def is_lc_serializable(cls) -> bool:
|
||||
return True
|
||||
|
||||
235
libs/langchain/langchain/schema/runnable/branch.py
Normal file
235
libs/langchain/langchain/schema/runnable/branch.py
Normal file
@ -0,0 +1,235 @@
|
||||
from typing import (
|
||||
Any,
|
||||
Awaitable,
|
||||
Callable,
|
||||
List,
|
||||
Mapping,
|
||||
Optional,
|
||||
Sequence,
|
||||
Tuple,
|
||||
Type,
|
||||
Union,
|
||||
cast,
|
||||
)
|
||||
|
||||
from langchain.load.dump import dumpd
|
||||
from langchain.pydantic_v1 import BaseModel
|
||||
from langchain.schema.runnable.base import (
|
||||
Runnable,
|
||||
RunnableLike,
|
||||
RunnableSerializable,
|
||||
coerce_to_runnable,
|
||||
)
|
||||
from langchain.schema.runnable.config import (
|
||||
RunnableConfig,
|
||||
ensure_config,
|
||||
get_callback_manager_for_config,
|
||||
patch_config,
|
||||
)
|
||||
from langchain.schema.runnable.utils import Input, Output
|
||||
|
||||
|
||||
class RunnableBranch(RunnableSerializable[Input, Output]):
|
||||
"""A Runnable that selects which branch to run based on a condition.
|
||||
|
||||
The runnable is initialized with a list of (condition, runnable) pairs and
|
||||
a default branch.
|
||||
|
||||
When operating on an input, the first condition that evaluates to True is
|
||||
selected, and the corresponding runnable is run on the input.
|
||||
|
||||
If no condition evaluates to True, the default branch is run on the input.
|
||||
|
||||
Examples:
|
||||
|
||||
.. code-block:: python
|
||||
|
||||
from langchain.schema.runnable import RunnableBranch
|
||||
|
||||
branch = RunnableBranch(
|
||||
(lambda x: isinstance(x, str), lambda x: x.upper()),
|
||||
(lambda x: isinstance(x, int), lambda x: x + 1),
|
||||
(lambda x: isinstance(x, float), lambda x: x * 2),
|
||||
lambda x: "goodbye",
|
||||
)
|
||||
|
||||
branch.invoke("hello") # "HELLO"
|
||||
branch.invoke(None) # "goodbye"
|
||||
"""
|
||||
|
||||
branches: Sequence[Tuple[Runnable[Input, bool], Runnable[Input, Output]]]
|
||||
default: Runnable[Input, Output]
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
*branches: Union[
|
||||
Tuple[
|
||||
Union[
|
||||
Runnable[Input, bool],
|
||||
Callable[[Input], bool],
|
||||
Callable[[Input], Awaitable[bool]],
|
||||
],
|
||||
RunnableLike,
|
||||
],
|
||||
RunnableLike, # To accommodate the default branch
|
||||
],
|
||||
) -> None:
|
||||
"""A Runnable that runs one of two branches based on a condition."""
|
||||
if len(branches) < 2:
|
||||
raise ValueError("RunnableBranch requires at least two branches")
|
||||
|
||||
default = branches[-1]
|
||||
|
||||
if not isinstance(
|
||||
default, (Runnable, Callable, Mapping) # type: ignore[arg-type]
|
||||
):
|
||||
raise TypeError(
|
||||
"RunnableBranch default must be runnable, callable or mapping."
|
||||
)
|
||||
|
||||
default_ = cast(
|
||||
Runnable[Input, Output], coerce_to_runnable(cast(RunnableLike, default))
|
||||
)
|
||||
|
||||
_branches = []
|
||||
|
||||
for branch in branches[:-1]:
|
||||
if not isinstance(branch, (tuple, list)): # type: ignore[arg-type]
|
||||
raise TypeError(
|
||||
f"RunnableBranch branches must be "
|
||||
f"tuples or lists, not {type(branch)}"
|
||||
)
|
||||
|
||||
if not len(branch) == 2:
|
||||
raise ValueError(
|
||||
f"RunnableBranch branches must be "
|
||||
f"tuples or lists of length 2, not {len(branch)}"
|
||||
)
|
||||
condition, runnable = branch
|
||||
condition = cast(Runnable[Input, bool], coerce_to_runnable(condition))
|
||||
runnable = coerce_to_runnable(runnable)
|
||||
_branches.append((condition, runnable))
|
||||
|
||||
super().__init__(branches=_branches, default=default_)
|
||||
|
||||
class Config:
|
||||
arbitrary_types_allowed = True
|
||||
|
||||
@classmethod
|
||||
def is_lc_serializable(cls) -> bool:
|
||||
"""RunnableBranch is serializable if all its branches are serializable."""
