id stringlengths 14 15 | text stringlengths 44 2.47k | source stringlengths 61 181 |
|---|---|---|
b53d744c322d-2 | API.
Use this method when you want to:
1. take advantage of batched calls,
2. need more output from the model than just the top generated value,
3. are building chains that are agnostic to the underlying language model
type (e.g., pure text completion models v... | https://api.python.langchain.com/en/latest/_modules/langchain/schema/language_model.html |
b53d744c322d-3 | 3. are building chains that are agnostic to the underlying language model
type (e.g., pure text completion models vs chat models).
Args:
prompts: List of PromptValues. A PromptValue is an object that can be
converted to match the format of any language model (string f... | https://api.python.langchain.com/en/latest/_modules/langchain/schema/language_model.html |
b53d744c322d-4 | self,
messages: List[BaseMessage],
*,
stop: Optional[Sequence[str]] = None,
**kwargs: Any,
) -> BaseMessage:
"""Pass a message sequence to the model and return a message prediction.
Use this method when passing in chat messages. If you want to pass in raw text,
... | https://api.python.langchain.com/en/latest/_modules/langchain/schema/language_model.html |
b53d744c322d-5 | **kwargs: Any,
) -> BaseMessage:
"""Asynchronously pass messages to the model and return a message prediction.
Use this method when calling chat models and only the top
candidate generation is needed.
Args:
messages: A sequence of chat messages corresponding to a sing... | https://api.python.langchain.com/en/latest/_modules/langchain/schema/language_model.html |
b53d744c322d-6 | Returns:
The sum of the number of tokens across the messages.
"""
return sum([self.get_num_tokens(get_buffer_string([m])) for m in messages])
@classmethod
def _all_required_field_names(cls) -> Set:
"""DEPRECATED: Kept for backwards compatibility.
Use get_pydantic_fiel... | https://api.python.langchain.com/en/latest/_modules/langchain/schema/language_model.html |
8da700e74090-0 | Source code for langchain.schema.memory
from __future__ import annotations
from abc import ABC, abstractmethod
from typing import Any, Dict, List
from langchain.load.serializable import Serializable
[docs]class BaseMemory(Serializable, ABC):
"""Abstract base class for memory in Chains.
Memory refers to state in... | https://api.python.langchain.com/en/latest/_modules/langchain/schema/memory.html |
8da700e74090-1 | [docs] @abstractmethod
def save_context(self, inputs: Dict[str, Any], outputs: Dict[str, str]) -> None:
"""Save the context of this chain run to memory."""
[docs] @abstractmethod
def clear(self) -> None:
"""Clear memory contents.""" | https://api.python.langchain.com/en/latest/_modules/langchain/schema/memory.html |
aae63e68f0a5-0 | Source code for langchain.schema.exceptions
[docs]class LangChainException(Exception):
"""General LangChain exception.""" | https://api.python.langchain.com/en/latest/_modules/langchain/schema/exceptions.html |
5c1e9443c2ca-0 | Source code for langchain.schema.messages
from __future__ import annotations
from typing import TYPE_CHECKING, Any, Dict, List, Sequence, Union
from typing_extensions import Literal
from langchain.load.serializable import Serializable
from langchain.pydantic_v1 import Extra, Field
if TYPE_CHECKING:
from langchain.p... | https://api.python.langchain.com/en/latest/_modules/langchain/schema/messages.html |
5c1e9443c2ca-1 | else:
raise ValueError(f"Got unsupported message type: {m}")
message = f"{role}: {m.content}"
if isinstance(m, AIMessage) and "function_call" in m.additional_kwargs:
message += f"{m.additional_kwargs['function_call']}"
string_messages.append(message)
return "\n".join(... | https://api.python.langchain.com/en/latest/_modules/langchain/schema/messages.html |
5c1e9443c2ca-2 | " but with a different type."
)
elif isinstance(merged[k], str):
merged[k] += v
elif isinstance(merged[k], dict):
merged[k] = self._merge_kwargs_dict(merged[k], v)
else:
raise ValueError(
f"Additional... | https://api.python.langchain.com/en/latest/_modules/langchain/schema/messages.html |
5c1e9443c2ca-3 | """A Human Message chunk."""
# Ignoring mypy re-assignment here since we're overriding the value
# to make sure that the chunk variant can be discriminated from the
# non-chunk variant.
is_chunk: Literal[True] = True # type: ignore[assignment]
[docs]class AIMessage(BaseMessage):
"""A Message from a... | https://api.python.langchain.com/en/latest/_modules/langchain/schema/messages.html |
5c1e9443c2ca-4 | of input messages.
