get_embeddings() — langchain Function Reference

Architecture documentation for the get_embeddings() function in vectorstores.py from the langchain codebase.

Function python CoreAbstractions RunnableInterface

Entity Profile

CoreAbstractions→ RunnableInterface→ get_embeddings() — langchain Function Reference

Dependency Diagram

graph TD
  181ef22d_b1c2_1bc3_fc3f_0c2fbc9655f0["get_embeddings()"]
  6b7f515d_5b14_acff_3191_2493436e519d["VectorStoreIntegrationTests"]
  181ef22d_b1c2_1bc3_fc3f_0c2fbc9655f0 -->|defined in| 6b7f515d_5b14_acff_3191_2493436e519d
  style 181ef22d_b1c2_1bc3_fc3f_0c2fbc9655f0 fill:#6366f1,stroke:#818cf8,color:#fff

Relationship Graph

Source Code

libs/standard-tests/langchain_tests/integration_tests/vectorstores.py lines 124–136

    def get_embeddings() -> Embeddings:
        """Get embeddings.

        A pre-defined embeddings model that should be used for this test.

        This currently uses `DeterministicFakeEmbedding` from `langchain-core`,
        which uses numpy to generate random numbers based on a hash of the input text.

        The resulting embeddings are not meaningful, but they are deterministic.
        """
        return DeterministicFakeEmbedding(
            size=EMBEDDING_SIZE,
        )