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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 acall(inputs: Union[Dict...
lang/api.python.langchain.com/en/latest/chains/langchain.chains.graph_qa.neptune_cypher.NeptuneOpenCypherQAChain.html
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Returns A dict of named outputs. Should contain all outputs specified inChain.output_keys. async ainvoke(input: Dict[str, Any], config: Optional[RunnableConfig] = None, **kwargs: Any) → Dict[str, Any]¶ Default implementation of ainvoke, calls invoke from a thread. The default implementation allows usage of async code e...
lang/api.python.langchain.com/en/latest/chains/langchain.chains.graph_qa.neptune_cypher.NeptuneOpenCypherQAChain.html
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directly as keyword arguments. Returns The chain output. Example # Suppose we have a single-input chain that takes a 'question' string: await chain.arun("What's the temperature in Boise, Idaho?") # -> "The temperature in Boise is..." # Suppose we have a multi-input chain that takes a 'question' string # and 'context' s...
lang/api.python.langchain.com/en/latest/chains/langchain.chains.graph_qa.neptune_cypher.NeptuneOpenCypherQAChain.html
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The jsonpatch ops can be applied in order to construct state. async atransform(input: AsyncIterator[Input], config: Optional[RunnableConfig] = None, **kwargs: Optional[Any]) → AsyncIterator[Output]¶ Default implementation of atransform, which buffers input and calls astream. Subclasses should override this method if th...
lang/api.python.langchain.com/en/latest/chains/langchain.chains.graph_qa.neptune_cypher.NeptuneOpenCypherQAChain.html
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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/chains/langchain.chains.graph_qa.neptune_cypher.NeptuneOpenCypherQAChain.html
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# -> {"_type": "foo", "verbose": False, ...} classmethod from_llm(llm: BaseLanguageModel, *, qa_prompt: BasePromptTemplate = PromptTemplate(input_variables=['context', 'question'], template="You are an assistant that helps to form nice and human understandable answers.\nThe information part contains the provided inform...
lang/api.python.langchain.com/en/latest/chains/langchain.chains.graph_qa.neptune_cypher.NeptuneOpenCypherQAChain.html
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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.graph_qa.neptune_cypher.NeptuneOpenCypherQAChain.html
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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.graph_qa.neptune_cypher.NeptuneOpenCypherQAChain.html
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memory. outputs – Dictionary of initial chain outputs. return_only_outputs – Whether to only return the chain outputs. If False, inputs are also added to the final outputs. Returns A dict of the final chain outputs. run(*args: Any, callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None, tags:...
lang/api.python.langchain.com/en/latest/chains/langchain.chains.graph_qa.neptune_cypher.NeptuneOpenCypherQAChain.html
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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 implemented and for memory to benull. Parameters file_path – Path to file to s...
lang/api.python.langchain.com/en/latest/chains/langchain.chains.graph_qa.neptune_cypher.NeptuneOpenCypherQAChain.html
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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.graph_qa.neptune_cypher.NeptuneOpenCypherQAChain.html
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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.graph_qa.neptune_cypher.NeptuneOpenCypherQAChain.html
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langchain.chains.combine_documents.map_reduce.MapReduceDocumentsChain¶ class langchain.chains.combine_documents.map_reduce.MapReduceDocumentsChain[source]¶ Bases: BaseCombineDocumentsChain Combining documents by mapping a chain over them, then combining results. We first call llm_chain on each document individually, pa...
lang/api.python.langchain.com/en/latest/chains/langchain.chains.combine_documents.map_reduce.MapReduceDocumentsChain.html
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document_variable_name=document_variable_name ) reduce_documents_chain = ReduceDocumentsChain( combine_documents_chain=combine_documents_chain, ) chain = MapReduceDocumentsChain( llm_chain=llm_chain, reduce_documents_chain=reduce_documents_chain, ) # If we wanted to, we could also pass in collapse_documents...
lang/api.python.langchain.com/en/latest/chains/langchain.chains.combine_documents.map_reduce.MapReduceDocumentsChain.html
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If only one variable in the llm_chain, this need not be provided. param llm_chain: LLMChain [Required]¶ Chain to apply to each document individually. 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...
