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EmbeddingDistance Class — langchain Architecture

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

Class python

Entity Profile

Dependency Diagram

graph TD
  7307a519_d4b7_31fb_c62e_81acca2e3b80["EmbeddingDistance"]
  8d2afa68_e16d_c06a_fbe2_08321c12e529["base.py"]
  7307a519_d4b7_31fb_c62e_81acca2e3b80 -->|defined in| 8d2afa68_e16d_c06a_fbe2_08321c12e529

Relationship Graph

Source Code

libs/langchain/langchain_classic/evaluation/embedding_distance/base.py lines 75–90

class EmbeddingDistance(str, Enum):
    """Embedding Distance Metric.

    Attributes:
        COSINE: Cosine distance metric.
        EUCLIDEAN: Euclidean distance metric.
        MANHATTAN: Manhattan distance metric.
        CHEBYSHEV: Chebyshev distance metric.
        HAMMING: Hamming distance metric.
    """

    COSINE = "cosine"
    EUCLIDEAN = "euclidean"
    MANHATTAN = "manhattan"
    CHEBYSHEV = "chebyshev"
    HAMMING = "hamming"

Defined In

Source

Frequently Asked Questions

What is the EmbeddingDistance class?
EmbeddingDistance is a class in the langchain codebase, defined in libs/langchain/langchain_classic/evaluation/embedding_distance/base.py.
Where is EmbeddingDistance defined?
EmbeddingDistance is defined in libs/langchain/langchain_classic/evaluation/embedding_distance/base.py at line 75.

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