FakeEmbeddings Class — langchain Architecture

Architecture documentation for the FakeEmbeddings class in test_hyde.py from the langchain codebase.

Class python

Entity Profile

Dependency Diagram

graph TD
  e1697692_0afb_1adc_ce1e_980922dcd4cd["FakeEmbeddings"]
  b1e4f760_c634_d3bf_ca9a_db7ab899cc4a["Embeddings"]
  e1697692_0afb_1adc_ce1e_980922dcd4cd -->|extends| b1e4f760_c634_d3bf_ca9a_db7ab899cc4a
  14c6e7c4_9f19_c161_786a_25327950593b["test_hyde.py"]
  e1697692_0afb_1adc_ce1e_980922dcd4cd -->|defined in| 14c6e7c4_9f19_c161_786a_25327950593b
  7b3d7bb0_090c_f8b7_297b_d4b900f25c98["embed_documents()"]
  e1697692_0afb_1adc_ce1e_980922dcd4cd -->|method| 7b3d7bb0_090c_f8b7_297b_d4b900f25c98
  ac059ee6_7663_73f2_90de_f1e094aa871c["embed_query()"]
  e1697692_0afb_1adc_ce1e_980922dcd4cd -->|method| ac059ee6_7663_73f2_90de_f1e094aa871c

Relationship Graph

Source Code

libs/langchain/tests/unit_tests/chains/test_hyde.py lines 19–30

class FakeEmbeddings(Embeddings):
    """Fake embedding class for tests."""

    @override
    def embed_documents(self, texts: list[str]) -> list[list[float]]:
        """Return random floats."""
        return [list(np.random.default_rng().uniform(0, 1, 10)) for _ in range(10)]

    @override
    def embed_query(self, text: str) -> list[float]:
        """Return random floats."""
        return list(np.random.default_rng().uniform(0, 1, 10))