and new question into a standalone question.
chain_type – The chain type to use to create the combine_docs_chain, will
be sent to load_qa_chain.
verbose – Verbosity flag for logging to stdout.
condense_question_llm – The language model to use for condensing the chat
history and new question into a standalone question. If none is
provided, will default to llm.
combine_docs_chain_kwargs – Parameters to pass as kwargs to load_qa_chain
when constructing the combine_docs_chain.
callbacks – Callbacks to pass to all subchains.
**kwargs – Additional parameters to pass when initializing
ConversationalRetrievalChain
classmethod from_orm(obj: Any) → Model¶
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”]
invoke(input: Dict[str, Any], config: Optional[RunnableConfig] = None, **kwargs: Any) → Dict[str, Any]¶
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_defaults: bool = False, exclude_none: bool = False, encoder: Optional[Callable[[Any], Any]] = None, models_as_dict: bool = True, **dumps_kwargs: Any) → unicode¶
Generate a JSON representation of the model, include and exclude arguments as per dict().