|
||||
return True
|
||||
|
||||
@classmethod
|
||||
def get_lc_namespace(cls) -> List[str]:
|
||||
"""The namespace of a RunnableBranch is the namespace of its default branch."""
|
||||
return cls.__module__.split(".")[:-1]
|
||||
|
||||
@property
|
||||
def input_schema(self) -> Type[BaseModel]:
|
||||
runnables = (
|
||||
[self.default]
|
||||
+ [r for _, r in self.branches]
|
||||
+ [r for r, _ in self.branches]
|
||||
)
|
||||
|
||||
for runnable in runnables:
|
||||
if runnable.input_schema.schema().get("type") is not None:
|
||||
return runnable.input_schema
|
||||
|
||||
return super().input_schema
|
||||
|
||||
def invoke(
|
||||
self, input: Input, config: Optional[RunnableConfig] = None, **kwargs: Any
|
||||
) -> Output:
|
||||
"""First evaluates the condition, then delegate to true or false branch."""
|
||||
config = ensure_config(config)
|
||||
callback_manager = get_callback_manager_for_config(config)
|
||||
run_manager = callback_manager.on_chain_start(
|
||||
dumpd(self),
|
||||
input,
|
||||
name=config.get("run_name"),
|
||||
)
|
||||
|
||||
try:
|
||||
for idx, branch in enumerate(self.branches):
|
||||
condition, runnable = branch
|
||||
|
||||
expression_value = condition.invoke(
|
||||
input,
|
||||
config=patch_config(
|
||||
config,
|
||||
callbacks=run_manager.get_child(tag=f"condition:{idx + 1}"),
|
||||
),
|
||||
)
|
||||
|
||||
if expression_value:
|
||||
output = runnable.invoke(
|
||||
input,
|
||||
config=patch_config(
|
||||
config,
|
||||
callbacks=run_manager.get_child(tag=f"branch:{idx + 1}"),
|
||||
),
|
||||
**kwargs,
|
||||
)
|
||||
break
|
||||
else:
|
||||
output = self.default.invoke(
|
||||
input,
|
||||
config=patch_config(
|
||||
config, callbacks=run_manager.get_child(tag="branch:default")
|
||||
),
|
||||
**kwargs,
|
||||
)
|
||||
except Exception as e:
|
||||
run_manager.on_chain_error(e)
|
||||
raise
|
||||
run_manager.on_chain_end(dumpd(output))
|
||||
return output
|
||||
|
||||
async def ainvoke(
|
||||
self, input: Input, config: Optional[RunnableConfig] = None, **kwargs: Any
|
||||
) -> Output:
|
||||
"""Async version of invoke."""
|
||||
config = ensure_config(config)
|
||||
callback_manager = get_callback_manager_for_config(config)
|
||||
run_manager = callback_manager.on_chain_start(
|
||||
dumpd(self),
|
||||
input,
|
||||
name=config.get("run_name"),
|
||||
)
|
||||
try:
|
||||
for idx, branch in enumerate(self.branches):
|
||||
condition, runnable = branch
|
||||
|
||||
expression_value = await condition.ainvoke(
|
||||
input,
|
||||
config=patch_config(
|
||||
config,
|
||||
callbacks=run_manager.get_child(tag=f"condition:{idx + 1}"),
|
||||
),
|
||||
)
|
||||
|
||||
if expression_value:
|
||||
output = await runnable.ainvoke(
|
||||
input,
|
||||
config=patch_config(
|
||||
config,
|
||||
callbacks=run_manager.get_child(tag=f"branch:{idx + 1}"),
|
||||
),
|
||||
**kwargs,
|
||||
)
|
||||
break
|
||||
else:
|
||||
output = await self.default.ainvoke(
|
||||
input,
|
||||
config=patch_config(
|
||||
config, callbacks=run_manager.get_child(tag="branch:default")
|
||||
),
|
||||
**kwargs,
|
||||
)
|
||||
except Exception as e:
|
||||
run_manager.on_chain_error(e)
|
||||
raise
|
||||
run_manager.on_chain_end(dumpd(output))
|
||||
return output
|
||||
286