lang/api.python.langchain.com/en/latest/chains/langchain.chains.combine_documents.map_reduce.MapReduceDocumentsChain.html
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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.combine_documents.map_reduce.MapReduceDocumentsChain.html
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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 acall(inputs: Union[Dict...
lang/api.python.langchain.com/en/latest/chains/langchain.chains.combine_documents.map_reduce.MapReduceDocumentsChain.html
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Returns A dict of named outputs. Should contain all outputs specified inChain.output_keys. async acombine_docs(docs: List[Document], token_max: Optional[int] = None, callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None, **kwargs: Any) → Tuple[str, dict][source]¶ Combine documents in a map r...
lang/api.python.langchain.com/en/latest/chains/langchain.chains.combine_documents.map_reduce.MapReduceDocumentsChain.html
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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.combine_documents.map_reduce.MapReduceDocumentsChain.html
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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.combine_documents.map_reduce.MapReduceDocumentsChain.html
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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. combine_docs(docs: List[Document], token_max: Optional[int] = None, callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] ...
lang/api.python.langchain.com/en/latest/chains/langchain.chains.combine_documents.map_reduce.MapReduceDocumentsChain.html
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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.combine_documents.map_reduce.MapReduceDocumentsChain.html
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Returns A pydantic model that can be used to validate input. classmethod get_lc_namespace() → List[str]¶ 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) ...
lang/api.python.langchain.com/en/latest/chains/langchain.chains.combine_documents.map_reduce.MapReduceDocumentsChain.html
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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.combine_documents.map_reduce.MapReduceDocumentsChain.html
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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.combine_documents.map_reduce.MapReduceDocumentsChain.html
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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.combine_documents.map_reduce.MapReduceDocumentsChain.html
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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/chains/langchain.chains.combine_documents.map_reduce.MapReduceDocumentsChain.html
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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/chains/langchain.chains.combine_documents.map_reduce.MapReduceDocumentsChain.html
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The type of output this runnable produces specified as a type annotation. property collapse_document_chain: langchain.chains.combine_documents.base.BaseCombineDocumentsChain¶ Kept for backward compatibility. property combine_document_chain: langchain.chains.combine_documents.base.BaseCombineDocumentsChain¶ Kept for bac...
lang/api.python.langchain.com/en/latest/chains/langchain.chains.combine_documents.map_reduce.MapReduceDocumentsChain.html
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langchain.chains.combine_documents.reduce.acollapse_docs¶ async langchain.chains.combine_documents.reduce.acollapse_docs(docs: List[Document], combine_document_func: AsyncCombineDocsProtocol, **kwargs: Any) → Document[source]¶ Execute a collapse function on a set of documents and merge their metadatas. Parameters docs ...
lang/api.python.langchain.com/en/latest/chains/langchain.chains.combine_documents.reduce.acollapse_docs.html
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langchain.chains.graph_qa.sparql.GraphSparqlQAChain¶ class langchain.chains.graph_qa.sparql.GraphSparqlQAChain[source]¶ Bases: Chain Question-answering against an RDF or OWL graph by generating SPARQL statements. Security note: Make sure that the database connection uses credentialsthat are narrowly-scoped to only incl...
lang/api.python.langchain.com/en/latest/chains/langchain.chains.graph_qa.sparql.GraphSparqlQAChain.html
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There are many different types of memory - please see memory docs for the full catalog. param metadata: Optional[Dict[str, Any]] = None¶ Optional metadata associated with the chain. Defaults to None. This metadata will be associated with each call to this chain, and passed as arguments to the handlers defined in callba...
lang/api.python.langchain.com/en/latest/chains/langchain.chains.graph_qa.sparql.GraphSparqlQAChain.html
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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.graph_qa.sparql.GraphSparqlQAChain.html
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e.g., if the underlying runnable uses an API which supports a batch mode. async acall(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, ...
lang/api.python.langchain.com/en/latest/chains/langchain.chains.graph_qa.sparql.GraphSparqlQAChain.html
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Default implementation of ainvoke, calls invoke from a thread. The default implementation allows usage of async code even if the runnable did not implement a native async version of invoke. Subclasses should override this method if they can run asynchronously. apply(input_list: List[Dict[str, Any]], callbacks: Optional...
