FakeEmbeddings Class — langchain Architecture

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

Class python

Entity Profile

Dependency Diagram

graph TD
  52dc38c4_a553_b0ec_2c2c_21dd83151dd4["FakeEmbeddings"]
  b1e4f760_c634_d3bf_ca9a_db7ab899cc4a["Embeddings"]
  52dc38c4_a553_b0ec_2c2c_21dd83151dd4 -->|extends| b1e4f760_c634_d3bf_ca9a_db7ab899cc4a
  b656da5c_781f_2669_c8cd_83d309b3feb8["fake_embeddings.py"]
  52dc38c4_a553_b0ec_2c2c_21dd83151dd4 -->|defined in| b656da5c_781f_2669_c8cd_83d309b3feb8
  d3805a78_7bfa_d113_27bb_02644a3715c5["embed_documents()"]
  52dc38c4_a553_b0ec_2c2c_21dd83151dd4 -->|method| d3805a78_7bfa_d113_27bb_02644a3715c5
  59f6944a_db8e_bd97_ddbd_3d788d64cba7["aembed_documents()"]
  52dc38c4_a553_b0ec_2c2c_21dd83151dd4 -->|method| 59f6944a_db8e_bd97_ddbd_3d788d64cba7
  e5c96f6b_0c40_3844_cb76_087fbb761a57["embed_query()"]
  52dc38c4_a553_b0ec_2c2c_21dd83151dd4 -->|method| e5c96f6b_0c40_3844_cb76_087fbb761a57
  5ef304a2_f940_570f_9b96_3bd813aa9835["aembed_query()"]
  52dc38c4_a553_b0ec_2c2c_21dd83151dd4 -->|method| 5ef304a2_f940_570f_9b96_3bd813aa9835

Relationship Graph

Source Code

libs/langchain_v1/tests/integration_tests/cache/fake_embeddings.py lines 11–36

class FakeEmbeddings(Embeddings):
    """Fake embeddings functionality for testing."""

    @override
    def embed_documents(self, texts: list[str]) -> list[list[float]]:
        """Return simple embeddings.

        Embeddings encode each text as its index.
        """
        return [[1.0] * 9 + [float(i)] for i in range(len(texts))]

    async def aembed_documents(self, texts: list[str]) -> list[list[float]]:
        return self.embed_documents(texts)

    @override
    def embed_query(self, text: str) -> list[float]:
        """Return constant query embeddings.

        Embeddings are identical to embed_documents(texts)[0].
        Distance to each text will be that text's index,
        as it was passed to embed_documents.
        """
        return [1.0] * 9 + [0.0]

    async def aembed_query(self, text: str) -> list[float]:
        return self.embed_query(text)