id stringlengths 14 16 | text stringlengths 13 2.7k | source stringlengths 57 178 |
|---|---|---|
0597fd79f5a2-2 | Default implementation runs ainvoke in parallel using asyncio.gather.
The default implementation of batch works well for IO bound runnables.
Subclasses should override this method if they can batch more efficiently;
e.g., if the underlying runnable uses an API which supports a batch mode.
async ainvoke(input: Input, co... | lang/api.python.langchain.com/en/latest/schema.runnable/langchain.schema.runnable.retry.RunnableRetry.html |
0597fd79f5a2-3 | The jsonpatch ops can be applied in order to construct state.
async atransform(input: AsyncIterator[Input], config: Optional[RunnableConfig] = None, **kwargs: Any) → AsyncIterator[Output]¶
Default implementation of atransform, which buffers input and calls astream.
Subclasses should override this method if they can sta... | lang/api.python.langchain.com/en/latest/schema.runnable/langchain.schema.runnable.retry.RunnableRetry.html |
0597fd79f5a2-4 | classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) → Model¶
Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data.
Default values are respected, but no other validation is performed.
Behaves as if Config.extra = ‘allow’ was set since it adds all passed values... | lang/api.python.langchain.com/en/latest/schema.runnable/langchain.schema.runnable.retry.RunnableRetry.html |
0597fd79f5a2-5 | Get a pydantic model that can be used to validate input to the runnable.
Runnables that leverage the configurable_fields and configurable_alternatives
methods will have a dynamic input schema that depends on which
configuration the runnable is invoked with.
This method allows to get an input schema for a specific confi... | lang/api.python.langchain.com/en/latest/schema.runnable/langchain.schema.runnable.retry.RunnableRetry.html |
0597fd79f5a2-6 | Returns
The output of the runnable.
classmethod is_lc_serializable() → bool¶
Is this class serializable?
json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclu... | lang/api.python.langchain.com/en/latest/schema.runnable/langchain.schema.runnable.retry.RunnableRetry.html |
0597fd79f5a2-7 | classmethod schema_json(*, by_alias: bool = True, ref_template: unicode = '#/definitions/{model}', **dumps_kwargs: Any) → unicode¶
stream(input: Input, config: Optional[RunnableConfig] = None, **kwargs: Optional[Any]) → Iterator[Output]¶
Default implementation of stream, which calls invoke.
Subclasses should override t... | lang/api.python.langchain.com/en/latest/schema.runnable/langchain.schema.runnable.retry.RunnableRetry.html |
0597fd79f5a2-8 | fallback in order, upon failures.
with_listeners(*, on_start: Optional[Listener] = None, on_end: Optional[Listener] = None, on_error: Optional[Listener] = None) → Runnable[Input, Output]¶
Bind lifecycle listeners to a Runnable, returning a new Runnable.
on_start: Called before the runnable starts running, with the Run ... | lang/api.python.langchain.com/en/latest/schema.runnable/langchain.schema.runnable.retry.RunnableRetry.html |
0597fd79f5a2-9 | The type of output this runnable produces specified as a type annotation.
property config_specs: List[langchain.schema.runnable.utils.ConfigurableFieldSpec]¶
List configurable fields for this runnable.
property input_schema: Type[pydantic.main.BaseModel]¶
The type of input this runnable accepts specified as a pydantic ... | lang/api.python.langchain.com/en/latest/schema.runnable/langchain.schema.runnable.retry.RunnableRetry.html |
c957e6bc73a3-0 | langchain.schema.runnable.config.get_callback_manager_for_config¶
langchain.schema.runnable.config.get_callback_manager_for_config(config: RunnableConfig) → CallbackManager[source]¶
Get a callback manager for a config.
Parameters
config (RunnableConfig) – The config.
Returns
The callback manager.
Return type
CallbackMa... | lang/api.python.langchain.com/en/latest/schema.runnable/langchain.schema.runnable.config.get_callback_manager_for_config.html |
9a7db9277062-0 | langchain.schema.runnable.config.patch_config¶
langchain.schema.runnable.config.patch_config(config: Optional[RunnableConfig], *, callbacks: Optional[BaseCallbackManager] = None, recursion_limit: Optional[int] = None, max_concurrency: Optional[int] = None, run_name: Optional[str] = None, configurable: Optional[Dict[str... | lang/api.python.langchain.com/en/latest/schema.runnable/langchain.schema.runnable.config.patch_config.html |
4d9ffa7b7672-0 | langchain.schema.runnable.config.acall_func_with_variable_args¶
async langchain.schema.runnable.config.acall_func_with_variable_args(func: Union[Callable[[Input], Awaitable[Output]], Callable[[Input, RunnableConfig], Awaitable[Output]], Callable[[Input, AsyncCallbackManagerForChainRun], Awaitable[Output]], Callable[[In... | lang/api.python.langchain.com/en/latest/schema.runnable/langchain.schema.runnable.config.acall_func_with_variable_args.html |
101615e42447-0 | langchain.schema.runnable.config.get_config_list¶
langchain.schema.runnable.config.get_config_list(config: Optional[Union[RunnableConfig, List[RunnableConfig]]], length: int) → List[RunnableConfig][source]¶
Get a list of configs from a single config or a list of configs.
It is useful for subclasses overriding batch() o... | lang/api.python.langchain.com/en/latest/schema.runnable/langchain.schema.runnable.config.get_config_list.html |
879f059862af-0 | langchain.schema.runnable.utils.SupportsAdd¶
class langchain.schema.runnable.utils.SupportsAdd(*args, **kwargs)[source]¶
Protocol for objects that support addition.