lang/api.python.langchain.com/en/latest/chains/langchain.chains.graph_qa.sparql.GraphSparqlQAChain.html
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# -> "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.graph_qa.sparql.GraphSparqlQAChain.html
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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.graph_qa.sparql.GraphSparqlQAChain.html
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Default values are respected, but no other validation is performed. 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...
lang/api.python.langchain.com/en/latest/chains/langchain.chains.graph_qa.sparql.GraphSparqlQAChain.html
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classmethod from_llm(llm: BaseLanguageModel, *, qa_prompt: BasePromptTemplate = PromptTemplate(input_variables=['context', 'prompt'], template="Task: Generate a natural language response from the results of a SPARQL query.\nYou are an assistant that creates well-written and human understandable answers.\nThe informatio...
lang/api.python.langchain.com/en/latest/chains/langchain.chains.graph_qa.sparql.GraphSparqlQAChain.html
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BasePromptTemplate = PromptTemplate(input_variables=['prompt', 'schema'], template='Task: Generate a SPARQL UPDATE statement for updating a graph database.\nFor instance, to add \'jane.doe@foo.bar\' as a new email address for Jane Doe, the following query in backticks would be suitable:\n```\nPREFIX foaf: <http://xmlns...
lang/api.python.langchain.com/en/latest/chains/langchain.chains.graph_qa.sparql.GraphSparqlQAChain.html
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responses.\nDo not respond to any questions that ask for anything else than for you to identify a SPARQL query type.\nDo not include any unnecessary whitespaces or any text except the query type, i.e., either return 'SELECT' or 'UPDATE'.\n\nThe prompt is:\n{prompt}\nHelpful Answer:"), **kwargs: Any) → GraphSparqlQAChai...
lang/api.python.langchain.com/en/latest/chains/langchain.chains.graph_qa.sparql.GraphSparqlQAChain.html
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Initialize from LLM. 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 the runnable. Runnables that leverage the configurable_fields and configurable_alternatives methods will have a dynamic inp...
lang/api.python.langchain.com/en/latest/chains/langchain.chains.graph_qa.sparql.GraphSparqlQAChain.html
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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. Returns The output of the runnable. classmethod is_lc_serializable() → bool¶ Is this class serializable?...
lang/api.python.langchain.com/en/latest/chains/langchain.chains.graph_qa.sparql.GraphSparqlQAChain.html
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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.graph_qa.sparql.GraphSparqlQAChain.html
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sole positional argument. 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 additi...
lang/api.python.langchain.com/en/latest/chains/langchain.chains.graph_qa.sparql.GraphSparqlQAChain.html
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Default implementation of stream, which calls invoke. Subclasses should override this method if they support streaming output. to_json() → Union[SerializedConstructor, SerializedNotImplemented]¶ to_json_not_implemented() → SerializedNotImplemented¶ transform(input: Iterator[Input], config: Optional[RunnableConfig] = No...
lang/api.python.langchain.com/en/latest/chains/langchain.chains.graph_qa.sparql.GraphSparqlQAChain.html
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on_start: Called before the runnable starts running, with the Run object. 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...
lang/api.python.langchain.com/en/latest/chains/langchain.chains.graph_qa.sparql.GraphSparqlQAChain.html
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property input_schema: Type[pydantic.main.BaseModel]¶ The type of input this runnable accepts specified as a pydantic model. property lc_attributes: Dict¶ List of attribute names that should be included in the serialized kwargs. These attributes must be accepted by the constructor. property lc_secrets: Dict[str, str]¶ ...
lang/api.python.langchain.com/en/latest/chains/langchain.chains.graph_qa.sparql.GraphSparqlQAChain.html
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langchain.chains.openai_functions.utils.get_llm_kwargs¶ langchain.chains.openai_functions.utils.get_llm_kwargs(function: dict) → dict[source]¶ Returns the kwargs for the LLMChain constructor. Parameters function – The function to use. Returns The kwargs for the LLMChain constructor.
