id stringlengths 14 16 | text stringlengths 13 2.7k | source stringlengths 57 178 |
|---|---|---|
1594fccb9d22-6 | # -> "The temperature in Boise is..."
# Suppose we have a multi-input chain that takes a 'question' string
# and 'context' string:
question = "What's the temperature in Boise, Idaho?"
context = "Weather report for Boise, Idaho on 07/03/23..."
await chain.arun(question=question, context=context)
# -> "The temperature in... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.combine_documents.map_rerank.MapRerankDocumentsChain.html |
1594fccb9d22-7 | Default implementation of atransform, which buffers input and calls astream.
Subclasses should override this method if they can start producing output while
input is still being generated.
batch(inputs: List[Input], config: Optional[Union[RunnableConfig, List[RunnableConfig]]] = None, *, return_exceptions: bool = False... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.combine_documents.map_rerank.MapRerankDocumentsChain.html |
1594fccb9d22-8 | Returns
A pydantic model that can be used to validate config.
configurable_alternatives(which: ConfigurableField, default_key: str = 'default', **kwargs: Union[Runnable[Input, Output], Callable[[], Runnable[Input, Output]]]) → RunnableSerializable[Input, Output]¶
configurable_fields(**kwargs: Union[ConfigurableField, C... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.combine_documents.map_rerank.MapRerankDocumentsChain.html |
1594fccb9d22-9 | method.
Returns
A dictionary representation of the chain.
Example
chain.dict(exclude_unset=True)
# -> {"_type": "foo", "verbose": False, ...}
classmethod from_orm(obj: Any) → Model¶
get_input_schema(config: Optional[RunnableConfig] = None) → Type[BaseModel]¶
Get a pydantic model that can be used to validate input to th... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.combine_documents.map_rerank.MapRerankDocumentsChain.html |
1594fccb9d22-10 | 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 keys. Please refer to the RunnableConfig
for more details.
Retur... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.combine_documents.map_rerank.MapRerankDocumentsChain.html |
1594fccb9d22-11 | classmethod parse_obj(obj: Any) → Model¶
classmethod parse_raw(b: Union[str, bytes], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: Protocol = None, allow_pickle: bool = False) → Model¶
prep_inputs(inputs: Union[Dict[str, Any], Any]) → Dict[str, str]¶
Validate and prepare chain inputs, including ad... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.combine_documents.map_rerank.MapRerankDocumentsChain.html |
1594fccb9d22-12 | otherwise the length of the prompt in tokens.
run(*args: Any, callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None, tags: Optional[List[str]] = None, metadata: Optional[Dict[str, Any]] = None, **kwargs: Any) → Any¶
Convenience method for executing chain.
The main difference between this met... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.combine_documents.map_rerank.MapRerankDocumentsChain.html |
1594fccb9d22-13 | save(file_path: Union[Path, str]) → None¶
Save the chain.
Expects Chain._chain_type property to be implemented and for memory to benull.
Parameters
file_path – Path to file to save the chain to.
Example
chain.save(file_path="path/chain.yaml")
classmethod schema(by_alias: bool = True, ref_template: unicode = '#/definiti... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.combine_documents.map_rerank.MapRerankDocumentsChain.html |
1594fccb9d22-14 | Add fallbacks to a runnable, returning a new Runnable.
Parameters
fallbacks – A sequence of runnables to try if the original runnable fails.
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_liste... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.combine_documents.map_rerank.MapRerankDocumentsChain.html |
1594fccb9d22-15 | Bind input and output types to a Runnable, returning a new Runnable.
property InputType: Type[langchain.schema.runnable.utils.Input]¶
The type of input this runnable accepts specified as a type annotation.
property OutputType: Type[langchain.schema.runnable.utils.Output]¶
The type of output this runnable produces speci... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.combine_documents.map_rerank.MapRerankDocumentsChain.html |
40c9c6b67d91-0 | langchain.chains.prompt_selector.is_chat_model¶
langchain.chains.prompt_selector.is_chat_model(llm: BaseLanguageModel) → bool[source]¶
Check if the language model is a chat model.
Parameters
llm – Language model to check.