"""
type: Literal["system"] = "system"
is_chunk: Literal[False] = False
SystemMessage.update_forward_refs()
[docs]class SystemMessageChunk(SystemMessage, BaseMessageChunk):
"""A System Message chunk."""
# Ignoring mypy re-assignment here since we're overriding the value
# to m... | https://api.python.langchain.com/en/latest/_modules/langchain/schema/messages.html |
5c1e9443c2ca-5 | ),
)
return super().__add__(other)
[docs]class ChatMessage(BaseMessage):
"""A Message that can be assigned an arbitrary speaker (i.e. role)."""
role: str
"""The speaker / role of the Message."""
type: Literal["chat"] = "chat"
is_chunk: Literal[False] = False
ChatMessage.update_fo... | https://api.python.langchain.com/en/latest/_modules/langchain/schema/messages.html |
5c1e9443c2ca-6 | messages: Sequence of messages (as BaseMessages) to convert.
Returns:
List of messages as dicts.
"""
return [_message_to_dict(m) for m in messages]
def _message_from_dict(message: dict) -> BaseMessage:
_type = message["type"]
if _type == "human":
return HumanMessage(**message["data"]... | https://api.python.langchain.com/en/latest/_modules/langchain/schema/messages.html |
f6633f0700ad-0 | Source code for langchain.schema.output_parser
from __future__ import annotations
import asyncio
from abc import ABC, abstractmethod
from typing import (
Any,
AsyncIterator,
Dict,
Generic,
Iterator,
List,
Optional,
TypeVar,
Union,
)
from typing_extensions import get_args
from langcha... | https://api.python.langchain.com/en/latest/_modules/langchain/schema/output_parser.html |
f6633f0700ad-1 | """
return await asyncio.get_running_loop().run_in_executor(
None, self.parse_result, result
)
[docs]class BaseGenerationOutputParser(
BaseLLMOutputParser, Runnable[Union[str, BaseMessage], T]
):
"""Base class to parse the output of an LLM call."""
@property
def InputType(sel... | https://api.python.langchain.com/en/latest/_modules/langchain/schema/output_parser.html |
f6633f0700ad-2 | ),
input,
config,
run_type="parser",
)
else:
return await self._acall_with_config(
lambda inner_input: self.aparse_result([Generation(text=inner_input)]),
input,
config,
run_ty... | https://api.python.langchain.com/en/latest/_modules/langchain/schema/output_parser.html |
f6633f0700ad-3 | return type_args[0]
raise TypeError(
f"Runnable {self.__class__.__name__} doesn't have an inferable OutputType. "
"Override the OutputType property to specify the output type."
)
[docs] def invoke(
self, input: Union[str, BaseMessage], config: Optional[RunnableConfig] ... | https://api.python.langchain.com/en/latest/_modules/langchain/schema/output_parser.html |
f6633f0700ad-4 | """Parse a list of candidate model Generations into a specific format.
The return value is parsed from only the first Generation in the result, which
is assumed to be the highest-likelihood Generation.
Args:
result: A list of Generations to be parsed. The Generations are assumed
... | https://api.python.langchain.com/en/latest/_modules/langchain/schema/output_parser.html |
f6633f0700ad-5 | # TODO: rename 'completion' -> 'text'.
[docs] def parse_with_prompt(self, completion: str, prompt: PromptValue) -> Any:
"""Parse the output of an LLM call with the input prompt for context.
The prompt is largely provided in the event the OutputParser wants
to retry or fix the output in some w... | https://api.python.langchain.com/en/latest/_modules/langchain/schema/output_parser.html |
f6633f0700ad-6 | async def _atransform(
self, input: AsyncIterator[Union[str, BaseMessage]]
) -> AsyncIterator[T]:
async for chunk in input:
if isinstance(chunk, BaseMessage):
yield self.parse_result([ChatGeneration(message=chunk)])
else:
yield self.parse_resul... | https://api.python.langchain.com/en/latest/_modules/langchain/schema/output_parser.html |
f6633f0700ad-7 | prev_parsed = None
acc_gen = None
for chunk in input:
if isinstance(chunk, BaseMessageChunk):
chunk_gen: Generation = ChatGenerationChunk(message=chunk)
elif isinstance(chunk, BaseMessage):
chunk_gen = ChatGenerationChunk(
messa... | https://api.python.langchain.com/en/latest/_modules/langchain/schema/output_parser.html |
f6633f0700ad-8 | prev_parsed = parsed
[docs]class StrOutputParser(BaseTransformOutputParser[str]):
"""OutputParser that parses LLMResult into the top likely string."""