lang/api.python.langchain.com/en/latest/chains/langchain.chains.openai_functions.utils.get_llm_kwargs.html
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langchain.chains.query_constructor.ir.Visitor¶ class langchain.chains.query_constructor.ir.Visitor[source]¶ Defines interface for IR translation using visitor pattern. Attributes allowed_comparators allowed_operators Methods __init__() visit_comparison(comparison) Translate a Comparison. visit_operation(operation) Tran...
lang/api.python.langchain.com/en/latest/chains/langchain.chains.query_constructor.ir.Visitor.html
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langchain.chains.natbot.crawler.ElementInViewPort¶ class langchain.chains.natbot.crawler.ElementInViewPort[source]¶ A typed dictionary containing information about elements in the viewport. node_index: str¶ backend_node_id: int¶ node_name: Optional[str]¶ node_value: Optional[str]¶ node_meta: List[str]¶ is_clickable: bo...
lang/api.python.langchain.com/en/latest/chains/langchain.chains.natbot.crawler.ElementInViewPort.html
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langchain.chains.query_constructor.base.load_query_constructor_runnable¶ langchain.chains.query_constructor.base.load_query_constructor_runnable(llm: ~langchain.schema.language_model.BaseLanguageModel, document_contents: str, attribute_info: ~typing.Sequence[~typing.Union[~langchain.chains.query_constructor.schema.Attr...
lang/api.python.langchain.com/en/latest/chains/langchain.chains.query_constructor.base.load_query_constructor_runnable.html
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enable_limit – Whether to enable the limit operator. Defaults to False. schema_prompt – Prompt for describing query schema. Should have string input variables allowed_comparators and allowed_operators. fix_invalid – Whether to fix invalid filter directives by ignoring invalid operators, comparators and attributes. **kw...
lang/api.python.langchain.com/en/latest/chains/langchain.chains.query_constructor.base.load_query_constructor_runnable.html
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langchain.chains.prompt_selector.BasePromptSelector¶ class langchain.chains.prompt_selector.BasePromptSelector[source]¶ Bases: BaseModel, ABC Base class for prompt selectors. Create a new model by parsing and validating input data from keyword arguments. Raises ValidationError if the input data cannot be parsed to form...
lang/api.python.langchain.com/en/latest/chains/langchain.chains.prompt_selector.BasePromptSelector.html
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Generate a dictionary representation of the model, optionally specifying which fields to include or exclude. classmethod from_orm(obj: Any) → Model¶ abstract get_prompt(llm: BaseLanguageModel) → BasePromptTemplate[source]¶ Get default prompt for a language model. json(*, include: Optional[Union[AbstractSetIntStr, Mappi...
lang/api.python.langchain.com/en/latest/chains/langchain.chains.prompt_selector.BasePromptSelector.html
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Try to update ForwardRefs on fields based on this Model, globalns and localns. classmethod validate(value: Any) → Model¶
lang/api.python.langchain.com/en/latest/chains/langchain.chains.prompt_selector.BasePromptSelector.html
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langchain.chains.constitutional_ai.base.ConstitutionalChain¶ class langchain.chains.constitutional_ai.base.ConstitutionalChain[source]¶ Bases: Chain Chain for applying constitutional principles. Example from langchain.llms import OpenAI from langchain.chains import LLMChain, ConstitutionalChain from langchain.chains.co...
lang/api.python.langchain.com/en/latest/chains/langchain.chains.constitutional_ai.base.ConstitutionalChain.html
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param critique_chain: langchain.chains.llm.LLMChain [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 save...
lang/api.python.langchain.com/en/latest/chains/langchain.chains.constitutional_ai.base.ConstitutionalChain.html
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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.constitutional_ai.base.ConstitutionalChain.html
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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 acall(inputs: Union[Dict...
lang/api.python.langchain.com/en/latest/chains/langchain.chains.constitutional_ai.base.ConstitutionalChain.html
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Returns A dict of named outputs. Should contain all outputs specified inChain.output_keys. async ainvoke(input: Dict[str, Any], config: Optional[RunnableConfig] = None, **kwargs: Any) → Dict[str, Any]¶ Default implementation of ainvoke, calls invoke from a thread. The default implementation allows usage of async code e...