Methods
__init__(*args, **kwargs)
__init__(*args, **kwargs)¶ | lang/api.python.langchain.com/en/latest/schema.runnable/langchain.schema.runnable.utils.SupportsAdd.html |
06fd57af7112-0 | langchain.schema.runnable.configurable.RunnableConfigurableAlternatives¶
class langchain.schema.runnable.configurable.RunnableConfigurableAlternatives[source]¶
Bases: DynamicRunnable[Input, Output]
A Runnable that can be dynamically configured.
Create a new model by parsing and validating input data from keyword argume... | lang/api.python.langchain.com/en/latest/schema.runnable/langchain.schema.runnable.configurable.RunnableConfigurableAlternatives.html |
06fd57af7112-1 | Subclasses should override this method if they can run asynchronously.
async astream(input: Input, config: Optional[RunnableConfig] = None, **kwargs: Optional[Any]) → AsyncIterator[Output]¶
Default implementation of astream, which calls ainvoke.
Subclasses should override this method if they support streaming output.
a... | lang/api.python.langchain.com/en/latest/schema.runnable/langchain.schema.runnable.configurable.RunnableConfigurableAlternatives.html |
06fd57af7112-2 | Default implementation runs invoke in parallel using a thread pool executor.
The default implementation of batch works well for IO bound runnables.
Subclasses should override this method if they can batch more efficiently;
e.g., if the underlying runnable uses an API which supports a batch mode.
bind(**kwargs: Any) → R... | lang/api.python.langchain.com/en/latest/schema.runnable/langchain.schema.runnable.configurable.RunnableConfigurableAlternatives.html |
06fd57af7112-3 | Duplicate a model, optionally choose which fields to include, exclude and change.
Parameters
include – fields to include in new model
exclude – fields to exclude from new model, as with values this takes precedence over include
update – values to change/add in the new model. Note: the data is not validated before creat... | lang/api.python.langchain.com/en/latest/schema.runnable/langchain.schema.runnable.configurable.RunnableConfigurableAlternatives.html |
06fd57af7112-4 | namespace is [“langchain”, “llms”, “openai”]
get_output_schema(config: Optional[RunnableConfig] = None) → Type[BaseModel]¶
Get a pydantic model that can be used to validate output to the runnable.
Runnables that leverage the configurable_fields and configurable_alternatives
methods will have a dynamic output schema tha... | lang/api.python.langchain.com/en/latest/schema.runnable/langchain.schema.runnable.configurable.RunnableConfigurableAlternatives.html |
06fd57af7112-5 | Generate a JSON representation of the model, include and exclude arguments as per dict().
encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().
classmethod lc_id() → List[str]¶
A unique identifier for this class for serialization purposes.
The unique identifier is a ... | lang/api.python.langchain.com/en/latest/schema.runnable/langchain.schema.runnable.configurable.RunnableConfigurableAlternatives.html |
06fd57af7112-6 | Default implementation of transform, which buffers input and then calls stream.
Subclasses should override this method if they can start producing output while
input is still being generated.
classmethod update_forward_refs(**localns: Any) → None¶
Try to update ForwardRefs on fields based on this Model, globalns and lo... | lang/api.python.langchain.com/en/latest/schema.runnable/langchain.schema.runnable.configurable.RunnableConfigurableAlternatives.html |
06fd57af7112-7 | added to the run.
with_retry(*, retry_if_exception_type: ~typing.Tuple[~typing.Type[BaseException], ...] = (<class 'Exception'>,), wait_exponential_jitter: bool = True, stop_after_attempt: int = 3) → Runnable[Input, Output]¶
Create a new Runnable that retries the original runnable on exceptions.
Parameters
retry_if_exc... | lang/api.python.langchain.com/en/latest/schema.runnable/langchain.schema.runnable.configurable.RunnableConfigurableAlternatives.html |
06fd57af7112-8 | property output_schema: Type[pydantic.main.BaseModel]¶
The type of output this runnable produces specified as a pydantic model. | lang/api.python.langchain.com/en/latest/schema.runnable/langchain.schema.runnable.configurable.RunnableConfigurableAlternatives.html |
91e216eb5365-0 | langchain.schema.runnable.base.RunnableLambda¶
class langchain.schema.runnable.base.RunnableLambda(func: Union[Union[Callable[[Input], Output], Callable[[Input, RunnableConfig], Output], Callable[[Input, CallbackManagerForChainRun], Output], Callable[[Input, CallbackManagerForChainRun, RunnableConfig], Output]], Union[... | lang/api.python.langchain.com/en/latest/schema.runnable/langchain.schema.runnable.base.RunnableLambda.html |
91e216eb5365-1 | # Alternatively, can provide both synd and sync implementations
async def add_one_async(x: int) -> int:
return x + 1
runnable = RunnableLambda(add_one, afunc=add_one_async)
runnable.invoke(1) # Uses add_one
await runnable.ainvoke(1) # Uses add_one_async
Create a RunnableLambda from a callable, and async callable or... | lang/api.python.langchain.com/en/latest/schema.runnable/langchain.schema.runnable.base.RunnableLambda.html |
91e216eb5365-2 | bind(**kwargs)
Bind arguments to a Runnable, returning a new Runnable.
config_schema(*[, include])
The type of config this runnable accepts specified as a pydantic model.
get_input_schema([config])
The pydantic schema for the input to this runnable.
get_output_schema([config])
Get a pydantic model that can be used to v... | lang/api.python.langchain.com/en/latest/schema.runnable/langchain.schema.runnable.base.RunnableLambda.html |
91e216eb5365-3 | Bind input and output types to a Runnable, returning a new Runnable.
