aadd_documents() — langchain Function Reference

Architecture documentation for the aadd_documents() function in time_weighted_retriever.py from the langchain codebase.

Function python LangChainCore ApiManagement

Entity Profile

LangChainCore→ ApiManagement→ aadd_documents() — langchain Function Reference

Dependency Diagram

graph TD
  60f8ad70_73fc_0bd8_e1d1_cd3d2d1ad6b1["aadd_documents()"]
  57cc5b02_6622_339b_0806_ef06db1bc8c7["TimeWeightedVectorStoreRetriever"]
  60f8ad70_73fc_0bd8_e1d1_cd3d2d1ad6b1 -->|defined in| 57cc5b02_6622_339b_0806_ef06db1bc8c7
  style 60f8ad70_73fc_0bd8_e1d1_cd3d2d1ad6b1 fill:#6366f1,stroke:#818cf8,color:#fff

Relationship Graph

Source Code

libs/langchain/langchain_classic/retrievers/time_weighted_retriever.py lines 180–198

    async def aadd_documents(
        self,
        documents: list[Document],
        **kwargs: Any,
    ) -> list[str]:
        """Add documents to vectorstore."""
        current_time = kwargs.get("current_time")
        if current_time is None:
            current_time = datetime.datetime.now()
        # Avoid mutating input documents
        dup_docs = [deepcopy(d) for d in documents]
        for i, doc in enumerate(dup_docs):
            if "last_accessed_at" not in doc.metadata:
                doc.metadata["last_accessed_at"] = current_time
            if "created_at" not in doc.metadata:
                doc.metadata["created_at"] = current_time
            doc.metadata["buffer_idx"] = len(self.memory_stream) + i
        self.memory_stream.extend(dup_docs)
        return await self.vectorstore.aadd_documents(dup_docs, **kwargs)