Returns
True if the language model is a BaseChatModel model, False otherwise. | lang/api.python.langchain.com/en/latest/chains/langchain.chains.prompt_selector.is_chat_model.html |
f3c002b9631a-0 | langchain.chains.query_constructor.parser.v_args¶
langchain.chains.query_constructor.parser.v_args(*args: Any, **kwargs: Any) → Any[source]¶
Dummy decorator for when lark is not installed. | lang/api.python.langchain.com/en/latest/chains/langchain.chains.query_constructor.parser.v_args.html |
c00e85fb16cf-0 | langchain.chains.router.base.RouterChain¶
class langchain.chains.router.base.RouterChain[source]¶
Bases: Chain, ABC
Chain that outputs the name of a destination chain and the inputs to it.
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be ... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.router.base.RouterChain.html |
c00e85fb16cf-1 | You can use these to eg identify a specific instance of a chain with its use case.
param verbose: bool [Optional]¶
Whether or not run in verbose mode. In verbose mode, some intermediate logs
will be printed to the console. Defaults to the global verbose value,
accessible via langchain.globals.get_verbose().
__call__(in... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.router.base.RouterChain.html |
c00e85fb16cf-2 | Returns
A dict of named outputs. Should contain all outputs specified inChain.output_keys.
async abatch(inputs: List[Input], config: Optional[Union[RunnableConfig, List[RunnableConfig]]] = None, *, return_exceptions: bool = False, **kwargs: Optional[Any]) → List[Output]¶
Default implementation runs ainvoke in parallel ... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.router.base.RouterChain.html |
c00e85fb16cf-3 | addition to tags passed to the chain during construction, but only
these runtime tags will propagate to calls to other objects.
metadata – Optional metadata associated with the chain. Defaults to None
include_run_info – Whether to include run info in the response. Defaults
to False.
Returns
A dict of named outputs. Sho... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.router.base.RouterChain.html |
c00e85fb16cf-4 | callbacks – Callbacks to use for this chain run. These will be called in
addition to callbacks passed to the chain during construction, but only
these runtime callbacks will propagate to calls to other objects.
tags – List of string tags to pass to all callbacks. These will be passed in
addition to tags passed to the c... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.router.base.RouterChain.html |
c00e85fb16cf-5 | 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/chains/langchain.chains.router.base.RouterChain.html |
c00e85fb16cf-6 | 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/chains/langchain.chains.router.base.RouterChain.html |
c00e85fb16cf-7 | 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(**kw... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.router.base.RouterChain.html |
c00e85fb16cf-8 | 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 configuration.
Parameters
config – A config to use when generating the schem... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.router.base.RouterChain.html |
c00e85fb16cf-9 | 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 each input.
classmethod parse_file... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.router.base.RouterChain.html |
c00e85fb16cf-10 | Returns
A dict of the final chain outputs.
route(inputs: Dict[str, Any], callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None) → Route[source]¶
Route inputs to a destination chain.
Parameters
inputs – inputs to the chain
callbacks – callbacks to use for the chain
Returns
a Route object
run(... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.router.base.RouterChain.html |
c00e85fb16cf-11 | # and 'context' string:
question = "What's the temperature in Boise, Idaho?"
context = "Weather report for Boise, Idaho on 07/03/23..."
chain.run(question=question, context=context)
# -> "The temperature in Boise is..."
save(file_path: Union[Path, str]) → None¶
Save the chain.
Expects Chain._chain_type property to be i... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.router.base.RouterChain.html |
c00e85fb16cf-12 | Bind config to a Runnable, returning a new Runnable.
with_fallbacks(fallbacks: Sequence[Runnable[Input, Output]], *, exceptions_to_handle: Tuple[Type[BaseException], ...] = (<class 'Exception'>,)) → RunnableWithFallbacksT[Input, Output]¶
Add fallbacks to a runnable, returning a new Runnable.