__init__(func: Union[Union[Callable[[Input], Output], Callable[[Input, RunnableConfig], Output], Callable[[Input, CallbackManagerForChainRun], Output], Callable[[Input, CallbackManagerForChainRun, RunnableConfig], Output]], Union[Callable[[Input], Awa... | lang/api.python.langchain.com/en/latest/schema.runnable/langchain.schema.runnable.base.RunnableLambda.html |
91e216eb5365-4 | Invoke this runnable asynchronously.
async astream(input: Input, config: Optional[RunnableConfig] = None, **kwargs: Optional[Any]) → AsyncIterator[Output]¶
Default implementation of astream, which calls ainvoke.
Subclasses should override this method if they support streaming output.
async astream_log(input: Any, confi... | lang/api.python.langchain.com/en/latest/schema.runnable/langchain.schema.runnable.base.RunnableLambda.html |
91e216eb5365-5 | Default implementation runs invoke in parallel using a thread pool executor.
The default implementation of batch works well for IO bound runnables.
Subclasses should override this method if they can batch more efficiently;
e.g., if the underlying runnable uses an API which supports a batch mode.
bind(**kwargs: Any) → R... | lang/api.python.langchain.com/en/latest/schema.runnable/langchain.schema.runnable.base.RunnableLambda.html |
91e216eb5365-6 | Return a new Runnable that maps a list of inputs to a list of outputs,
by calling invoke() with each input.
stream(input: Input, config: Optional[RunnableConfig] = None, **kwargs: Optional[Any]) → Iterator[Output]¶
Default implementation of stream, which calls invoke.
Subclasses should override this method if they supp... | lang/api.python.langchain.com/en/latest/schema.runnable/langchain.schema.runnable.base.RunnableLambda.html |
91e216eb5365-7 | on_end: Called after the runnable finishes running, with the Run object.
on_error: Called if the runnable throws an error, with the Run object.
The Run object contains information about the run, including its id,
type, input, output, error, start_time, end_time, and any tags or metadata
added to the run.
with_retry(*, ... | lang/api.python.langchain.com/en/latest/schema.runnable/langchain.schema.runnable.base.RunnableLambda.html |
bbf66f0b0d50-0 | langchain.schema.runnable.base.RunnableEach¶
class langchain.schema.runnable.base.RunnableEach[source]¶
Bases: RunnableEachBase[Input, Output]
A runnable that delegates calls to another runnable
with each element of the input sequence.
Create a new model by parsing and validating input data from keyword arguments.
Rais... | lang/api.python.langchain.com/en/latest/schema.runnable/langchain.schema.runnable.base.RunnableEach.html |
bbf66f0b0d50-1 | Subclasses should override this method if they support streaming output.
async astream_log(input: Any, config: Optional[RunnableConfig] = None, *, diff: bool = True, include_names: Optional[Sequence[str]] = None, include_types: Optional[Sequence[str]] = None, include_tags: Optional[Sequence[str]] = None, exclude_names:... | lang/api.python.langchain.com/en/latest/schema.runnable/langchain.schema.runnable.base.RunnableEach.html |
bbf66f0b0d50-2 | e.g., if the underlying runnable uses an API which supports a batch mode.
bind(**kwargs: Any) → RunnableEach[Input, Output][source]¶
Bind arguments to a Runnable, returning a new Runnable.
config_schema(*, include: Optional[Sequence[str]] = None) → Type[BaseModel]¶
The type of config this runnable accepts specified as ... | lang/api.python.langchain.com/en/latest/schema.runnable/langchain.schema.runnable.base.RunnableEach.html |
bbf66f0b0d50-3 | Parameters
include – fields to include in new model
exclude – fields to exclude from new model, as with values this takes precedence over include
update – values to change/add in the new model. Note: the data is not validated before creating
the new model: you should trust this data
deep – set to True to make a deep co... | lang/api.python.langchain.com/en/latest/schema.runnable/langchain.schema.runnable.base.RunnableEach.html |
bbf66f0b0d50-4 | Get a pydantic model that can be used to validate output to the runnable.
Runnables that leverage the configurable_fields and configurable_alternatives
methods will have a dynamic output schema that depends on which
configuration the runnable is invoked with.
This method allows to get an output schema for a specific co... | lang/api.python.langchain.com/en/latest/schema.runnable/langchain.schema.runnable.base.RunnableEach.html |
bbf66f0b0d50-5 | classmethod lc_id() → List[str]¶
A unique identifier for this class for serialization purposes.
The unique identifier is a list of strings that describes the path
to the object.
map() → Runnable[List[Input], List[Output]]¶
Return a new Runnable that maps a list of inputs to a list of outputs,
by calling invoke() with e... | lang/api.python.langchain.com/en/latest/schema.runnable/langchain.schema.runnable.base.RunnableEach.html |
bbf66f0b0d50-6 | classmethod update_forward_refs(**localns: Any) → None¶
Try to update ForwardRefs on fields based on this Model, globalns and localns.
classmethod validate(value: Any) → Model¶
with_config(config: Optional[RunnableConfig] = None, **kwargs: Any) → RunnableEach[Input, Output][source]¶
Bind config to a Runnable, returning... | lang/api.python.langchain.com/en/latest/schema.runnable/langchain.schema.runnable.base.RunnableEach.html |
bbf66f0b0d50-7 | added to the run.
with_retry(*, retry_if_exception_type: ~typing.Tuple[~typing.Type[BaseException], ...] = (<class 'Exception'>,), wait_exponential_jitter: bool = True, stop_after_attempt: int = 3) → Runnable[Input, Output]¶
Create a new Runnable that retries the original runnable on exceptions.
