_get_docs() — langchain Function Reference

Architecture documentation for the _get_docs() function in vector_db.py from the langchain codebase.

Function python AgentOrchestration ClassicChains calls 1

Entity Profile

AgentOrchestration→ ClassicChains→ _get_docs() — langchain Function Reference

Dependency Diagram

graph TD
  351a2d31_1d62_5bc7_cdde_9096743e5070["_get_docs()"]
  5eb6dd31_a76d_429d_2244_999951beb530["VectorDBQAWithSourcesChain"]
  351a2d31_1d62_5bc7_cdde_9096743e5070 -->|defined in| 5eb6dd31_a76d_429d_2244_999951beb530
  a733a44b_a858_f174_7563_58bb90e6fa35["_reduce_tokens_below_limit()"]
  351a2d31_1d62_5bc7_cdde_9096743e5070 -->|calls| a733a44b_a858_f174_7563_58bb90e6fa35
  style 351a2d31_1d62_5bc7_cdde_9096743e5070 fill:#6366f1,stroke:#818cf8,color:#fff

Relationship Graph

Source Code

libs/langchain/langchain_classic/chains/qa_with_sources/vector_db.py lines 53–65

    def _get_docs(
        self,
        inputs: dict[str, Any],
        *,
        run_manager: CallbackManagerForChainRun,
    ) -> list[Document]:
        question = inputs[self.question_key]
        docs = self.vectorstore.similarity_search(
            question,
            k=self.k,
            **self.search_kwargs,
        )
        return self._reduce_tokens_below_limit(docs)