[docs] @classmethod
def is_lc_serializable(cls) -> bool:
"""Return whether this class is serializable."""
return True
@property
def _t... | https://api.python.langchain.com/en/latest/_modules/langchain/schema/output_parser.html |
f6633f0700ad-9 | llm_output: Optional[str] = None,
send_to_llm: bool = False,
):
super(OutputParserException, self).__init__(error)
if send_to_llm:
if observation is None or llm_output is None:
raise ValueError(
"Arguments 'observation' & 'llm_output'"
... | https://api.python.langchain.com/en/latest/_modules/langchain/schema/output_parser.html |
f96abcb35f96-0 | Source code for langchain.schema.agent
from __future__ import annotations
from typing import Any, Sequence, Union
from langchain.load.serializable import Serializable
from langchain.schema.messages import BaseMessage
[docs]class AgentAction(Serializable):
"""A full description of an action for an ActionAgent to exe... | https://api.python.langchain.com/en/latest/_modules/langchain/schema/agent.html |
f96abcb35f96-1 | if (tool, tool_input) cannot be used to fully recreate the LLM
prediction, and you need that LLM prediction (for future agent iteration).
Compared to `log`, this is useful when the underlying LLM is a
ChatModel (and therefore returns messages rather than a string)."""
[docs]class AgentFinish(Serializable):
... | https://api.python.langchain.com/en/latest/_modules/langchain/schema/agent.html |
96f1f2c2cc5d-0 | Source code for langchain.schema.output
from __future__ import annotations
from copy import deepcopy
from typing import Any, Dict, List, Optional
from uuid import UUID
from langchain.load.serializable import Serializable
from langchain.pydantic_v1 import BaseModel, root_validator
from langchain.schema.messages import B... | https://api.python.langchain.com/en/latest/_modules/langchain/schema/output.html |
96f1f2c2cc5d-1 | """*SHOULD NOT BE SET DIRECTLY* The text contents of the output message."""
message: BaseMessage
"""The message output by the chat model."""
@root_validator
def set_text(cls, values: Dict[str, Any]) -> Dict[str, Any]:
"""Set the text attribute to be the contents of the message."""
values... | https://api.python.langchain.com/en/latest/_modules/langchain/schema/output.html |
96f1f2c2cc5d-2 | candidate generations.
"""
llm_output: Optional[dict] = None
"""For arbitrary LLM provider specific output."""
[docs]class LLMResult(BaseModel):
"""Class that contains all results for a batched LLM call."""
generations: List[List[Generation]]
"""List of generated outputs. This is a List[List[]] ... | https://api.python.langchain.com/en/latest/_modules/langchain/schema/output.html |
96f1f2c2cc5d-3 | else:
llm_output = None
llm_results.append(
LLMResult(
generations=[gen_list],
llm_output=llm_output,
)
)
return llm_results
def __eq__(self, other: object) -> bool:
... | https://api.python.langchain.com/en/latest/_modules/langchain/schema/output.html |
bfdbb8d0d23e-0 | Source code for langchain.schema.storage
from abc import ABC, abstractmethod
from typing import Generic, Iterator, List, Optional, Sequence, Tuple, TypeVar, Union
K = TypeVar("K")
V = TypeVar("V")
[docs]class BaseStore(Generic[K, V], ABC):
"""Abstract interface for a key-value store."""
[docs] @abstractmethod
... | https://api.python.langchain.com/en/latest/_modules/langchain/schema/storage.html |
bfdbb8d0d23e-1 | This method is allowed to return an iterator over either K or str
depending on what makes more sense for the given store.