Parameters
retry_if_exc... | lang/api.python.langchain.com/en/latest/schema.runnable/langchain.schema.runnable.base.RunnableEach.html |
bbf66f0b0d50-8 | property output_schema: Type[pydantic.main.BaseModel]¶
The type of output this runnable produces specified as a pydantic model. | lang/api.python.langchain.com/en/latest/schema.runnable/langchain.schema.runnable.base.RunnableEach.html |
e2e1b5ce1d7c-0 | langchain.schema.runnable.utils.ConfigurableFieldSingleOption¶
class langchain.schema.runnable.utils.ConfigurableFieldSingleOption(id: str, options: Mapping[str, Any], default: str, name: Optional[str] = None, description: Optional[str] = None)[source]¶
A field that can be configured by the user with a default value.
C... | lang/api.python.langchain.com/en/latest/schema.runnable/langchain.schema.runnable.utils.ConfigurableFieldSingleOption.html |
c5797a5da699-0 | langchain.schema.runnable.configurable.StrEnum¶
class langchain.schema.runnable.configurable.StrEnum(value, names=None, *, module=None, qualname=None, type=None, start=1, boundary=None)[source]¶
A string enum. | lang/api.python.langchain.com/en/latest/schema.runnable/langchain.schema.runnable.configurable.StrEnum.html |
acd8f82bbabe-0 | langchain.schema.runnable.configurable.DynamicRunnable¶
class langchain.schema.runnable.configurable.DynamicRunnable[source]¶
Bases: RunnableSerializable[Input, Output]
A Serializable Runnable that can be dynamically configured.
Create a new model by parsing and validating input data from keyword arguments.
Raises Vali... | lang/api.python.langchain.com/en/latest/schema.runnable/langchain.schema.runnable.configurable.DynamicRunnable.html |
acd8f82bbabe-1 | Subclasses should override this method if they support streaming output.
async astream_log(input: Any, config: Optional[RunnableConfig] = None, *, diff: bool = True, include_names: Optional[Sequence[str]] = None, include_types: Optional[Sequence[str]] = None, include_tags: Optional[Sequence[str]] = None, exclude_names:... | lang/api.python.langchain.com/en/latest/schema.runnable/langchain.schema.runnable.configurable.DynamicRunnable.html |
acd8f82bbabe-2 | e.g., if the underlying runnable uses an API which supports a batch mode.
bind(**kwargs: Any) → Runnable[Input, Output]¶
Bind arguments to a Runnable, returning a new Runnable.
config_schema(*, include: Optional[Sequence[str]] = None) → Type[BaseModel]¶
The type of config this runnable accepts specified as a pydantic m... | lang/api.python.langchain.com/en/latest/schema.runnable/langchain.schema.runnable.configurable.DynamicRunnable.html |
acd8f82bbabe-3 | exclude – fields to exclude from new model, as with values this takes precedence over include
update – values to change/add in the new model. Note: the data is not validated before creating
the new model: you should trust this data
deep – set to True to make a deep copy of the model
Returns
new model instance
dict(*, i... | lang/api.python.langchain.com/en/latest/schema.runnable/langchain.schema.runnable.configurable.DynamicRunnable.html |
acd8f82bbabe-4 | Get a pydantic model that can be used to validate output to the runnable.
Runnables that leverage the configurable_fields and configurable_alternatives
methods will have a dynamic output schema that depends on which
configuration the runnable is invoked with.
This method allows to get an output schema for a specific co... | lang/api.python.langchain.com/en/latest/schema.runnable/langchain.schema.runnable.configurable.DynamicRunnable.html |
acd8f82bbabe-5 | classmethod lc_id() → List[str]¶
A unique identifier for this class for serialization purposes.
The unique identifier is a list of strings that describes the path
to the object.
map() → Runnable[List[Input], List[Output]]¶
Return a new Runnable that maps a list of inputs to a list of outputs,
by calling invoke() with e... | lang/api.python.langchain.com/en/latest/schema.runnable/langchain.schema.runnable.configurable.DynamicRunnable.html |
acd8f82bbabe-6 | classmethod update_forward_refs(**localns: Any) → None¶
Try to update ForwardRefs on fields based on this Model, globalns and localns.
classmethod validate(value: Any) → Model¶
with_config(config: Optional[RunnableConfig] = None, **kwargs: Any) → Runnable[Input, Output]¶
Bind config to a Runnable, returning a new Runna... | lang/api.python.langchain.com/en/latest/schema.runnable/langchain.schema.runnable.configurable.DynamicRunnable.html |
acd8f82bbabe-7 | added to the run.
with_retry(*, retry_if_exception_type: ~typing.Tuple[~typing.Type[BaseException], ...] = (<class 'Exception'>,), wait_exponential_jitter: bool = True, stop_after_attempt: int = 3) → Runnable[Input, Output]¶
Create a new Runnable that retries the original runnable on exceptions.
Parameters
retry_if_exc... | lang/api.python.langchain.com/en/latest/schema.runnable/langchain.schema.runnable.configurable.DynamicRunnable.html |
acd8f82bbabe-8 | property output_schema: Type[pydantic.main.BaseModel]¶
The type of output this runnable produces specified as a pydantic model. | lang/api.python.langchain.com/en/latest/schema.runnable/langchain.schema.runnable.configurable.DynamicRunnable.html |
ca2fc64fbb6d-0 | langchain.schema.runnable.utils.ConfigurableField¶
class langchain.schema.runnable.utils.ConfigurableField(id: str, name: Optional[str] = None, description: Optional[str] = None, annotation: Optional[Any] = None)[source]¶
A field that can be configured by the user.