Parameters
fallbacks – A se... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.router.base.RouterChain.html |
c00e85fb16cf-13 | between retries
stop_after_attempt – The maximum number of attempts to make before giving up
Returns
A new Runnable that retries the original runnable on exceptions.
with_types(*, input_type: Optional[Type[Input]] = None, output_type: Optional[Type[Output]] = None) → Runnable[Input, Output]¶
Bind input and output types... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.router.base.RouterChain.html |
2b438990ce2a-0 | langchain.chains.openai_functions.openapi.openapi_spec_to_openai_fn¶
langchain.chains.openai_functions.openapi.openapi_spec_to_openai_fn(spec: OpenAPISpec) → Tuple[List[Dict[str, Any]], Callable][source]¶
Convert a valid OpenAPI spec to the JSON Schema format expected for OpenAIfunctions.
Parameters
spec – OpenAPI spec... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.openai_functions.openapi.openapi_spec_to_openai_fn.html |
dbfa371c9647-0 | langchain.chains.openai_functions.citation_fuzzy_match.FactWithEvidence¶
class langchain.chains.openai_functions.citation_fuzzy_match.FactWithEvidence[source]¶
Bases: BaseModel
Class representing a single statement.
Each fact has a body and a list of sources.
If there are multiple facts make sure to break them apart
su... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.openai_functions.citation_fuzzy_match.FactWithEvidence.html |
dbfa371c9647-1 | 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(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[boo... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.openai_functions.citation_fuzzy_match.FactWithEvidence.html |
dbfa371c9647-2 | classmethod parse_obj(obj: Any) → Model¶
classmethod parse_raw(b: Union[str, bytes], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: Protocol = None, allow_pickle: bool = False) → Model¶
classmethod schema(by_alias: bool = True, ref_template: unicode = '#/definitions/{model}') → DictStrAny¶
classmet... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.openai_functions.citation_fuzzy_match.FactWithEvidence.html |
a4061c4cd0bb-0 | langchain.chains.loading.load_chain¶
langchain.chains.loading.load_chain(path: Union[str, Path], **kwargs: Any) → Chain[source]¶
Unified method for loading a chain from LangChainHub or local fs.
Examples using load_chain¶
Hugging Face Prompt Injection Identification
Serialization
Loading from LangChainHub | lang/api.python.langchain.com/en/latest/chains/langchain.chains.loading.load_chain.html |
ff5cf52bc116-0 | langchain.chains.flare.prompts.FinishedOutputParser¶
class langchain.chains.flare.prompts.FinishedOutputParser[source]¶
Bases: BaseOutputParser[Tuple[str, bool]]
Output parser that checks if the output is finished.
param finished_value: str = 'FINISHED'¶
Value that indicates the output is finished.
async abatch(inputs:... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.flare.prompts.FinishedOutputParser.html |
ff5cf52bc116-1 | to be different candidate outputs for a single model input.
Returns
Structured output.
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 str... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.flare.prompts.FinishedOutputParser.html |
ff5cf52bc116-2 | 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/chains/langchain.chains.flare.prompts.FinishedOutputParser.html |
ff5cf52bc116-3 | 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/chains/langchain.chains.flare.prompts.FinishedOutputParser.html |
ff5cf52bc116-4 | 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 configuration.
Parameters
config – A config to use when generating the schema.
Returns
A pydantic model that can be used to validate output.
invoke(input:... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.flare.prompts.FinishedOutputParser.html |
ff5cf52bc116-5 | 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 each input.
parse(text: str) → Tuple[str, bool][source]¶
Parse a single string model output into ... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.flare.prompts.FinishedOutputParser.html |
ff5cf52bc116-6 | prompt – Input PromptValue.
Returns
Structured output
classmethod schema(by_alias: bool = True, ref_template: unicode = '#/definitions/{model}') → DictStrAny¶
classmethod schema_json(*, by_alias: bool = True, ref_template: unicode = '#/definitions/{model}', **dumps_kwargs: Any) → unicode¶
stream(input: Input, config: O... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.flare.prompts.FinishedOutputParser.html |
ff5cf52bc116-7 | 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/chains/langchain.chains.flare.prompts.FinishedOutputParser.html |
ff5cf52bc116-8 | The type of input this runnable accepts specified as a type annotation.
property OutputType: Type[langchain.schema.output_parser.T]¶
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 ... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.flare.prompts.FinishedOutputParser.html |
009cf75efbd1-0 | langchain.chains.moderation.OpenAIModerationChain¶
class langchain.chains.moderation.OpenAIModerationChain[source]¶
Bases: Chain
Pass input through a moderation endpoint.