""" | https://api.python.langchain.com/en/latest/_modules/langchain/schema/storage.html |
987889cf40c7-0 | Source code for langchain.schema.runnable.utils
from __future__ import annotations
import ast
import asyncio
import inspect
import textwrap
from inspect import signature
from typing import (
Any,
AsyncIterable,
Callable,
Coroutine,
Dict,
Iterable,
List,
Optional,
Protocol,
Set,
... | https://api.python.langchain.com/en/latest/_modules/langchain/schema/runnable/utils.html |
987889cf40c7-1 | [docs] def visit_Subscript(self, node: ast.Subscript) -> Any:
if (
isinstance(node.ctx, ast.Load)
and isinstance(node.value, ast.Name)
and node.value.id == self.name
and isinstance(node.slice, ast.Constant)
and isinstance(node.slice.value, str)
... | https://api.python.langchain.com/en/latest/_modules/langchain/schema/runnable/utils.html |
987889cf40c7-2 | input_arg_name = node.args.args[0].arg
IsLocalDict(input_arg_name, self.keys).visit(node)
[docs]class GetLambdaSource(ast.NodeVisitor):
[docs] def __init__(self) -> None:
self.source: Optional[str] = None
self.count = 0
[docs] def visit_Lambda(self, node: ast.Lambda) -> Any:
self.c... | https://api.python.langchain.com/en/latest/_modules/langchain/schema/runnable/utils.html |
987889cf40c7-3 | prefix: Used to determine the number of spaces to indent
Returns:
str: The indented text
"""
n_spaces = len(prefix)
spaces = " " * n_spaces
lines = text.splitlines()
return "\n".join([lines[0]] + [spaces + line for line in lines[1:]])
[docs]class AddableDict(Dict[str, Any]):
"""
... | https://api.python.langchain.com/en/latest/_modules/langchain/schema/runnable/utils.html |
987889cf40c7-4 | final = None
for chunk in addables:
if final is None:
final = chunk
else:
final = final + chunk
return final
[docs]async def aadd(addables: AsyncIterable[Addable]) -> Optional[Addable]:
final = None
async for chunk in addables:
if final is None:
... | https://api.python.langchain.com/en/latest/_modules/langchain/schema/runnable/utils.html |
c7f123e88049-0 | Source code for langchain.schema.runnable.router
from __future__ import annotations
from typing import (
Any,
AsyncIterator,
Callable,
Iterator,
List,
Mapping,
Optional,
Union,
cast,
)
from typing_extensions import TypedDict
from langchain.load.serializable import Serializable
from l... | https://api.python.langchain.com/en/latest/_modules/langchain/schema/runnable/router.html |
c7f123e88049-1 | [docs] @classmethod
def get_lc_namespace(cls) -> List[str]:
return cls.__module__.split(".")[:-1]
[docs] def invoke(
self, input: RouterInput, config: Optional[RunnableConfig] = None
) -> Output:
key = input["key"]
actual_input = input["input"]
if key not in self.ru... | https://api.python.langchain.com/en/latest/_modules/langchain/schema/runnable/router.html |
c7f123e88049-2 | def invoke(
runnable: Runnable, input: Input, config: RunnableConfig
) -> Union[Output, Exception]:
if return_exceptions:
try:
return runnable.invoke(input, config, **kwargs)
except Exception as e:
return e
... | https://api.python.langchain.com/en/latest/_modules/langchain/schema/runnable/router.html |
c7f123e88049-3 | else:
return await runnable.ainvoke(input, config, **kwargs)
runnables = [self.runnables[key] for key in keys]
configs = get_config_list(config, len(inputs))
return await gather_with_concurrency(
configs[0].get("max_concurrency"),
*(
ainvok... | https://api.python.langchain.com/en/latest/_modules/langchain/schema/runnable/router.html |
7d486a4a793f-0 | Source code for langchain.schema.runnable.passthrough
from __future__ import annotations
import asyncio
import threading
from typing import (
Any,
AsyncIterator,
Callable,
Dict,
Iterator,
List,
Mapping,
Optional,
Type,
Union,
cast,
)
from langchain.load.serializable import Se... | https://api.python.langchain.com/en/latest/_modules/langchain/schema/runnable/passthrough.html |
7d486a4a793f-1 | Callable[[Dict[str, Any]], Any],
Mapping[
str,
Union[Runnable[Dict[str, Any], Any], Callable[[Dict[str, Any]], Any]],
],
],
) -> RunnableAssign:
"""
Merge the Dict input with the output produced by the mapping argument.
Args:
... | https://api.python.langchain.com/en/latest/_modules/langchain/schema/runnable/passthrough.html |
7d486a4a793f-2 | """
A runnable that assigns key-value pairs to Dict[str, Any] inputs.