Create new instance of ConfigurableField(id, name, des... | lang/api.python.langchain.com/en/latest/schema.runnable/langchain.schema.runnable.utils.ConfigurableField.html |
be314d7bb5ec-0 | langchain.schema.runnable.base.RunnableBindingBase¶
class langchain.schema.runnable.base.RunnableBindingBase[source]¶
Bases: RunnableSerializable[Input, Output]
A runnable that delegates calls to another runnable with a set of kwargs.
Use only if creating a new RunnableBinding subclass with different __init__ args.
Cre... | lang/api.python.langchain.com/en/latest/schema.runnable/langchain.schema.runnable.base.RunnableBindingBase.html |
be314d7bb5ec-1 | the runnable did not implement a native async version of invoke.
Subclasses should override this method if they can run asynchronously.
async astream(input: Input, config: Optional[RunnableConfig] = None, **kwargs: Optional[Any]) → AsyncIterator[Output][source]¶
Default implementation of astream, which calls ainvoke.
S... | lang/api.python.langchain.com/en/latest/schema.runnable/langchain.schema.runnable.base.RunnableBindingBase.html |
be314d7bb5ec-2 | input is still being generated.
batch(inputs: List[Input], config: Optional[Union[RunnableConfig, List[RunnableConfig]]] = None, *, return_exceptions: bool = False, **kwargs: Optional[Any]) → List[Output][source]¶
Default implementation runs invoke in parallel using a thread pool executor.
The default implementation of... | lang/api.python.langchain.com/en/latest/schema.runnable/langchain.schema.runnable.base.RunnableBindingBase.html |
be314d7bb5ec-3 | Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny] = None, deep: bool = False) → Model¶
Duplicate a model, optionally... | lang/api.python.langchain.com/en/latest/schema.runnable/langchain.schema.runnable.base.RunnableBindingBase.html |
be314d7bb5ec-4 | Parameters
config – A config to use when generating the schema.
Returns
A pydantic model that can be used to validate input.
classmethod get_lc_namespace() → List[str][source]¶
Get the namespace of the langchain object.
For example, if the class is langchain.llms.openai.OpenAI, then the
namespace is [“langchain”, “llms... | lang/api.python.langchain.com/en/latest/schema.runnable/langchain.schema.runnable.base.RunnableBindingBase.html |
be314d7bb5ec-5 | classmethod is_lc_serializable() → bool[source]¶
Is this class serializable?
json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, excl... | lang/api.python.langchain.com/en/latest/schema.runnable/langchain.schema.runnable.base.RunnableBindingBase.html |
be314d7bb5ec-6 | classmethod schema_json(*, by_alias: bool = True, ref_template: unicode = '#/definitions/{model}', **dumps_kwargs: Any) → unicode¶
stream(input: Input, config: Optional[RunnableConfig] = None, **kwargs: Optional[Any]) → Iterator[Output][source]¶
Default implementation of stream, which calls invoke.
Subclasses should ov... | lang/api.python.langchain.com/en/latest/schema.runnable/langchain.schema.runnable.base.RunnableBindingBase.html |
be314d7bb5ec-7 | fallback in order, upon failures.
with_listeners(*, on_start: Optional[Listener] = None, on_end: Optional[Listener] = None, on_error: Optional[Listener] = None) → Runnable[Input, Output]¶
Bind lifecycle listeners to a Runnable, returning a new Runnable.
on_start: Called before the runnable starts running, with the Run ... | lang/api.python.langchain.com/en/latest/schema.runnable/langchain.schema.runnable.base.RunnableBindingBase.html |
be314d7bb5ec-8 | The type of output this runnable produces specified as a type annotation.
property config_specs: List[langchain.schema.runnable.utils.ConfigurableFieldSpec]¶
List configurable fields for this runnable.
property input_schema: Type[pydantic.main.BaseModel]¶
The type of input this runnable accepts specified as a pydantic ... | lang/api.python.langchain.com/en/latest/schema.runnable/langchain.schema.runnable.base.RunnableBindingBase.html |
dad58b6aa148-0 | langchain.schema.runnable.passthrough.aidentity¶
async langchain.schema.runnable.passthrough.aidentity(x: Other) → Other[source]¶
An async identity function | lang/api.python.langchain.com/en/latest/schema.runnable/langchain.schema.runnable.passthrough.aidentity.html |
25c4de52b9b8-0 | langchain.schema.runnable.utils.GetLambdaSource¶
class langchain.schema.runnable.utils.GetLambdaSource[source]¶
Get the source code of a lambda function.
Initialize the visitor.
Methods
__init__()
Initialize the visitor.
generic_visit(node)
Called if no explicit visitor function exists for a node.
visit(node)
Visit a n... | lang/api.python.langchain.com/en/latest/schema.runnable/langchain.schema.runnable.utils.GetLambdaSource.html |
e3ac21010b3e-0 | langchain.schema.runnable.passthrough.RunnableAssign¶
class langchain.schema.runnable.passthrough.RunnableAssign[source]¶
Bases: RunnableSerializable[Dict[str, Any], Dict[str, Any]]
A runnable that assigns key-value pairs to Dict[str, Any] inputs.
