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from typing import List
from langchain_core.documents import Document
from langchain_core.embeddings import Embeddings
fake_texts = ["foo", "bar", "baz"]
class FakeEmbeddings(Embeddings):
"""Fake embeddings functionality for testing."""
def embed_documents(self, texts: List[str]) -> List[List[float]]:
"""Return simple embeddings.
Embeddings encode each text as its index."""
return [[float(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)
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 [float(1.0)] * 9 + [float(0.0)]
async def aembed_query(self, text: str) -> List[float]:
return self.embed_query(text)
def assert_docs_equal_without_pk(
docs1: List[Document], docs2: List[Document], pk_field: str = "pk"
) -> None:
"""Assert two lists of Documents are equal, ignoring the primary key field."""
assert len(docs1) == len(docs2)
for doc1, doc2 in zip(docs1, docs2):
assert doc1.page_content == doc2.page_content
doc1.metadata.pop(pk_field, None)
doc2.metadata.pop(pk_field, None)
assert doc1.metadata == doc2.metadata
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