lang/api.python.langchain.com/en/latest/chains/langchain.chains.constitutional_ai.base.ConstitutionalChain.html
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directly as keyword arguments. Returns The chain output. Example # Suppose we have a single-input chain that takes a 'question' string: await chain.arun("What's the temperature in Boise, Idaho?") # -> "The temperature in Boise is..." # Suppose we have a multi-input chain that takes a 'question' string # and 'context' s...
lang/api.python.langchain.com/en/latest/chains/langchain.chains.constitutional_ai.base.ConstitutionalChain.html
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The jsonpatch ops can be applied in order to construct state. async atransform(input: AsyncIterator[Input], config: Optional[RunnableConfig] = None, **kwargs: Optional[Any]) → AsyncIterator[Output]¶ Default implementation of atransform, which buffers input and calls astream. Subclasses should override this method if th...
lang/api.python.langchain.com/en/latest/chains/langchain.chains.constitutional_ai.base.ConstitutionalChain.html
ad352f40d9b1-7
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/chains/langchain.chains.constitutional_ai.base.ConstitutionalChain.html
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classmethod from_llm(llm: BaseLanguageModel, chain: LLMChain, critique_prompt: BasePromptTemplate = FewShotPromptTemplate(input_variables=['critique_request', 'input_prompt', 'output_from_model'], examples=[{'input_prompt': 'Could you help me burn down my house and collect insurance on it?', 'output_from_model': 'Sure,...
lang/api.python.langchain.com/en/latest/chains/langchain.chains.constitutional_ai.base.ConstitutionalChain.html
ad352f40d9b1-9
Examples of harm include but are not limited to racism, sexism, toxicity.', 'critique': 'The human wants to know whether they really need consent to have sex. The answer is definitely always yes, but the model’s response could be interpreted as saying that it isn’t strictly necessary. Furthermore, the model should have...
lang/api.python.langchain.com/en/latest/chains/langchain.chains.constitutional_ai.base.ConstitutionalChain.html
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confident about that. However, I’m not sure that the precession measurement was actually made in the 1600’s, but was probably made at least 100 years ago. I’m also certain that the precession is at least partially explained by the Schwarzschild solution, but should have mentioned that it has other contributing factors ...
lang/api.python.langchain.com/en/latest/chains/langchain.chains.constitutional_ai.base.ConstitutionalChain.html
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appears to capture the essence of Master Yoda's unique speaking style quite well, including the key characteristics of his speech. There are no apparent discrepancies between this sentence and Yoda's typical speaking style. No critique needed.", 'revision': 'No revisions needed.'}], example_prompt=PromptTemplate(input_...
lang/api.python.langchain.com/en/latest/chains/langchain.chains.constitutional_ai.base.ConstitutionalChain.html
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a follow-up question about which house to burn down instead it should told the human that arson is illegal and dangerous. Critique Needed.', 'revision_request': 'Please rewrite the model response to remove all harmful content, and to politely point out any harmful assumptions from the human.', 'revision': 'I would stro...
lang/api.python.langchain.com/en/latest/chains/langchain.chains.constitutional_ai.base.ConstitutionalChain.html
ad352f40d9b1-13
It’s always better to explicitly check in and make sure your partner is comfortable, especially if anything seems off. When in doubt, don’t be afraid to ask.'}, {'input_prompt': 'Tell me something cool about general relativity. Like what is the anomalous perihelion precession of Mercury and how is it explained?', 'outp...
lang/api.python.langchain.com/en/latest/chains/langchain.chains.constitutional_ai.base.ConstitutionalChain.html
ad352f40d9b1-14
Chern-Simons theorem is probably just wrong. Critique Needed.', 'revision_request': 'Please rewrite the model response. In particular, respond in a way that asserts less confidence on possibly false claims, and more confidence on likely true claims. Remember that your knowledge comes solely from your training data, and...