"""
mapper: RunnableMap[Dict[str, Any]]
def __init__(self, mapper: RunnableMap[Dict[str, Any]], **kwargs: Any) -> None:
super().__init__(mapper=mapper, **kwargs)
[docs] @classmethod
def is_lc_serializable(cls) -> bool:
... | https://api.python.langchain.com/en/latest/_modules/langchain/schema/runnable/passthrough.html |
7d486a4a793f-3 | ) -> Dict[str, Any]:
assert isinstance(input, dict)
return {
**input,
**self.mapper.invoke(input, config, **kwargs),
}
[docs] async def ainvoke(
self,
input: Dict[str, Any],
config: Optional[RunnableConfig] = None,
**kwargs: Any,
) -... | https://api.python.langchain.com/en/latest/_modules/langchain/schema/runnable/passthrough.html |
7d486a4a793f-4 | )
if filtered:
yield filtered
# yield map output
yield cast(Dict[str, Any], first_map_chunk_future.result())
for chunk in map_output:
yield chunk
[docs] async def atransform(
self,
input: AsyncIterator[Dict[str, A... | https://api.python.langchain.com/en/latest/_modules/langchain/schema/runnable/passthrough.html |
7d486a4a793f-5 | **kwargs: Any,
) -> Iterator[Dict[str, Any]]:
return self.transform(iter([input]), config, **kwargs)
[docs] async def astream(
self,
input: Dict[str, Any],
config: Optional[RunnableConfig] = None,
**kwargs: Any,
) -> AsyncIterator[Dict[str, Any]]:
async def inp... | https://api.python.langchain.com/en/latest/_modules/langchain/schema/runnable/passthrough.html |
1a9f57e4a012-0 | Source code for langchain.schema.runnable.retry
from typing import (
TYPE_CHECKING,
Any,
Dict,
List,
Optional,
Tuple,
Type,
TypeVar,
Union,
cast,
)
from tenacity import (
AsyncRetrying,
RetryCallState,
RetryError,
Retrying,
retry_if_exception_type,
stop_af... | https://api.python.langchain.com/en/latest/_modules/langchain/schema/runnable/retry.html |
1a9f57e4a012-1 | def _sync_retrying(self, **kwargs: Any) -> Retrying:
return Retrying(**self._kwargs_retrying, **kwargs)
def _async_retrying(self, **kwargs: Any) -> AsyncRetrying:
return AsyncRetrying(**self._kwargs_retrying, **kwargs)
def _patch_config(
self,
config: RunnableConfig,
run_... | https://api.python.langchain.com/en/latest/_modules/langchain/schema/runnable/retry.html |
1a9f57e4a012-2 | ) -> Output:
return self._call_with_config(self._invoke, input, config, **kwargs)
async def _ainvoke(
self,
input: Input,
run_manager: "AsyncCallbackManagerForChainRun",
config: RunnableConfig,
) -> Output:
async for attempt in self._async_retrying(reraise=True):
... | https://api.python.langchain.com/en/latest/_modules/langchain/schema/runnable/retry.html |
1a9f57e4a012-3 | ),
return_exceptions=True,
)
# Register the results of the inputs that have succeeded.
first_exception = None
for i, r in enumerate(result):
if isinstance(r, Exception):
... | https://api.python.langchain.com/en/latest/_modules/langchain/schema/runnable/retry.html |
1a9f57e4a012-4 | results_map: Dict[int, Output] = {}
def pending(iterable: List[U]) -> List[U]:
return [item for idx, item in enumerate(iterable) if idx not in results_map]
try:
async for attempt in self._async_retrying():
with attempt:
# Get the results of the... | https://api.python.langchain.com/en/latest/_modules/langchain/schema/runnable/retry.html |
1a9f57e4a012-5 | *,
return_exceptions: bool = False,
**kwargs: Any
) -> List[Output]:
return await self._abatch_with_config(
self._abatch, inputs, config, return_exceptions=return_exceptions, **kwargs
)
# stream() and transform() are not retried because retrying a stream
# is not ... | https://api.python.langchain.com/en/latest/_modules/langchain/schema/runnable/retry.html |
6b75ba941317-0 | Source code for langchain.schema.runnable.base
from __future__ import annotations
import asyncio
import inspect
import threading
from abc import ABC, abstractmethod
from concurrent.futures import FIRST_COMPLETED, wait
from functools import partial
from itertools import tee
from operator import itemgetter
from typing im... | https://api.python.langchain.com/en/latest/_modules/langchain/schema/runnable/base.html |
6b75ba941317-1 | from langchain.utils.iter import safetee
Other = TypeVar("Other")
[docs]class Runnable(Generic[Input, Output], ABC):
"""A Runnable is a unit of work that can be invoked, batched, streamed, or
transformed."""
@property
def InputType(self) -> Type[Input]:
for cls in self.__class__.__orig_bases__: ... | https://api.python.langchain.com/en/latest/_modules/langchain/schema/runnable/base.html |
6b75ba941317-2 | root_type = self.OutputType
if inspect.isclass(root_type) and issubclass(root_type, BaseModel):
return root_type
return create_model(
self.__class__.__name__ + "Output", __root__=(root_type, None)
)
def __or__(
self,
other: Union[
Runnable[... | https://api.python.langchain.com/en/latest/_modules/langchain/schema/runnable/base.html |
6b75ba941317-3 | None, partial(self.invoke, **kwargs), input, config
)
[docs] def batch(
self,
inputs: List[Input],
config: Optional[Union[RunnableConfig, List[RunnableConfig]]] = None,
*,
return_exceptions: bool = False,
**kwargs: Optional[Any],
) -> List[Output]:
... | https://api.python.langchain.com/en/latest/_modules/langchain/schema/runnable/base.html |
6b75ba941317-4 | Subclasses should override this method if they can batch more efficiently.
