split_documents() — langchain Function Reference

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

Function python DocumentProcessing TextSplitters calls 1 called by 1

Entity Profile

DocumentProcessing→ TextSplitters→ split_documents() — langchain Function Reference

Dependency Diagram

graph TD
  d14f3e1b_dd57_6268_5d47_c8b53356440d["split_documents()"]
  c86e37d5_f962_cc1e_9821_b665e1359ae8["TextSplitter"]
  d14f3e1b_dd57_6268_5d47_c8b53356440d -->|defined in| c86e37d5_f962_cc1e_9821_b665e1359ae8
  e269bebc_7f11_3715_6f4a_f53fba4229cb["transform_documents()"]
  e269bebc_7f11_3715_6f4a_f53fba4229cb -->|calls| d14f3e1b_dd57_6268_5d47_c8b53356440d
  a4cdf08b_5d25_7d6b_a425_7a96372e8666["create_documents()"]
  d14f3e1b_dd57_6268_5d47_c8b53356440d -->|calls| a4cdf08b_5d25_7d6b_a425_7a96372e8666
  style d14f3e1b_dd57_6268_5d47_c8b53356440d fill:#6366f1,stroke:#818cf8,color:#fff

Relationship Graph

Source Code

libs/text-splitters/langchain_text_splitters/base.py lines 131–144

    def split_documents(self, documents: Iterable[Document]) -> list[Document]:
        """Split documents.

        Args:
            documents: The documents to split.

        Returns:
            A list of split documents.
        """
        texts, metadatas = [], []
        for doc in documents:
            texts.append(doc.page_content)
            metadatas.append(doc.metadata)
        return self.create_documents(texts, metadatas=metadatas)