ConsistentFakeEmbeddings Class — langchain Architecture

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

Class python

Entity Profile

Dependency Diagram

graph TD
  7513f7c3_4c62_459e_738a_c4afde0288a1["ConsistentFakeEmbeddings"]
  dca08b34_f922_a3fa_4752_e72b03b86d89["FakeEmbeddings"]
  7513f7c3_4c62_459e_738a_c4afde0288a1 -->|extends| dca08b34_f922_a3fa_4752_e72b03b86d89
  137cdc23_3587_d3e6_41a8_782c05eb74a4["fake_embeddings.py"]
  7513f7c3_4c62_459e_738a_c4afde0288a1 -->|defined in| 137cdc23_3587_d3e6_41a8_782c05eb74a4
  3bf76df1_e1b0_41c7_33da_92327420cb30["__init__()"]
  7513f7c3_4c62_459e_738a_c4afde0288a1 -->|method| 3bf76df1_e1b0_41c7_33da_92327420cb30
  e151f1ea_3e38_6d9b_73bb_f8e186c0aec3["embed_documents()"]
  7513f7c3_4c62_459e_738a_c4afde0288a1 -->|method| e151f1ea_3e38_6d9b_73bb_f8e186c0aec3
  b86271bf_b4fe_f56c_d275_f88094a14a26["embed_query()"]
  7513f7c3_4c62_459e_738a_c4afde0288a1 -->|method| b86271bf_b4fe_f56c_d275_f88094a14a26

Relationship Graph

Source Code

libs/partners/chroma/tests/integration_tests/fake_embeddings.py lines 32–55

class ConsistentFakeEmbeddings(FakeEmbeddings):
    """Fake embeddings which remember all the texts seen so far to return consistent
    vectors for the same texts."""

    def __init__(self, dimensionality: int = 10) -> None:
        self.known_texts: list[str] = []
        self.dimensionality = dimensionality

    def embed_documents(self, texts: list[str]) -> list[list[float]]:
        """Return consistent embeddings for each text seen so far."""
        out_vectors = []
        for text in texts:
            if text not in self.known_texts:
                self.known_texts.append(text)
            vector = [1.0] * (self.dimensionality - 1) + [
                float(self.known_texts.index(text)),
            ]
            out_vectors.append(vector)
        return out_vectors

    def embed_query(self, text: str) -> list[float]:
        """Return consistent embeddings for the text, if seen before, or a constant
        one if the text is unknown."""
        return self.embed_documents([text])[0]