langchain.agents.agent_toolkits.vectorstore.base.create_vectorstore_agent¶
langchain.agents.agent_toolkits.vectorstore.base.create_vectorstore_agent(llm: BaseLanguageModel, toolkit: VectorStoreToolkit, callback_manager: Optional[BaseCallbackManager] = None, prefix: str = 'You are an agent designed to answer questions about sets of documents.\nYou have access to tools for interacting with the documents, and the inputs to the tools are questions.\nSometimes, you will be asked to provide sources for your questions, in which case you should use the appropriate tool to do so.\nIf the question does not seem relevant to any of the tools provided, just return "I don\'t know" as the answer.\n', verbose: bool = False, agent_executor_kwargs: Optional[Dict[str, Any]] = None, **kwargs: Dict[str, Any]) → AgentExecutor[source]¶
Construct a VectorStore agent from an LLM and tools.
Examples using create_vectorstore_agent¶
Vectorstore Agent