mirror of
https://github.com/hwchase17/langchain
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35 lines
1.2 KiB
Python
35 lines
1.2 KiB
Python
import pytest
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from langchain.retrievers.tfidf import TFIDFRetriever
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from langchain.schema import Document
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@pytest.mark.requires("sklearn")
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def test_from_texts() -> None:
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input_texts = ["I have a pen.", "Do you have a pen?", "I have a bag."]
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tfidf_retriever = TFIDFRetriever.from_texts(texts=input_texts)
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assert len(tfidf_retriever.docs) == 3
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assert tfidf_retriever.tfidf_array.toarray().shape == (3, 5)
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@pytest.mark.requires("sklearn")
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def test_from_texts_with_tfidf_params() -> None:
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input_texts = ["I have a pen.", "Do you have a pen?", "I have a bag."]
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tfidf_retriever = TFIDFRetriever.from_texts(
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texts=input_texts, tfidf_params={"min_df": 2}
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)
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# should count only multiple words (have, pan)
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assert tfidf_retriever.tfidf_array.toarray().shape == (3, 2)
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@pytest.mark.requires("sklearn")
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def test_from_documents() -> None:
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input_docs = [
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Document(page_content="I have a pen."),
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Document(page_content="Do you have a pen?"),
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Document(page_content="I have a bag."),
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]
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tfidf_retriever = TFIDFRetriever.from_documents(documents=input_docs)
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assert len(tfidf_retriever.docs) == 3
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assert tfidf_retriever.tfidf_array.toarray().shape == (3, 5)
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