_euclidean_distance() — langchain Function Reference

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

Function python LangChainCore LanguageModelBase calls 1

Entity Profile

LangChainCore→ LanguageModelBase→ _euclidean_distance() — langchain Function Reference

Dependency Diagram

graph TD
  5fc9ebcf_0906_f3ae_cddd_91b2aafd49a5["_euclidean_distance()"]
  dc2d52f5_736c_0ec2_ad57_0e2fdaa94e04["_EmbeddingDistanceChainMixin"]
  5fc9ebcf_0906_f3ae_cddd_91b2aafd49a5 -->|defined in| dc2d52f5_736c_0ec2_ad57_0e2fdaa94e04
  91b8ba41_75bf_8afd_e893_d85d055226da["_check_numpy()"]
  5fc9ebcf_0906_f3ae_cddd_91b2aafd49a5 -->|calls| 91b8ba41_75bf_8afd_e893_d85d055226da
  style 5fc9ebcf_0906_f3ae_cddd_91b2aafd49a5 fill:#6366f1,stroke:#818cf8,color:#fff

Relationship Graph

Source Code

libs/langchain/langchain_classic/evaluation/embedding_distance/base.py lines 241–261

    def _euclidean_distance(a: Any, b: Any) -> Any:
        """Compute the Euclidean distance between two vectors.

        Args:
            a (np.ndarray): The first vector.
            b (np.ndarray): The second vector.

        Returns:
            np.floating: The Euclidean distance.
        """
        try:
            from scipy.spatial.distance import euclidean

            return euclidean(a.flatten(), b.flatten())
        except ImportError:
            if _check_numpy():
                import numpy as np

                return np.linalg.norm(a - b)

            return sum((x - y) * (x - y) for x, y in zip(a, b, strict=False)) ** 0.5