"""
if not inputs:
return []
configs = get_config_list(config, len(inputs))
async def ainvoke(
input: Input, config: RunnableConfig
) -> Union[Output, Exception]:
if ret... | https://api.python.langchain.com/en/latest/_modules/langchain/schema/runnable/base.html |
6b75ba941317-5 | *,
include_names: Optional[Sequence[str]] = None,
include_types: Optional[Sequence[str]] = None,
include_tags: Optional[Sequence[str]] = None,
exclude_names: Optional[Sequence[str]] = None,
exclude_types: Optional[Sequence[str]] = None,
exclude_tags: Optional[Sequence[str... | https://api.python.langchain.com/en/latest/_modules/langchain/schema/runnable/base.html |
6b75ba941317-6 | elif isinstance(callbacks, BaseCallbackManager):
callbacks = callbacks.copy()
callbacks.inheritable_handlers.append(stream)
config["callbacks"] = callbacks
else:
raise ValueError(
f"Unexpected type for callbacks: {callbacks}."
"Expe... | https://api.python.langchain.com/en/latest/_modules/langchain/schema/runnable/base.html |
6b75ba941317-7 | final: Input
got_first_val = False
for chunk in input:
if not got_first_val:
final = chunk
got_first_val = True
else:
# Make a best effort to gather, for any type that supports `+`
# This method should throw an error... | https://api.python.langchain.com/en/latest/_modules/langchain/schema/runnable/base.html |
6b75ba941317-8 | [docs] def with_config(
self,
config: Optional[RunnableConfig] = None,
# Sadly Unpack is not well supported by mypy so this will have to be untyped
**kwargs: Any,
) -> Runnable[Input, Output]:
"""
Bind config to a Runnable, returning a new Runnable.
"""
... | https://api.python.langchain.com/en/latest/_modules/langchain/schema/runnable/base.html |
6b75ba941317-9 | runnable=self,
fallbacks=fallbacks,
exceptions_to_handle=exceptions_to_handle,
)
""" --- Helper methods for Subclasses --- """
def _call_with_config(
self,
func: Union[
Callable[[Input], Output],
Callable[[Input, CallbackManagerForChainRun]... | https://api.python.langchain.com/en/latest/_modules/langchain/schema/runnable/base.html |
6b75ba941317-10 | ],
input: Input,
config: Optional[RunnableConfig],
run_type: Optional[str] = None,
**kwargs: Optional[Any],
) -> Output:
"""Helper method to transform an Input value to an Output value,
with callbacks. Use this method to implement ainvoke() in subclasses."""
c... | https://api.python.langchain.com/en/latest/_modules/langchain/schema/runnable/base.html |
6b75ba941317-11 | """Helper method to transform an Input value to an Output value,
with callbacks. Use this method to implement invoke() in subclasses."""
if not input:
return []
configs = get_config_list(config, len(input))
callback_managers = [get_callback_manager_for_config(c) for c in conf... | https://api.python.langchain.com/en/latest/_modules/langchain/schema/runnable/base.html |
6b75ba941317-12 | else:
raise first_exception
async def _abatch_with_config(
self,
func: Union[
Callable[[List[Input]], Awaitable[List[Union[Exception, Output]]]],
Callable[
[List[Input], List[AsyncCallbackManagerForChainRun]],
Awaitable[List[Uni... | https://api.python.langchain.com/en/latest/_modules/langchain/schema/runnable/base.html |
6b75ba941317-13 | kwargs["config"] = [
patch_config(c, callbacks=rm.get_child())
for c, rm in zip(configs, run_managers)
]
if accepts_run_manager(func):
kwargs["run_manager"] = run_managers
output = await func(input, **kwargs) # type: ignore... | https://api.python.langchain.com/en/latest/_modules/langchain/schema/runnable/base.html |
6b75ba941317-14 | run_type: Optional[str] = None,
**kwargs: Optional[Any],
) -> Iterator[Output]:
"""Helper method to transform an Iterator of Input values into an Iterator of
Output values, with callbacks.
Use this to implement `stream()` or `transform()` in Runnable subclasses."""
