vectors() — langchain Function Reference

Architecture documentation for the vectors() function in test_embedding.py from the langchain codebase.

Function python LangChainCore MessageInterface

Entity Profile

LangChainCore→ MessageInterface→ vectors() — langchain Function Reference

Dependency Diagram

graph TD
  f6ec6a27_b13e_0cb8_38dc_dea6949f9880["vectors()"]
  89627e7b_46a2_902e_b342_68623bc9d7ef["test_embedding.py"]
  f6ec6a27_b13e_0cb8_38dc_dea6949f9880 -->|defined in| 89627e7b_46a2_902e_b342_68623bc9d7ef
  style f6ec6a27_b13e_0cb8_38dc_dea6949f9880 fill:#6366f1,stroke:#818cf8,color:#fff

Relationship Graph

Source Code

libs/langchain/tests/integration_tests/evaluation/embedding_distance/test_embedding.py lines 12–42

def vectors() -> tuple[np.ndarray, np.ndarray]:
    """Create two random vectors."""
    vector_a = np.array(
        [
            0.5488135,
            0.71518937,
            0.60276338,
            0.54488318,
            0.4236548,
            0.64589411,
            0.43758721,
            0.891773,
            0.96366276,
            0.38344152,
        ],
    )
    vector_b = np.array(
        [
            0.79172504,
            0.52889492,
            0.56804456,
            0.92559664,
            0.07103606,
            0.0871293,
            0.0202184,
            0.83261985,
            0.77815675,
            0.87001215,
        ],
    )
    return vector_a, vector_b