libs/langchain/langchain/schema/runnable/fallbacks.py
Normal file
286
libs/langchain/langchain/schema/runnable/fallbacks.py
Normal file
@ -0,0 +1,286 @@
|
||||
import asyncio
|
||||
from typing import (
|
||||
TYPE_CHECKING,
|
||||
Any,
|
||||
Iterator,
|
||||
List,
|
||||
Optional,
|
||||
Sequence,
|
||||
Tuple,
|
||||
Type,
|
||||
Union,
|
||||
)
|
||||
|
||||
from langchain.load.dump import dumpd
|
||||
from langchain.pydantic_v1 import BaseModel
|
||||
from langchain.schema.runnable.base import Runnable, RunnableSerializable
|
||||
from langchain.schema.runnable.config import (
|
||||
RunnableConfig,
|
||||
ensure_config,
|
||||
get_async_callback_manager_for_config,
|
||||
get_callback_manager_for_config,
|
||||
get_config_list,
|
||||
patch_config,
|
||||
)
|
||||
from langchain.schema.runnable.utils import Input, Output
|
||||
|
||||
if TYPE_CHECKING:
|
||||
from langchain.callbacks.manager import AsyncCallbackManagerForChainRun
|
||||
|
||||
|
||||
class RunnableWithFallbacks(RunnableSerializable[Input, Output]):
|
||||
"""
|
||||
A Runnable that can fallback to other Runnables if it fails.
|
||||
"""
|
||||
|
||||
runnable: Runnable[Input, Output]
|
||||
fallbacks: Sequence[Runnable[Input, Output]]
|
||||
exceptions_to_handle: Tuple[Type[BaseException], ...] = (Exception,)
|
||||
|
||||
class Config:
|
||||
arbitrary_types_allowed = True
|
||||
|
||||
@property
|
||||
def InputType(self) -> Type[Input]:
|
||||
return self.runnable.InputType
|
||||
|
||||
@property
|
||||
def OutputType(self) -> Type[Output]:
|
||||
return self.runnable.OutputType
|
||||
|
||||
@property
|
||||
def input_schema(self) -> Type[BaseModel]:
|
||||
return self.runnable.input_schema
|
||||
|
||||
@property
|
||||
def output_schema(self) -> Type[BaseModel]:
|
||||
return self.runnable.output_schema
|
||||
|
||||
def config_schema(
|
||||
self, *, include: Optional[Sequence[str]] = None
|
||||
) -> Type[BaseModel]:
|
||||
return self.runnable.config_schema(include=include)
|
||||
|
||||
@classmethod
|
||||
def is_lc_serializable(cls) -> bool:
|
||||
return True
|
||||
|
||||
@classmethod
|
||||
def get_lc_namespace(cls) -> List[str]:
|
||||
return cls.__module__.split(".")[:-1]
|
||||
|
||||
@property
|
||||
def runnables(self) -> Iterator[Runnable[Input, Output]]:
|
||||
yield self.runnable
|
||||
yield from self.fallbacks
|
||||
|
||||
def invoke(
|
||||
self, input: Input, config: Optional[RunnableConfig] = None, **kwargs: Any
|
||||
) -> Output:
|
||||
# setup callbacks
|
||||
config = ensure_config(config)
|
||||
callback_manager = get_callback_manager_for_config(config)
|
||||
# start the root run
|
||||
run_manager = callback_manager.on_chain_start(
|
||||
dumpd(self), input, name=config.get("run_name")
|
||||
)
|
||||
first_error = None
|
||||
for runnable in self.runnables:
|
||||
try:
|
||||
output = runnable.invoke(
|
||||
input,
|
||||
patch_config(config, callbacks=run_manager.get_child()),
|
||||
**kwargs,
|
||||
)
|
||||
except self.exceptions_to_handle as e:
|
||||
if first_error is None:
|
||||
first_error = e
|
||||
except BaseException as e:
|
||||
run_manager.on_chain_error(e)
|
||||
raise e
|
||||
else:
|
||||
run_manager.on_chain_end(output)
|
||||
return output
|
||||
if first_error is None:
|
||||
raise ValueError("No error stored at end of fallbacks.")
