EmbeddingDistance Class — langchain Architecture

Architecture documentation for the EmbeddingDistance class in config.py from the langchain codebase.

Class python

Entity Profile

Dependency Diagram

graph TD
  ffe759c0_4bd5_afde_4ff3_1094cfbab4b9["EmbeddingDistance"]
  5528a09f_3682_a8b0_958b_cd9a898b6e3c["SingleKeyEvalConfig"]
  ffe759c0_4bd5_afde_4ff3_1094cfbab4b9 -->|extends| 5528a09f_3682_a8b0_958b_cd9a898b6e3c
  ba7f9415_541a_d99f_0400_a688a10212b0["config.py"]
  ffe759c0_4bd5_afde_4ff3_1094cfbab4b9 -->|defined in| ba7f9415_541a_d99f_0400_a688a10212b0

Relationship Graph

Source Code

libs/langchain/langchain_classic/smith/evaluation/config.py lines 147–161

    class EmbeddingDistance(SingleKeyEvalConfig):
        """Configuration for an embedding distance evaluator.

        Attributes:
            embeddings: The embeddings to use for computing the distance.
            distance_metric: The distance metric to use for computing the distance.
        """

        evaluator_type: EvaluatorType = EvaluatorType.EMBEDDING_DISTANCE
        embeddings: Embeddings | None = None
        distance_metric: EmbeddingDistanceEnum | None = None

        model_config = ConfigDict(
            arbitrary_types_allowed=True,
        )