# -> {"_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 information that you must use to construct an answer.\nThe provided information is authoritative, you must never doubt it or try to use your internal knowledge to correct it.\nMake the answer sound as a response to the question. Do not mention that you based the result on the given information.\nIf the provided information is empty, say that you don't know the answer.\nInformation:\n{context}\n\nQuestion: {question}\nHelpful Answer:"), cypher_prompt: Optional[BasePromptTemplate] = None, **kwargs: Any) → NeptuneOpenCypherQAChain[source]¶
Initialize from LLM.
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?