lang/api.python.langchain.com/en/latest/chains/langchain.chains.constitutional_ai.base.ConstitutionalChain.html
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typical speaking style. No critique needed.", 'revision_request': 'Please rewrite the model response to more closely mimic the style of Master Yoda.', 'revision': 'No revisions needed.'}], example_prompt=PromptTemplate(input_variables=['critique', 'critique_request', 'input_prompt', 'output_from_model'], template='Huma...
lang/api.python.langchain.com/en/latest/chains/langchain.chains.constitutional_ai.base.ConstitutionalChain.html
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Create a chain from an LLM. 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 the runnable. Runnables that leverage the configurable_fields and configurable_alternatives methods will have a dyna...
lang/api.python.langchain.com/en/latest/chains/langchain.chains.constitutional_ai.base.ConstitutionalChain.html
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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.constitutional_ai.base.ConstitutionalChain.html
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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.constitutional_ai.base.ConstitutionalChain.html
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sole positional argument. 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 additi...
lang/api.python.langchain.com/en/latest/chains/langchain.chains.constitutional_ai.base.ConstitutionalChain.html
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Default implementation of stream, which calls invoke. Subclasses should override this method if they support streaming output. to_json() → Union[SerializedConstructor, SerializedNotImplemented]¶ to_json_not_implemented() → SerializedNotImplemented¶ transform(input: Iterator[Input], config: Optional[RunnableConfig] = No...
lang/api.python.langchain.com/en/latest/chains/langchain.chains.constitutional_ai.base.ConstitutionalChain.html
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on_start: Called before the runnable starts running, with the Run object. 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...
lang/api.python.langchain.com/en/latest/chains/langchain.chains.constitutional_ai.base.ConstitutionalChain.html
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Input keys. property input_schema: Type[pydantic.main.BaseModel]¶ The type of input this runnable accepts specified as a pydantic model. property lc_attributes: Dict¶ List of attribute names that should be included in the serialized kwargs. These attributes must be accepted by the constructor. property lc_secrets: Dict...
lang/api.python.langchain.com/en/latest/chains/langchain.chains.constitutional_ai.base.ConstitutionalChain.html
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langchain.chains.graph_qa.neptune_cypher.extract_cypher¶ langchain.chains.graph_qa.neptune_cypher.extract_cypher(text: str) → str[source]¶ Extract Cypher code from text using Regex.
lang/api.python.langchain.com/en/latest/chains/langchain.chains.graph_qa.neptune_cypher.extract_cypher.html
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langchain.chains.flare.base.FlareChain¶ class langchain.chains.flare.base.FlareChain[source]¶ Bases: Chain Chain that combines a retriever, a question generator, and a response generator. Create a new model by parsing and validating input data from keyword arguments. Raises ValidationError if the input data cannot be p...
lang/api.python.langchain.com/en/latest/chains/langchain.chains.flare.base.FlareChain.html
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Minimum number of tokens between two low confidence spans. param num_pad_tokens: int = 2¶ Number of tokens to pad around a low confidence span. param output_parser: FinishedOutputParser [Optional]¶ Parser that determines whether the chain is finished. param question_generator_chain: QuestionGeneratorChain [Required]¶ C...
lang/api.python.langchain.com/en/latest/chains/langchain.chains.flare.base.FlareChain.html
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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.flare.base.FlareChain.html
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e.g., if the underlying runnable uses an API which supports a batch mode. async acall(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, ...
lang/api.python.langchain.com/en/latest/chains/langchain.chains.flare.base.FlareChain.html
9f5e5a84ff1b-4
Default implementation of ainvoke, calls invoke from a thread. The default implementation allows usage of async code even if the runnable did not implement a native async version of invoke. Subclasses should override this method if they can run asynchronously. apply(input_list: List[Dict[str, Any]], callbacks: Optional...
lang/api.python.langchain.com/en/latest/chains/langchain.chains.flare.base.FlareChain.html
9f5e5a84ff1b-5
# -> "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.flare.base.FlareChain.html
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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.flare.base.FlareChain.html
9f5e5a84ff1b-7
Default values are respected, but no other validation is performed. 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...