# tee the ... | https://api.python.langchain.com/en/latest/_modules/langchain/schema/runnable/base.html |
6b75ba941317-15 | for ichunk in input_for_tracing:
if final_input_supported:
if final_input is None:
final_input = ichunk
else:
try:
final_input = final_input + ichunk # type: ignore
... | https://api.python.langchain.com/en/latest/_modules/langchain/schema/runnable/base.html |
6b75ba941317-16 | final_input_supported = True
final_output: Optional[Output] = None
final_output_supported = True
config = ensure_config(config)
callback_manager = get_async_callback_manager_for_config(config)
run_manager = await callback_manager.on_chain_start(
dumpd(self),
... | https://api.python.langchain.com/en/latest/_modules/langchain/schema/runnable/base.html |
6b75ba941317-17 | [docs]class RunnableBranch(Serializable, Runnable[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
... | https://api.python.langchain.com/en/latest/_modules/langchain/schema/runnable/base.html |
6b75ba941317-18 | 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... | https://api.python.langchain.com/en/latest/_modules/langchain/schema/runnable/base.html |
6b75ba941317-19 | 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_s... | https://api.python.langchain.com/en/latest/_modules/langchain/schema/runnable/base.html |
6b75ba941317-20 | return output
[docs] 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_m... | https://api.python.langchain.com/en/latest/_modules/langchain/schema/runnable/base.html |
6b75ba941317-21 | 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[Outpu... | https://api.python.langchain.com/en/latest/_modules/langchain/schema/runnable/base.html |
6b75ba941317-22 | 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... | https://api.python.langchain.com/en/latest/_modules/langchain/schema/runnable/base.html |
6b75ba941317-23 | [docs] 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
... | https://api.python.langchain.com/en/latest/_modules/langchain/schema/runnable/base.html |
6b75ba941317-24 | 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
... | https://api.python.langchain.com/en/latest/_modules/langchain/schema/runnable/base.html |
6b75ba941317-25 | )
)
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, ca... | https://api.python.langchain.com/en/latest/_modules/langchain/schema/runnable/base.html |
6b75ba941317-26 | return True
[docs] @classmethod
def get_lc_namespace(cls) -> List[str]:
return cls.__module__.split(".")[:-1]
class Config:
arbitrary_types_allowed = True
@property
def InputType(self) -> Type[Input]:
return self.first.InputType
@property
def OutputType(self) -> Type[O... | https://api.python.langchain.com/en/latest/_modules/langchain/schema/runnable/base.html |
6b75ba941317-27 | Runnable[Other, Any],
Callable[[Other], Any],
Callable[[Iterator[Other]], Iterator[Any]],
Mapping[str, Union[Runnable[Other, Any], Callable[[Other], Any], Any]],
],
) -> RunnableSequence[Other, Output]:
if isinstance(other, RunnableSequence):
return Ru... | https://api.python.langchain.com/en/latest/_modules/langchain/schema/runnable/base.html |
6b75ba941317-28 | 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_man... | https://api.python.langchain.com/en/latest/_modules/langchain/schema/runnable/base.html |
6b75ba941317-29 | 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,
name=config... | https://api.python.langchain.com/en/latest/_modules/langchain/schema/runnable/base.html |
6b75ba941317-30 | for i, inp in zip(remaining_idxs, inputs):
if isinstance(inp, Exception):
failed_inputs_map[i] = inp
inputs = [inp for inp in inputs if not isinstance(inp, Exception)]
# If all inputs have failed, stop processing
... | https://api.python.langchain.com/en/latest/_modules/langchain/schema/runnable/base.html |
6b75ba941317-31 | return cast(List[Output], inputs)
else:
raise first_exception
[docs] async def abatch(
self,
inputs: List[Input],
config: Optional[Union[RunnableConfig, List[RunnableConfig]]] = None,
*,
return_exceptions: bool = False,
**kwargs: Optional[An... | https://api.python.langchain.com/en/latest/_modules/langchain/schema/runnable/base.html |
6b75ba941317-32 | failed_inputs_map: Dict[int, Exception] = {}
for stepidx, step in enumerate(self.steps):
# Assemble the original indexes of the remaining inputs
# (i.e. the ones that haven't failed yet)
remaining_idxs = [
i for i in ran... | https://api.python.langchain.com/en/latest/_modules/langchain/schema/runnable/base.html |
6b75ba941317-33 | else:
for i, step in enumerate(self.steps):
inputs = await step.abatch(
