pydantic model langchain.chains.MapReduceChain[source]#
Map-reduce chain.
Validators
raise_deprecation » all fields
set_verbose » verbose
field combine_documents_chain: BaseCombineDocumentsChain [Required]#
Chain to use to combine documents.
field text_splitter: TextSplitter [Required]#
Text splitter to use.
classmethod from_params(llm: langchain.base_language.BaseLanguageModel, prompt: langchain.prompts.base.BasePromptTemplate, text_splitter: langchain.text_splitter.TextSplitter, callbacks: Optional[Union[List[langchain.callbacks.base.BaseCallbackHandler], langchain.callbacks.base.BaseCallbackManager]] = None, combine_chain_kwargs: Optional[Mapping[str, Any]] = None, reduce_chain_kwargs: Optional[Mapping[str, Any]] = None, **kwargs: Any) → langchain.chains.mapreduce.MapReduceChain[source]#
Construct a map-reduce chain that uses the chain for map and reduce.
pydantic model langchain.chains.NebulaGraphQAChain[source]#
Chain for question-answering against a graph by generating nGQL statements.
Validators
raise_deprecation » all fields
set_verbose » verbose
field graph: NebulaGraph [Required]#
field ngql_generation_chain: LLMChain [Required]#
field qa_chain: LLMChain [Required]#
rtdocs_stable/api.python.langchain.com/en/stable/reference/modules/chains.html