Create a new model by parsing and validating input data from keyword arg... | lang/api.python.langchain.com/en/latest/schema.runnable/langchain.schema.runnable.passthrough.RunnableAssign.html |
e3ac21010b3e-1 | Subclasses should override this method if they support streaming output.
async astream_log(input: Any, config: Optional[RunnableConfig] = None, *, diff: bool = True, include_names: Optional[Sequence[str]] = None, include_types: Optional[Sequence[str]] = None, include_tags: Optional[Sequence[str]] = None, exclude_names:... | lang/api.python.langchain.com/en/latest/schema.runnable/langchain.schema.runnable.passthrough.RunnableAssign.html |
e3ac21010b3e-2 | e.g., if the underlying runnable uses an API which supports a batch mode.
bind(**kwargs: Any) → Runnable[Input, Output]¶
Bind arguments to a Runnable, returning a new Runnable.
config_schema(*, include: Optional[Sequence[str]] = None) → Type[BaseModel]¶
The type of config this runnable accepts specified as a pydantic m... | lang/api.python.langchain.com/en/latest/schema.runnable/langchain.schema.runnable.passthrough.RunnableAssign.html |
e3ac21010b3e-3 | exclude – fields to exclude from new model, as with values this takes precedence over include
update – values to change/add in the new model. Note: the data is not validated before creating
the new model: you should trust this data
deep – set to True to make a deep copy of the model
Returns
new model instance
dict(*, i... | lang/api.python.langchain.com/en/latest/schema.runnable/langchain.schema.runnable.passthrough.RunnableAssign.html |
e3ac21010b3e-4 | Get a pydantic model that can be used to validate output to the runnable.
Runnables that leverage the configurable_fields and configurable_alternatives
methods will have a dynamic output schema that depends on which
configuration the runnable is invoked with.
This method allows to get an output schema for a specific co... | lang/api.python.langchain.com/en/latest/schema.runnable/langchain.schema.runnable.passthrough.RunnableAssign.html |
e3ac21010b3e-5 | classmethod lc_id() → List[str]¶
A unique identifier for this class for serialization purposes.
The unique identifier is a list of strings that describes the path
to the object.
map() → Runnable[List[Input], List[Output]]¶
Return a new Runnable that maps a list of inputs to a list of outputs,
by calling invoke() with e... | lang/api.python.langchain.com/en/latest/schema.runnable/langchain.schema.runnable.passthrough.RunnableAssign.html |
e3ac21010b3e-6 | input is still being generated.
classmethod update_forward_refs(**localns: Any) → None¶
Try to update ForwardRefs on fields based on this Model, globalns and localns.
classmethod validate(value: Any) → Model¶
with_config(config: Optional[RunnableConfig] = None, **kwargs: Any) → Runnable[Input, Output]¶
Bind config to a... | lang/api.python.langchain.com/en/latest/schema.runnable/langchain.schema.runnable.passthrough.RunnableAssign.html |
e3ac21010b3e-7 | added to the run.
with_retry(*, retry_if_exception_type: ~typing.Tuple[~typing.Type[BaseException], ...] = (<class 'Exception'>,), wait_exponential_jitter: bool = True, stop_after_attempt: int = 3) → Runnable[Input, Output]¶
Create a new Runnable that retries the original runnable on exceptions.
Parameters
retry_if_exc... | lang/api.python.langchain.com/en/latest/schema.runnable/langchain.schema.runnable.passthrough.RunnableAssign.html |
e3ac21010b3e-8 | property output_schema: Type[pydantic.main.BaseModel]¶
The type of output this runnable produces specified as a pydantic model. | lang/api.python.langchain.com/en/latest/schema.runnable/langchain.schema.runnable.passthrough.RunnableAssign.html |
ec7aa9c77030-0 | langchain.schema.runnable.base.RunnableGenerator¶
class langchain.schema.runnable.base.RunnableGenerator(transform: Union[Callable[[Iterator[Input]], Iterator[Output]], Callable[[AsyncIterator[Input]], AsyncIterator[Output]]], atransform: Optional[Callable[[AsyncIterator[Input]], AsyncIterator[Output]]] = None)[source]... | lang/api.python.langchain.com/en/latest/schema.runnable/langchain.schema.runnable.base.RunnableGenerator.html |
ec7aa9c77030-1 | get_output_schema([config])
Get a pydantic model that can be used to validate output to the runnable.
invoke(input[, config])
Transform a single input into an output.
map()
Return a new Runnable that maps a list of inputs to a list of outputs, by calling invoke() with each input.
stream(input[, config])
Default impleme... | lang/api.python.langchain.com/en/latest/schema.runnable/langchain.schema.runnable.base.RunnableGenerator.html |
ec7aa9c77030-2 | Subclasses should override this method if they can batch more efficiently;
e.g., if the underlying runnable uses an API which supports a batch mode.
async ainvoke(input: Input, config: Optional[RunnableConfig] = None, **kwargs: Any) → Output[source]¶
Default implementation of ainvoke, calls invoke from a thread.
The de... | lang/api.python.langchain.com/en/latest/schema.runnable/langchain.schema.runnable.base.RunnableGenerator.html |
ec7aa9c77030-3 | The jsonpatch ops can be applied in order to construct state.
atransform(input: AsyncIterator[Input], config: Optional[RunnableConfig] = None, **kwargs: Any) → AsyncIterator[Output][source]¶
Default implementation of atransform, which buffers input and calls astream.
Subclasses should override this method if they can s... | lang/api.python.langchain.com/en/latest/schema.runnable/langchain.schema.runnable.base.RunnableGenerator.html |
ec7aa9c77030-4 | This method allows to get an input schema for a specific configuration.