To use, you should have the openai python package installed, and the
environment variable OPENAI_API_KEY set with your API key.
Any parameters that a... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.moderation.OpenAIModerationChain.html |
009cf75efbd1-1 | This metadata will be associated with each call to this chain,
and passed as arguments to the handlers defined in callbacks.
You can use these to eg identify a specific instance of a chain with its use case.
param model_name: Optional[str] = None¶
Moderation model name to use.
param openai_api_key: Optional[str] = None... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.moderation.OpenAIModerationChain.html |
009cf75efbd1-2 | chain will be returned. Defaults to False.
callbacks – Callbacks to use for this chain run. These will be called in
addition to callbacks passed to the chain during construction, but only
these runtime callbacks will propagate to calls to other objects.
tags – List of string tags to pass to all callbacks. These will be... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.moderation.OpenAIModerationChain.html |
009cf75efbd1-3 | Chain.input_keys except for inputs that will be set by the chain’s
memory.
return_only_outputs – Whether to return only outputs in the
response. If True, only new keys generated by this chain will be
returned. If False, both input keys and new keys generated by this
chain will be returned. Defaults to False.
callbacks ... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.moderation.OpenAIModerationChain.html |
009cf75efbd1-4 | Convenience method for executing chain.
The main difference between this method and Chain.__call__ is that this
method expects inputs to be passed directly in as positional arguments or
keyword arguments, whereas Chain.__call__ expects a single input dictionary
with all the inputs
Parameters
*args – If the chain expect... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.moderation.OpenAIModerationChain.html |
009cf75efbd1-5 | 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/chains/langchain.chains.moderation.OpenAIModerationChain.html |
009cf75efbd1-6 | 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/chains/langchain.chains.moderation.OpenAIModerationChain.html |
009cf75efbd1-7 | 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(**kw... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.moderation.OpenAIModerationChain.html |
009cf75efbd1-8 | 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 configuration.
Parameters
config – A config to use when generating the schem... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.moderation.OpenAIModerationChain.html |
009cf75efbd1-9 | 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 each input.
classmethod parse_file... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.moderation.OpenAIModerationChain.html |
009cf75efbd1-10 | Returns
A dict of the final chain outputs.
run(*args: Any, callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None, tags: Optional[List[str]] = None, metadata: Optional[Dict[str, Any]] = None, **kwargs: Any) → Any¶
Convenience method for executing chain.
The main difference between this method... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.moderation.OpenAIModerationChain.html |
009cf75efbd1-11 | save(file_path: Union[Path, str]) → None¶
Save the chain.
Expects Chain._chain_type property to be implemented and for memory to benull.
Parameters
file_path – Path to file to save the chain to.
Example
chain.save(file_path="path/chain.yaml")
classmethod schema(by_alias: bool = True, ref_template: unicode = '#/definiti... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.moderation.OpenAIModerationChain.html |
009cf75efbd1-12 | Add fallbacks to a runnable, returning a new Runnable.
Parameters
fallbacks – A sequence of runnables to try if the original runnable fails.
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_liste... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.moderation.OpenAIModerationChain.html |
009cf75efbd1-13 | Bind input and output types to a Runnable, returning a new Runnable.
property InputType: Type[langchain.schema.runnable.utils.Input]¶
The type of input this runnable accepts specified as a type annotation.
property OutputType: Type[langchain.schema.runnable.utils.Output]¶
The type of output this runnable produces speci... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.moderation.OpenAIModerationChain.html |
00fc2981231d-0 | langchain.chains.router.multi_retrieval_qa.MultiRetrievalQAChain¶
class langchain.chains.router.multi_retrieval_qa.MultiRetrievalQAChain[source]¶
Bases: MultiRouteChain
A multi-route chain that uses an LLM router chain to choose amongst retrieval
qa chains.
Create a new model by parsing and validating input data from k... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.router.multi_retrieval_qa.MultiRetrievalQAChain.html |
00fc2981231d-1 | and passed as arguments to the handlers defined in callbacks.