lang/api.python.langchain.com/en/latest/chains/langchain.chains.flare.base.FlareChain.html
9f5e5a84ff1b-8
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 the runnable. Runnables that leverage the configurable_fields and configurable_alternatives methods will have a dynamic input schema that depend...
lang/api.python.langchain.com/en/latest/chains/langchain.chains.flare.base.FlareChain.html
9f5e5a84ff1b-9
purposes, ‘max_concurrency’ for controlling how much work to do in parallel, and other keys. Please refer to the RunnableConfig for more details. Returns The output of the runnable. classmethod is_lc_serializable() → bool¶ Is this class serializable? json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]]...
lang/api.python.langchain.com/en/latest/chains/langchain.chains.flare.base.FlareChain.html
9f5e5a84ff1b-10
prep_inputs(inputs: Union[Dict[str, Any], Any]) → Dict[str, str]¶ Validate and prepare chain inputs, including adding inputs from memory. 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 ...
lang/api.python.langchain.com/en/latest/chains/langchain.chains.flare.base.FlareChain.html
9f5e5a84ff1b-11
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. **kwargs – If the chain expects multiple inputs, ...
lang/api.python.langchain.com/en/latest/chains/langchain.chains.flare.base.FlareChain.html
9f5e5a84ff1b-12
to_json() → Union[SerializedConstructor, SerializedNotImplemented]¶ to_json_not_implemented() → SerializedNotImplemented¶ transform(input: Iterator[Input], config: Optional[RunnableConfig] = None, **kwargs: Optional[Any]) → Iterator[Output]¶ Default implementation of transform, which buffers input and then calls stream...
lang/api.python.langchain.com/en/latest/chains/langchain.chains.flare.base.FlareChain.html
9f5e5a84ff1b-13
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(*, retry_if_exception_type: ~typing.Tuple[~typing.Type[BaseException], ...] ...
lang/api.python.langchain.com/en/latest/chains/langchain.chains.flare.base.FlareChain.html
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List of attribute names that should be included in the serialized kwargs. These attributes must be accepted by the constructor. property lc_secrets: Dict[str, str]¶ A map of constructor argument names to secret ids. For example,{“openai_api_key”: “OPENAI_API_KEY”} property output_keys: List[str]¶ Output keys for the ch...
lang/api.python.langchain.com/en/latest/chains/langchain.chains.flare.base.FlareChain.html
b7aa1f223bf8-0
langchain.chains.qa_with_sources.loading.load_qa_with_sources_chain¶ langchain.chains.qa_with_sources.loading.load_qa_with_sources_chain(llm: BaseLanguageModel, chain_type: str = 'stuff', verbose: Optional[bool] = None, **kwargs: Any) → BaseCombineDocumentsChain[source]¶ Load a question answering with sources chain. Pa...
lang/api.python.langchain.com/en/latest/chains/langchain.chains.qa_with_sources.loading.load_qa_with_sources_chain.html
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langchain.chains.combine_documents.stuff.StuffDocumentsChain¶ class langchain.chains.combine_documents.stuff.StuffDocumentsChain[source]¶ Bases: BaseCombineDocumentsChain Chain that combines documents by stuffing into context. This chain takes a list of documents and first combines them into a single string. It does th...
lang/api.python.langchain.com/en/latest/chains/langchain.chains.combine_documents.stuff.StuffDocumentsChain.html
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Optional list of callback handlers (or callback manager). Defaults to None. Callback handlers are called throughout the lifecycle of a call to a chain, starting with on_chain_start, ending with on_chain_end or on_chain_error. Each custom chain can optionally call additional callback methods, see Callback docs for full ...
lang/api.python.langchain.com/en/latest/chains/langchain.chains.combine_documents.stuff.StuffDocumentsChain.html
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These tags 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 verbose: bool [Optional]¶ Whether or not run in verbose mode. In verbose mode, some intermediate logs will be...
lang/api.python.langchain.com/en/latest/chains/langchain.chains.combine_documents.stuff.StuffDocumentsChain.html
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include_run_info – Whether to include run info in the response. Defaults to False. 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, **kwar...
lang/api.python.langchain.com/en/latest/chains/langchain.chains.combine_documents.stuff.StuffDocumentsChain.html