Parameters
config – A config to use when generating the schema.
Returns
A pydantic model that can be used to validate input.
get_output_schema(config: Optional[RunnableConfig] = None) → Type[BaseModel]¶
Get a pydantic model that can be used to vali... | lang/api.python.langchain.com/en/latest/schema.runnable/langchain.schema.runnable.base.RunnableGenerator.html |
ec7aa9c77030-5 | Subclasses should override this method if they support streaming output.
transform(input: Iterator[Input], config: Optional[RunnableConfig] = None, **kwargs: Any) → Iterator[Output][source]¶
Default implementation of transform, which buffers input and then calls stream.
Subclasses should override this method if they ca... | lang/api.python.langchain.com/en/latest/schema.runnable/langchain.schema.runnable.base.RunnableGenerator.html |
ec7aa9c77030-6 | added to the run.
with_retry(*, retry_if_exception_type: ~typing.Tuple[~typing.Type[BaseException], ...] = (<class 'Exception'>,), wait_exponential_jitter: bool = True, stop_after_attempt: int = 3) → Runnable[Input, Output]¶
Create a new Runnable that retries the original runnable on exceptions.
Parameters
retry_if_exc... | lang/api.python.langchain.com/en/latest/schema.runnable/langchain.schema.runnable.base.RunnableGenerator.html |
5614e378e6d6-0 | langchain.schema.runnable.configurable.make_options_spec¶
langchain.schema.runnable.configurable.make_options_spec(spec: Union[ConfigurableFieldSingleOption, ConfigurableFieldMultiOption], description: Optional[str]) → ConfigurableFieldSpec[source]¶
Make a ConfigurableFieldSpec for a ConfigurableFieldSingleOption or
Co... | lang/api.python.langchain.com/en/latest/schema.runnable/langchain.schema.runnable.configurable.make_options_spec.html |
c288d11208ee-0 | langchain.schema.runnable.configurable.RunnableConfigurableFields¶
class langchain.schema.runnable.configurable.RunnableConfigurableFields[source]¶
Bases: DynamicRunnable[Input, Output]
A Runnable that can be dynamically configured.
Create a new model by parsing and validating input data from keyword arguments.
Raises ... | lang/api.python.langchain.com/en/latest/schema.runnable/langchain.schema.runnable.configurable.RunnableConfigurableFields.html |
c288d11208ee-1 | Default implementation of astream, which calls ainvoke.
Subclasses should override this method if they support streaming output.
async astream_log(input: Any, config: Optional[RunnableConfig] = None, *, diff: bool = True, include_names: Optional[Sequence[str]] = None, include_types: Optional[Sequence[str]] = None, incl... | lang/api.python.langchain.com/en/latest/schema.runnable/langchain.schema.runnable.configurable.RunnableConfigurableFields.html |
c288d11208ee-2 | Subclasses should override this method if they can batch more efficiently;
e.g., if the underlying runnable uses an API which supports a batch mode.
bind(**kwargs: Any) → Runnable[Input, Output]¶
Bind arguments to a Runnable, returning a new Runnable.
config_schema(*, include: Optional[Sequence[str]] = None) → Type[Bas... | lang/api.python.langchain.com/en/latest/schema.runnable/langchain.schema.runnable.configurable.RunnableConfigurableFields.html |
c288d11208ee-3 | Parameters
include – fields to include in new model
exclude – fields to exclude from new model, as with values this takes precedence over include
update – values to change/add in the new model. Note: the data is not validated before creating
the new model: you should trust this data
deep – set to True to make a deep co... | lang/api.python.langchain.com/en/latest/schema.runnable/langchain.schema.runnable.configurable.RunnableConfigurableFields.html |
c288d11208ee-4 | Get a pydantic model that can be used to validate output to the runnable.
Runnables that leverage the configurable_fields and configurable_alternatives
methods will have a dynamic output schema that depends on which
configuration the runnable is invoked with.
This method allows to get an output schema for a specific co... | lang/api.python.langchain.com/en/latest/schema.runnable/langchain.schema.runnable.configurable.RunnableConfigurableFields.html |
c288d11208ee-5 | classmethod lc_id() → List[str]¶
A unique identifier for this class for serialization purposes.
The unique identifier is a list of strings that describes the path
to the object.
map() → Runnable[List[Input], List[Output]]¶
Return a new Runnable that maps a list of inputs to a list of outputs,
by calling invoke() with e... | lang/api.python.langchain.com/en/latest/schema.runnable/langchain.schema.runnable.configurable.RunnableConfigurableFields.html |
c288d11208ee-6 | classmethod update_forward_refs(**localns: Any) → None¶
Try to update ForwardRefs on fields based on this Model, globalns and localns.
classmethod validate(value: Any) → Model¶
with_config(config: Optional[RunnableConfig] = None, **kwargs: Any) → Runnable[Input, Output]¶
Bind config to a Runnable, returning a new Runna... | lang/api.python.langchain.com/en/latest/schema.runnable/langchain.schema.runnable.configurable.RunnableConfigurableFields.html |
c288d11208ee-7 | added to the run.
with_retry(*, retry_if_exception_type: ~typing.Tuple[~typing.Type[BaseException], ...] = (<class 'Exception'>,), wait_exponential_jitter: bool = True, stop_after_attempt: int = 3) → Runnable[Input, Output]¶
Create a new Runnable that retries the original runnable on exceptions.