|
||||
run_manager.on_chain_error(first_error)
|
||||
raise first_error
|
||||
|
||||
async def ainvoke(
|
||||
self,
|
||||
input: Input,
|
||||
config: Optional[RunnableConfig] = None,
|
||||
**kwargs: Optional[Any],
|
||||
) -> Output:
|
||||
# setup callbacks
|
||||
config = ensure_config(config)
|
||||
callback_manager = get_async_callback_manager_for_config(config)
|
||||
# start the root run
|
||||
run_manager = await callback_manager.on_chain_start(
|
||||
dumpd(self), input, name=config.get("run_name")
|
||||
)
|
||||
|
||||
first_error = None
|
||||
for runnable in self.runnables:
|
||||
try:
|
||||
output = await runnable.ainvoke(
|
||||
input,
|
||||
patch_config(config, callbacks=run_manager.get_child()),
|
||||
**kwargs,
|
||||
)
|
||||
except self.exceptions_to_handle as e:
|
||||
if first_error is None:
|
||||
first_error = e
|
||||
except BaseException as e:
|
||||
await run_manager.on_chain_error(e)
|
||||
raise e
|
||||
else:
|
||||
await run_manager.on_chain_end(output)
|
||||
return output
|
||||
if first_error is None:
|
||||
raise ValueError("No error stored at end of fallbacks.")
|
||||
await run_manager.on_chain_error(first_error)
|
||||
raise first_error
|
||||
|
||||
def batch(
|
||||
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 CallbackManager
|
||||
|
||||
if return_exceptions:
|
||||
raise NotImplementedError()
|
||||
|
||||
if not inputs:
|
||||
return []
|
||||
|
||||
# setup callbacks
|
||||
configs = get_config_list(config, len(inputs))
|
||||
callback_managers = [
|
||||
CallbackManager.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 = [
|
||||
cm.on_chain_start(
|
||||
dumpd(self),
|
||||
input if isinstance(input, dict) else {"input": 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 = runnable.batch(
|
||||
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:
|
||||
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)
|
||||
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
|
||||
@ -16,9 +16,13 @@ from typing import (
|
||||
cast,
|
||||
)
|
||||
|
||||
from langchain.load.serializable import Serializable
|
||||
from langchain.pydantic_v1 import BaseModel, create_model
|
||||
from langchain.schema.runnable.base import Input, Runnable, RunnableMap
|
||||
from langchain.schema.runnable.base import (
|
||||
Input,
|
||||
Runnable,
|
||||
RunnableMap,
|
||||
RunnableSerializable,
|
||||
)
|
||||
from langchain.schema.runnable.config import RunnableConfig, get_executor_for_config
|
||||
from langchain.schema.runnable.utils import AddableDict
|
||||
from langchain.utils.aiter import atee, py_anext
|
||||
@ -33,7 +37,7 @@ async def aidentity(x: Input) -> Input:
|
||||
return x
|
||||
|
||||
|
||||
class RunnablePassthrough(Serializable, Runnable[Input, Input]):
|
||||
class RunnablePassthrough(RunnableSerializable[Input, Input]):
|
||||
"""
|
||||
A runnable that passes through the input.
|
||||
"""
|
||||
@ -109,7 +113,7 @@ class RunnablePassthrough(Serializable, Runnable[Input, Input]):
|
||||
yield chunk
|
||||
|
||||
|
||||
class RunnableAssign(Serializable, Runnable[Dict[str, Any], Dict[str, Any]]):
|
||||
class RunnableAssign(RunnableSerializable[Dict[str, Any], Dict[str, Any]]):
|
||||
"""
|
||||
A runnable that assigns key-value pairs to Dict[str, Any] inputs.
|
||||
"""
|
||||
|
||||
@ -14,8 +14,13 @@ from typing import (
|
||||
|
||||
from typing_extensions import TypedDict
|
||||
|
||||
from langchain.load.serializable import Serializable
|
||||
from langchain.schema.runnable.base import Input, Output, Runnable, coerce_to_runnable
|
||||
from langchain.schema.runnable.base import (
|
||||
Input,
|
||||
Output,
|
||||
Runnable,
|
||||
RunnableSerializable,
|
||||
coerce_to_runnable,
|
||||
)
|
||||
from langchain.schema.runnable.config import (
|
||||
RunnableConfig,
|
||||
get_config_list,
|
||||
@ -36,7 +41,7 @@ class RouterInput(TypedDict):
|
||||
input: Any
|
||||
|
||||
|
||||
class RouterRunnable(Serializable, Runnable[RouterInput, Output]):
|
||||
class RouterRunnable(RunnableSerializable[RouterInput, Output]):
|
||||
"""
|
||||
A runnable that routes to a set of runnables based on Input['key'].
