aadd_texts() — langchain Function Reference

Architecture documentation for the aadd_texts() function in base.py from the langchain codebase.

Function python DataProcessing DocumentLoaders calls 2 called by 1

Entity Profile

DataProcessing→ DocumentLoaders→ aadd_texts() — langchain Function Reference

Dependency Diagram

graph TD
  08a89237_e844_a3d9_353e_d89cd55c7b6a["aadd_texts()"]
  6c336ac6_f55c_1ad7_6db3_73dbd71fb625["VectorStore"]
  08a89237_e844_a3d9_353e_d89cd55c7b6a -->|defined in| 6c336ac6_f55c_1ad7_6db3_73dbd71fb625
  c79bd583_f243_61a3_9784_31be23df6e6b["aadd_documents()"]
  c79bd583_f243_61a3_9784_31be23df6e6b -->|calls| 08a89237_e844_a3d9_353e_d89cd55c7b6a
  c79bd583_f243_61a3_9784_31be23df6e6b["aadd_documents()"]
  08a89237_e844_a3d9_353e_d89cd55c7b6a -->|calls| c79bd583_f243_61a3_9784_31be23df6e6b
  e5cf61af_382b_d2da_c38b_d74628394456["aadd_documents()"]
  08a89237_e844_a3d9_353e_d89cd55c7b6a -->|calls| e5cf61af_382b_d2da_c38b_d74628394456
  style 08a89237_e844_a3d9_353e_d89cd55c7b6a fill:#6366f1,stroke:#818cf8,color:#fff

Relationship Graph

Source Code

libs/core/langchain_core/vectorstores/base.py lines 185–232

    async def aadd_texts(
        self,
        texts: Iterable[str],
        metadatas: list[dict] | None = None,
        *,
        ids: list[str] | None = None,
        **kwargs: Any,
    ) -> list[str]:
        """Async run more texts through the embeddings and add to the `VectorStore`.

        Args:
            texts: Iterable of strings to add to the `VectorStore`.
            metadatas: Optional list of metadatas associated with the texts.
            ids: Optional list
            **kwargs: `VectorStore` specific parameters.

        Returns:
            List of IDs from adding the texts into the `VectorStore`.

        Raises:
            ValueError: If the number of metadatas does not match the number of texts.
            ValueError: If the number of IDs does not match the number of texts.
        """
        if ids is not None:
            # For backward compatibility
            kwargs["ids"] = ids
        if type(self).aadd_documents != VectorStore.aadd_documents:
            # This condition is triggered if the subclass has provided
            # an implementation of the upsert method.
            # The existing add_texts
            texts_: Sequence[str] = (
                texts if isinstance(texts, (list, tuple)) else list(texts)
            )
            if metadatas and len(metadatas) != len(texts_):
                msg = (
                    "The number of metadatas must match the number of texts."
                    f"Got {len(metadatas)} metadatas and {len(texts_)} texts."
                )
                raise ValueError(msg)
            metadatas_ = iter(metadatas) if metadatas else cycle([{}])
            ids_: Iterator[str | None] = iter(ids) if ids else cycle([None])

            docs = [
                Document(id=id_, page_content=text, metadata=metadata_)
                for text, metadata_, id_ in zip(texts, metadatas_, ids_, strict=False)
            ]
            return await self.aadd_documents(docs, **kwargs)
        return await run_in_executor(None, self.add_texts, texts, metadatas, **kwargs)