You can use these to eg identify a specific instance of a chain with its use case.
param router_chain: LLMRouterChain [Required]¶
Chain for deciding a destination chain and the input to it.
param silent_errors: bool = False¶
If True, use default_chain when a... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.router.multi_retrieval_qa.MultiRetrievalQAChain.html |
00fc2981231d-2 | chain will be returned. Defaults to False.
callbacks – Callbacks to use for this chain run. These will be called in
addition to callbacks passed to the chain during construction, but only
these runtime callbacks will propagate to calls to other objects.
tags – List of string tags to pass to all callbacks. These will be... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.router.multi_retrieval_qa.MultiRetrievalQAChain.html |
00fc2981231d-3 | Chain.input_keys except for inputs that will be set by the chain’s
memory.
return_only_outputs – Whether to return only outputs in the
response. If True, only new keys generated by this chain will be
returned. If False, both input keys and new keys generated by this
chain will be returned. Defaults to False.
callbacks ... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.router.multi_retrieval_qa.MultiRetrievalQAChain.html |
00fc2981231d-4 | Convenience method for executing chain.
The main difference between this method and Chain.__call__ is that this
method expects inputs to be passed directly in as positional arguments or
keyword arguments, whereas Chain.__call__ expects a single input dictionary
with all the inputs
Parameters
*args – If the chain expect... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.router.multi_retrieval_qa.MultiRetrievalQAChain.html |
00fc2981231d-5 | 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/chains/langchain.chains.router.multi_retrieval_qa.MultiRetrievalQAChain.html |
00fc2981231d-6 | 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/chains/langchain.chains.router.multi_retrieval_qa.MultiRetrievalQAChain.html |
00fc2981231d-7 | 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(**kw... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.router.multi_retrieval_qa.MultiRetrievalQAChain.html |
00fc2981231d-8 | Get the namespace of the langchain object.
For example, if the class is langchain.llms.openai.OpenAI, then the
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 th... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.router.multi_retrieval_qa.MultiRetrievalQAChain.html |
00fc2981231d-9 | 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, exclude_unset: bool = False, exclude_defa... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.router.multi_retrieval_qa.MultiRetrievalQAChain.html |
00fc2981231d-10 | Parameters
inputs – Dictionary of raw inputs, or single input if chain expects
only one param. Should contain all inputs specified in
Chain.input_keys except for inputs that will be set by the chain’s
memory.
Returns
A dictionary of all inputs, including those added by the chain’s memory.
prep_outputs(inputs: Dict[str,... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.router.multi_retrieval_qa.MultiRetrievalQAChain.html |
00fc2981231d-11 | these runtime tags will propagate to calls to other objects.
**kwargs – If the chain expects multiple inputs, they can be passed in
directly as keyword arguments.
Returns
The chain output.
Example
# Suppose we have a single-input chain that takes a 'question' string:
chain.run("What's the temperature in Boise, Idaho?")... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.router.multi_retrieval_qa.MultiRetrievalQAChain.html |
00fc2981231d-12 | 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/chains/langchain.chains.router.multi_retrieval_qa.MultiRetrievalQAChain.html |
00fc2981231d-13 | 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/chains/langchain.chains.router.multi_retrieval_qa.MultiRetrievalQAChain.html |
00fc2981231d-14 | 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/chains/langchain.chains.router.multi_retrieval_qa.MultiRetrievalQAChain.html |
31fcd879db42-0 | langchain.chains.openai_functions.base.get_openai_output_parser¶
langchain.chains.openai_functions.base.get_openai_output_parser(functions: Sequence[Union[Dict[str, Any], Type[BaseModel], Callable]]) → Union[BaseOutputParser, BaseGenerationOutputParser][source]¶
Get the appropriate function output parser given the user... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.openai_functions.base.get_openai_output_parser.html |
3bdc1c890f1f-0 | langchain.chains.conversational_retrieval.base.InputType¶
class langchain.chains.conversational_retrieval.base.InputType[source]¶
Bases: BaseModel
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to form a valid model.
