embed_documents() — langchain Function Reference

Architecture documentation for the embed_documents() function in huggingface.py from the langchain codebase.

Function python LangChainCore MessageInterface calls 1

Entity Profile

LangChainCore→ MessageInterface→ embed_documents() — langchain Function Reference

Dependency Diagram

graph TD
  6c6f5815_8b28_d2f4_cafa_af0cebf3ee04["embed_documents()"]
  bc29a19b_53a3_8e06_ab58_d933298d898b["HuggingFaceEmbeddings"]
  6c6f5815_8b28_d2f4_cafa_af0cebf3ee04 -->|defined in| bc29a19b_53a3_8e06_ab58_d933298d898b
  b7c83ab3_15c9_f495_f1c6_d2b68282f2a6["_embed()"]
  6c6f5815_8b28_d2f4_cafa_af0cebf3ee04 -->|calls| b7c83ab3_15c9_f495_f1c6_d2b68282f2a6
  style 6c6f5815_8b28_d2f4_cafa_af0cebf3ee04 fill:#6366f1,stroke:#818cf8,color:#fff

Relationship Graph

Source Code

libs/partners/huggingface/langchain_huggingface/embeddings/huggingface.py lines 145–155

    def embed_documents(self, texts: list[str]) -> list[list[float]]:
        """Compute doc embeddings using a HuggingFace transformer model.

        Args:
            texts: The list of texts to embed.

        Returns:
            List of embeddings, one for each text.

        """
        return self._embed(texts, self.encode_kwargs)