langchain/tests/integration_tests/retrievers/test_merger_retriever.py

33 lines
1.2 KiB
Python
Raw Normal View History

from langchain.embeddings import OpenAIEmbeddings
from langchain.retrievers.merger_retriever import MergerRetriever
from langchain.vectorstores import Chroma
def test_merger_retriever_get_relevant_docs() -> None:
"""Test get_relevant_docs."""
texts_group_a = [
"This is a document about the Boston Celtics",
"Fly me to the moon is one of my favourite songs."
"I simply love going to the movies",
]
texts_group_b = [
"This is a document about the Poenix Suns",
"The Boston Celtics won the game by 20 points",
"Real stupidity beats artificial intelligence every time. TP",
]
embeddings = OpenAIEmbeddings()
retriever_a = Chroma.from_texts(texts_group_a, embedding=embeddings).as_retriever(
search_kwargs={"k": 1}
)
retriever_b = Chroma.from_texts(texts_group_b, embedding=embeddings).as_retriever(
search_kwargs={"k": 1}
)
# The Lord of the Retrievers.
lotr = MergerRetriever([retriever_a, retriever_b])
actual = lotr.get_relevant_documents("Tell me about the Celtics")
assert len(actual) == 2
assert texts_group_a[0] in [d.page_content for d in actual]
assert texts_group_b[1] in [d.page_content for d in actual]