param chat_h... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.conversational_retrieval.base.InputType.html |
3bdc1c890f1f-1 | deep – set to True to make a deep copy of the model
Returns
new model instance
dict(*, 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, ex... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.conversational_retrieval.base.InputType.html |
3bdc1c890f1f-2 | classmethod schema(by_alias: bool = True, ref_template: unicode = '#/definitions/{model}') → DictStrAny¶
classmethod schema_json(*, by_alias: bool = True, ref_template: unicode = '#/definitions/{model}', **dumps_kwargs: Any) → unicode¶
classmethod update_forward_refs(**localns: Any) → None¶
Try to update ForwardRefs on... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.conversational_retrieval.base.InputType.html |
fd3d37402eaa-0 | langchain.chains.llm_requests.LLMRequestsChain¶
class langchain.chains.llm_requests.LLMRequestsChain[source]¶
Bases: Chain
Chain that requests a URL and then uses an LLM to parse results.
Security Note: This chain can make GET requests to arbitrary URLs,including internal URLs.
Control access to who can run this chain ... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.llm_requests.LLMRequestsChain.html |
fd3d37402eaa-1 | You can use these to eg identify a specific instance of a chain with its use case.
param requests_wrapper: TextRequestsWrapper [Optional]¶
param tags: Optional[List[str]] = None¶
Optional list of tags associated with the chain. Defaults to None.
These tags will be associated with each call to this chain,
and passed as ... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.llm_requests.LLMRequestsChain.html |
fd3d37402eaa-2 | these runtime callbacks will propagate to calls to other objects.
tags – List of string tags to pass to all callbacks. These will be passed in
addition to tags passed to the chain during construction, but only
these runtime tags will propagate to calls to other objects.
metadata – Optional metadata associated with the ... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.llm_requests.LLMRequestsChain.html |
fd3d37402eaa-3 | returned. If False, both input keys and new keys generated by this
chain will be returned. Defaults to False.
callbacks – Callbacks to use for this chain run. These will be called in
addition to callbacks passed to the chain during construction, but only
these runtime callbacks will propagate to calls to other objects.... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.llm_requests.LLMRequestsChain.html |
fd3d37402eaa-4 | method expects inputs to be passed directly in as positional arguments or
keyword arguments, whereas Chain.__call__ expects a single input dictionary
with all the inputs
Parameters
*args – If the chain expects a single input, it can be passed in as the
sole positional argument.
callbacks – Callbacks to use for this cha... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.llm_requests.LLMRequestsChain.html |
fd3d37402eaa-5 | 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/chains/langchain.chains.llm_requests.LLMRequestsChain.html |
fd3d37402eaa-6 | 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/chains/langchain.chains.llm_requests.LLMRequestsChain.html |
fd3d37402eaa-7 | 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(**kw... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.llm_requests.LLMRequestsChain.html |
fd3d37402eaa-8 | 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 configuration.
Parameters
config – A config to use when generating the schem... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.llm_requests.LLMRequestsChain.html |
fd3d37402eaa-9 | 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 each input.
classmethod parse_file... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.llm_requests.LLMRequestsChain.html |
fd3d37402eaa-10 | Returns
A dict of the final chain outputs.
run(*args: Any, callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None, tags: Optional[List[str]] = None, metadata: Optional[Dict[str, Any]] = None, **kwargs: Any) → Any¶
Convenience method for executing chain.
The main difference between this method... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.llm_requests.LLMRequestsChain.html |
fd3d37402eaa-11 | save(file_path: Union[Path, str]) → None¶
Save the chain.
Expects Chain._chain_type property to be implemented and for memory to benull.
Parameters
file_path – Path to file to save the chain to.
Example
chain.save(file_path="path/chain.yaml")
classmethod schema(by_alias: bool = True, ref_template: unicode = '#/definiti... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.llm_requests.LLMRequestsChain.html |
fd3d37402eaa-12 | Add fallbacks to a runnable, returning a new Runnable.
Parameters
fallbacks – A sequence of runnables to try if the original runnable fails.