Parameters
retry_if_exc... | lang/api.python.langchain.com/en/latest/schema.runnable/langchain.schema.runnable.configurable.RunnableConfigurableFields.html |
c288d11208ee-8 | property output_schema: Type[pydantic.main.BaseModel]¶
The type of output this runnable produces specified as a pydantic model. | lang/api.python.langchain.com/en/latest/schema.runnable/langchain.schema.runnable.configurable.RunnableConfigurableFields.html |
867445ce28eb-0 | langchain.schema.runnable.base.Runnable¶
class langchain.schema.runnable.base.Runnable[source]¶
A unit of work that can be invoked, batched, streamed, transformed and composed.
invoke/ainvoke: Transforms a single input into an output.
batch/abatch: Efficiently transforms multiple inputs into outputs.
stream/astream: St... | lang/api.python.langchain.com/en/latest/schema.runnable/langchain.schema.runnable.base.Runnable.html |
867445ce28eb-1 | # A RunnableSequence constructed using the `|` operator
sequence = RunnableLambda(lambda x: x + 1) | RunnableLambda(lambda x: x * 2)
sequence.invoke(1) # 4
sequence.batch([1, 2, 3]) # [4, 6, 8]
# A sequence that contains a RunnableParallel constructed using a dict literal
sequence = RunnableLambda(lambda x: x + 1) | {
... | lang/api.python.langchain.com/en/latest/schema.runnable/langchain.schema.runnable.base.Runnable.html |
867445ce28eb-2 | print(sequence.output_schema.schema()) # Show inferred output schema
print(sequence.invoke(2)) # invoke the sequence (note the retry above!!)
As the chains get longer, it can be useful to be able to see intermediate results
to debug and trace the chain.
You can set the global debug flag to True to enable debug output f... | lang/api.python.langchain.com/en/latest/schema.runnable/langchain.schema.runnable.base.Runnable.html |
867445ce28eb-3 | Default implementation runs invoke in parallel using a thread pool executor.
bind(**kwargs)
Bind arguments to a Runnable, returning a new Runnable.
config_schema(*[, include])
The type of config this runnable accepts specified as a pydantic model.
get_input_schema([config])
Get a pydantic model that can be used to vali... | lang/api.python.langchain.com/en/latest/schema.runnable/langchain.schema.runnable.base.Runnable.html |
867445ce28eb-4 | Default implementation runs ainvoke in parallel using asyncio.gather.
The default implementation of batch works well for IO bound runnables.
Subclasses should override this method if they can batch more efficiently;
e.g., if the underlying runnable uses an API which supports a batch mode.
async ainvoke(input: Input, co... | lang/api.python.langchain.com/en/latest/schema.runnable/langchain.schema.runnable.base.Runnable.html |
867445ce28eb-5 | async astream_log(input: Any, config: Optional[RunnableConfig] = None, *, diff: Literal[False], 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[Seque... | lang/api.python.langchain.com/en/latest/schema.runnable/langchain.schema.runnable.base.Runnable.html |
867445ce28eb-6 | bind(**kwargs: Any) → Runnable[Input, Output][source]¶
Bind arguments to a Runnable, returning a new Runnable.
config_schema(*, include: Optional[Sequence[str]] = None) → Type[BaseModel][source]¶
The type of config this runnable accepts specified as a pydantic model.
To mark a field as configurable, see the configurabl... | lang/api.python.langchain.com/en/latest/schema.runnable/langchain.schema.runnable.base.Runnable.html |
867445ce28eb-7 | Transform a single input into an output. Override to implement.
Parameters
input – The input to the runnable.
config – A config to use when invoking the runnable.
The config supports standard keys like ‘tags’, ‘metadata’ for tracing
purposes, ‘max_concurrency’ for controlling how much work to do
in parallel, and other ... | lang/api.python.langchain.com/en/latest/schema.runnable/langchain.schema.runnable.base.Runnable.html |
867445ce28eb-8 | exceptions_to_handle – A tuple of exception types to handle.
Returns
A new Runnable that will try the original runnable, and then each
fallback in order, upon failures.
with_listeners(*, on_start: Optional[Listener] = None, on_end: Optional[Listener] = None, on_error: Optional[Listener] = None) → Runnable[Input, Output... | lang/api.python.langchain.com/en/latest/schema.runnable/langchain.schema.runnable.base.Runnable.html |
be89f6ba731b-0 | langchain.schema.runnable.history.RunnableWithMessageHistory¶
class langchain.schema.runnable.history.RunnableWithMessageHistory[source]¶
Bases: RunnableBindingBase
A runnable that manages chat message history for another runnable.
Base runnable must have inputs and outputs that can be converted to a list ofBaseMessage... | lang/api.python.langchain.com/en/latest/schema.runnable/langchain.schema.runnable.history.RunnableWithMessageHistory.html |
be89f6ba731b-1 | Must take as input one of:
- A sequence of BaseMessages
- A dict with one key for all messages
- A dict with one key for the current input string/message(s) and
a separate key for historical messages. If the input key points
to a string, it will be treated as a HumanMessage in history.
Must return as output one of:
- A... | lang/api.python.langchain.com/en/latest/schema.runnable/langchain.schema.runnable.history.RunnableWithMessageHistory.html |
be89f6ba731b-2 | param input_messages_key: Optional[str] = None¶
param kwargs: Mapping[str, Any] [Optional]¶
param output_messages_key: Optional[str] = None¶
async abatch(inputs: List[Input], config: Optional[Union[RunnableConfig, List[RunnableConfig]]] = None, *, return_exceptions: bool = False, **kwargs: Optional[Any]) → List[Output]... | lang/api.python.langchain.com/en/latest/schema.runnable/langchain.schema.runnable.history.RunnableWithMessageHistory.html |
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