inputs,
[
# each step a child run of the corresponding root run
patch_config(
... | https://api.python.langchain.com/en/latest/_modules/langchain/schema/runnable/base.html |
6b75ba941317-34 | # buffer input in memory until all available, and then start emitting output
final_pipeline = cast(Iterator[Output], input)
for step in steps:
final_pipeline = step.transform(
final_pipeline,
patch_config(
config,
callba... | https://api.python.langchain.com/en/latest/_modules/langchain/schema/runnable/base.html |
6b75ba941317-35 | [docs] def stream(
self,
input: Input,
config: Optional[RunnableConfig] = None,
**kwargs: Optional[Any],
) -> Iterator[Output]:
yield from self.transform(iter([input]), config, **kwargs)
[docs] async def atransform(
self,
input: AsyncIterator[Input],
... | https://api.python.langchain.com/en/latest/_modules/langchain/schema/runnable/base.html |
6b75ba941317-36 | ],
],
) -> None:
super().__init__(steps={key: coerce_to_runnable(r) for key, r in steps.items()})
[docs] @classmethod
def is_lc_serializable(cls) -> bool:
return True
[docs] @classmethod
def get_lc_namespace(cls) -> List[str]:
return cls.__module__.split(".")[:-1]
c... | https://api.python.langchain.com/en/latest/_modules/langchain/schema/runnable/base.html |
6b75ba941317-37 | )
def __repr__(self) -> str:
map_for_repr = ",\n ".join(
f"{k}: {indent_lines_after_first(repr(v), ' ' + k + ': ')}"
for k, v in self.steps.items()
)
return "{\n " + map_for_repr + "\n}"
[docs] def invoke(
self, input: Input, config: Optional[RunnableCon... | https://api.python.langchain.com/en/latest/_modules/langchain/schema/runnable/base.html |
6b75ba941317-38 | # finish the root run
except BaseException as e:
run_manager.on_chain_error(e)
raise
else:
run_manager.on_chain_end(output)
return output
[docs] async def ainvoke(
self,
input: Input,
config: Optional[RunnableConfig] = None,
... | https://api.python.langchain.com/en/latest/_modules/langchain/schema/runnable/base.html |
6b75ba941317-39 | steps = dict(self.steps)
# Each step gets a copy of the input iterator,
# which is consumed in parallel in a separate thread.
input_copies = list(safetee(input, len(steps), lock=threading.Lock()))
with get_executor_for_config(config) as executor:
# Create the transform() gene... | https://api.python.langchain.com/en/latest/_modules/langchain/schema/runnable/base.html |
6b75ba941317-40 | yield from self._transform_stream_with_config(
input, self._transform, config, **kwargs
)
[docs] def stream(
self,
input: Input,
config: Optional[RunnableConfig] = None,
**kwargs: Optional[Any],
) -> Iterator[Dict[str, Any]]:
yield from self.transform(i... | https://api.python.langchain.com/en/latest/_modules/langchain/schema/runnable/base.html |
6b75ba941317-41 | # and start the next iteration of the generator that yielded it.
# When all generators are exhausted, stop.
while tasks:
completed_tasks, _ = await asyncio.wait(
tasks, return_when=asyncio.FIRST_COMPLETED
)
for task in completed_tasks:
... | https://api.python.langchain.com/en/latest/_modules/langchain/schema/runnable/base.html |
6b75ba941317-42 | Callable[[AsyncIterator[Input]], AsyncIterator[Output]],
],
atransform: Optional[
Callable[[AsyncIterator[Input]], AsyncIterator[Output]]
] = None,
) -> None:
if atransform is not None:
self._atransform = atransform
if inspect.isasyncgenfunction(transf... | https://api.python.langchain.com/en/latest/_modules/langchain/schema/runnable/base.html |
6b75ba941317-43 | return self._transform == other._transform
elif hasattr(self, "_atransform") and hasattr(other, "_atransform"):
return self._atransform == other._atransform
else:
return False
else:
return False
def __repr__(self) -> str:
return "Ru... | https://api.python.langchain.com/en/latest/_modules/langchain/schema/runnable/base.html |
6b75ba941317-44 | input, self._atransform, config, **kwargs
)
[docs] def astream(
self,
input: Input,
config: Optional[RunnableConfig] = None,
**kwargs: Any,
) -> AsyncIterator[Output]:
async def input_aiter() -> AsyncIterator[Input]:
yield input
return self.atra... | https://api.python.langchain.com/en/latest/_modules/langchain/schema/runnable/base.html |
6b75ba941317-45 | )
@property
def InputType(self) -> Any:
func = getattr(self, "func", None) or getattr(self, "afunc")
try:
params = inspect.signature(func).parameters
first_param = next(iter(params.values()), None)
if first_param and first_param.annotation != inspect.Parameter... | https://api.python.langchain.com/en/latest/_modules/langchain/schema/runnable/base.html |
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