|
||||
Returns the output of the selected runnable.
|
||||
|
||||
@ -17,6 +17,7 @@ from langchain.callbacks.manager import (
|
||||
CallbackManagerForToolRun,
|
||||
Callbacks,
|
||||
)
|
||||
from langchain.load.serializable import Serializable
|
||||
from langchain.pydantic_v1 import (
|
||||
BaseModel,
|
||||
Extra,
|
||||
@ -25,7 +26,7 @@ from langchain.pydantic_v1 import (
|
||||
root_validator,
|
||||
validate_arguments,
|
||||
)
|
||||
from langchain.schema.runnable import Runnable, RunnableConfig
|
||||
from langchain.schema.runnable import Runnable, RunnableConfig, RunnableSerializable
|
||||
|
||||
|
||||
class SchemaAnnotationError(TypeError):
|
||||
@ -97,7 +98,7 @@ class ToolException(Exception):
|
||||
pass
|
||||
|
||||
|
||||
class BaseTool(BaseModel, Runnable[Union[str, Dict], Any]):
|
||||
class BaseTool(RunnableSerializable[Union[str, Dict], Any]):
|
||||
"""Interface LangChain tools must implement."""
|
||||
|
||||
def __init_subclass__(cls, **kwargs: Any) -> None:
|
||||
@ -165,10 +166,9 @@ class ChildTool(BaseTool):
|
||||
] = False
|
||||
"""Handle the content of the ToolException thrown."""
|
||||
|
||||
class Config:
|
||||
class Config(Serializable.Config):
|
||||
"""Configuration for this pydantic object."""
|
||||
|
||||
extra = Extra.forbid
|
||||
arbitrary_types_allowed = True
|
||||
|
||||
@property
|
||||
|
||||
@ -2,7 +2,7 @@
|
||||
"""Tools for interacting with Spark SQL."""
|
||||
from typing import Any, Dict, Optional
|
||||
|
||||
from langchain.pydantic_v1 import BaseModel, Extra, Field, root_validator
|
||||
from langchain.pydantic_v1 import BaseModel, Field, root_validator
|
||||
|
||||
from langchain.schema.language_model import BaseLanguageModel
|
||||
from langchain.callbacks.manager import (
|
||||
@ -21,13 +21,8 @@ class BaseSparkSQLTool(BaseModel):
|
||||
|
||||
db: SparkSQL = Field(exclude=True)
|
||||
|
||||
# Override BaseTool.Config to appease mypy
|
||||
# See https://github.com/pydantic/pydantic/issues/4173
|
||||
class Config(BaseTool.Config):
|
||||
"""Configuration for this pydantic object."""
|
||||
|
||||
arbitrary_types_allowed = True
|
||||
extra = Extra.forbid
|
||||
pass
|
||||
|
||||
|
||||
class QuerySparkSQLTool(BaseSparkSQLTool, BaseTool):
|
||||
|
||||
@ -21,13 +21,8 @@ class BaseSQLDatabaseTool(BaseModel):
|
||||
|
||||
db: SQLDatabase = Field(exclude=True)
|
||||
|
||||
# Override BaseTool.Config to appease mypy
|
||||
# See https://github.com/pydantic/pydantic/issues/4173
|
||||
class Config(BaseTool.Config):
|
||||
"""Configuration for this pydantic object."""
|
||||
|
||||
arbitrary_types_allowed = True
|
||||
extra = Extra.forbid
|
||||
pass
|
||||
|
||||
|
||||
class QuerySQLDataBaseTool(BaseSQLDatabaseTool, BaseTool):
|
||||
|
||||
@ -18,9 +18,7 @@ class BaseVectorStoreTool(BaseModel):
|
||||
llm: BaseLanguageModel = Field(default_factory=lambda: OpenAI(temperature=0))
|
||||
|
||||
class Config(BaseTool.Config):
|
||||
"""Configuration for this pydantic object."""
|
||||
|
||||
arbitrary_types_allowed = True
|
||||
pass
|
||||
|
||||
|
||||
def _create_description_from_template(values: Dict[str, Any]) -> Dict[str, Any]:
|
||||
|
||||
Loading…
Reference in New Issue
Block a user