Create a multi retrieval qa chain from an LLM and a default chain.
from_retrievers(
cls,
llm: BaseLanguageModel,
retriever_infos: list[dict[str, Any]],
default_retriever: BaseRetriever | None = None,
default_prompt: PromptTemplate | None = None,
default_chain: Chain | None = None,
*,
default_chain_llm: BaseLanguageModel | None = None,
**kwargs: Any = {}
) -> MultiRetrievalQAChain| Name | Type | Description |
|---|---|---|
llm* | BaseLanguageModel | The language model to use. |
retriever_infos* | list[dict[str, Any]] | Dictionaries containing retriever information. |
default_retriever | BaseRetriever | None | Default: NoneOptional default retriever to use if no default chain is provided. |
default_prompt | PromptTemplate | None | Default: NoneOptional prompt template to use for the default retriever. |
default_chain | Chain | None | Default: NoneOptional default chain to use when router doesn't map input to one of the destinations. |
default_chain_llm | BaseLanguageModel | None | Default: NoneOptional language model to use if no default chain and no default retriever are provided. |
**kwargs | Any | Default: {}Additional keyword arguments to pass to the chain. |