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_liste... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.llm_requests.LLMRequestsChain.html |
fd3d37402eaa-13 | Bind input and output types to a Runnable, returning a new Runnable.
property InputType: Type[langchain.schema.runnable.utils.Input]¶
The type of input this runnable accepts specified as a type annotation.
property OutputType: Type[langchain.schema.runnable.utils.Output]¶
The type of output this runnable produces speci... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.llm_requests.LLMRequestsChain.html |
68eac2854fa4-0 | langchain.chains.router.llm_router.RouterOutputParser¶
class langchain.chains.router.llm_router.RouterOutputParser[source]¶
Bases: BaseOutputParser[Dict[str, str]]
Parser for output of router chain in the multi-prompt chain.
param default_destination: str = 'DEFAULT'¶
param next_inputs_inner_key: str = 'input'¶
param n... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.router.llm_router.RouterOutputParser.html |
68eac2854fa4-1 | Parameters
result – A list of Generations to be parsed. The Generations are assumed
to be different candidate outputs for a single model input.
Returns
Structured output.
async astream(input: Input, config: Optional[RunnableConfig] = None, **kwargs: Optional[Any]) → AsyncIterator[Output]¶
Default implementation of astr... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.router.llm_router.RouterOutputParser.html |
68eac2854fa4-2 | 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]¶
Default implementation runs invoke in parallel using a thread pool executor.
The default implementation of batch w... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.router.llm_router.RouterOutputParser.html |
68eac2854fa4-3 | 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/chains/langchain.chains.router.llm_router.RouterOutputParser.html |
68eac2854fa4-4 | 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/chains/langchain.chains.router.llm_router.RouterOutputParser.html |
68eac2854fa4-5 | 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/chains/langchain.chains.router.llm_router.RouterOutputParser.html |
68eac2854fa4-6 | The prompt is largely provided in the event the OutputParser wants
to retry or fix the output in some way, and needs information from
the prompt to do so.
Parameters
completion – String output of a language model.
prompt – Input PromptValue.
Returns
Structured output
classmethod schema(by_alias: bool = True, ref_templa... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.router.llm_router.RouterOutputParser.html |
68eac2854fa4-7 | Add fallbacks to a runnable, returning a new Runnable.
Parameters
fallbacks – A sequence of runnables to try if the original runnable fails.
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_liste... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.router.llm_router.RouterOutputParser.html |
68eac2854fa4-8 | Bind input and output types to a Runnable, returning a new Runnable.
property InputType: Any¶
The type of input this runnable accepts specified as a type annotation.
property OutputType: Type[langchain.schema.output_parser.T]¶
The type of output this runnable produces specified as a type annotation.
property config_spe... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.router.llm_router.RouterOutputParser.html |
d05cf5c56d31-0 | langchain.chains.graph_qa.cypher.construct_schema¶
langchain.chains.graph_qa.cypher.construct_schema(structured_schema: Dict[str, Any], include_types: List[str], exclude_types: List[str]) → str[source]¶
Filter the schema based on included or excluded types | lang/api.python.langchain.com/en/latest/chains/langchain.chains.graph_qa.cypher.construct_schema.html |
cb2572552a7b-0 | langchain.chains.graph_qa.neptune_cypher.NeptuneOpenCypherQAChain¶
class langchain.chains.graph_qa.neptune_cypher.NeptuneOpenCypherQAChain[source]¶
Bases: Chain
Chain for question-answering against a Neptune graph
by generating openCypher statements.
Security note: Make sure that the database connection uses credential... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.graph_qa.neptune_cypher.NeptuneOpenCypherQAChain.html |
cb2572552a7b-1 | param graph: NeptuneGraph [Required]¶
param memory: Optional[BaseMemory] = None¶
Optional memory object. Defaults to None.
Memory is a class that gets called at the start
and at the end of every chain. At the start, memory loads variables and passes
them along in the chain. At the end, it saves any returned variables.
... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.graph_qa.neptune_cypher.NeptuneOpenCypherQAChain.html |
cb2572552a7b-2 | accessible via langchain.globals.get_verbose().
__call__(inputs: Union[Dict[str, Any], Any], return_only_outputs: bool = False, callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None, *, tags: Optional[List[str]] = None, metadata: Optional[Dict[str, Any]] = None, run_name: Optional[str] = Non... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.graph_qa.neptune_cypher.NeptuneOpenCypherQAChain.html |
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