agenerate_queries() — langchain Function Reference

Architecture documentation for the agenerate_queries() function in multi_query.py from the langchain codebase.

Function python LangChainCore Runnables called by 1

Entity Profile

LangChainCore→ Runnables→ agenerate_queries() — langchain Function Reference

Dependency Diagram

graph TD
  1b6d98c6_de11_daac_c877_e735a1432e2b["agenerate_queries()"]
  cc26ec3b_70dc_5b02_e974_582867b22f34["MultiQueryRetriever"]
  1b6d98c6_de11_daac_c877_e735a1432e2b -->|defined in| cc26ec3b_70dc_5b02_e974_582867b22f34
  437f73d9_6841_a790_7045_3311a114243f["_aget_relevant_documents()"]
  437f73d9_6841_a790_7045_3311a114243f -->|calls| 1b6d98c6_de11_daac_c877_e735a1432e2b
  style 1b6d98c6_de11_daac_c877_e735a1432e2b fill:#6366f1,stroke:#818cf8,color:#fff

Relationship Graph

Source Code

libs/langchain/langchain_classic/retrievers/multi_query.py lines 116–137

    async def agenerate_queries(
        self,
        question: str,
        run_manager: AsyncCallbackManagerForRetrieverRun,
    ) -> list[str]:
        """Generate queries based upon user input.

        Args:
            question: user query
            run_manager: the callback handler to use.

        Returns:
            List of LLM generated queries that are similar to the user input
        """
        response = await self.llm_chain.ainvoke(
            {"question": question},
            config={"callbacks": run_manager.get_child()},
        )
        lines = response["text"] if isinstance(self.llm_chain, LLMChain) else response
        if self.verbose:
            logger.info("Generated queries: %s", lines)
        return lines