mirror of
https://github.com/hwchase17/langchain
synced 2024-11-10 01:10:59 +00:00
c010ec8b71
- `.get_relevant_documents(query)` -> `.invoke(query)`
- `.get_relevant_documents(query=query)` -> `.invoke(query)`
- `.get_relevant_documents(query, callbacks=callbacks)` ->
`.invoke(query, config={"callbacks": callbacks})`
- `.get_relevant_documents(query, **kwargs)` -> `.invoke(query,
**kwargs)`
---------
Co-authored-by: Erick Friis <erick@langchain.dev>
43 lines
1.6 KiB
Python
43 lines
1.6 KiB
Python
import pytest
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from langchain_core.documents import Document
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from langchain_community.embeddings import FakeEmbeddings
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from langchain_community.retrievers.svm import SVMRetriever
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class TestSVMRetriever:
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@pytest.mark.requires("sklearn")
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def test_from_texts(self) -> None:
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input_texts = ["I have a pen.", "Do you have a pen?", "I have a bag."]
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svm_retriever = SVMRetriever.from_texts(
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texts=input_texts, embeddings=FakeEmbeddings(size=100)
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)
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assert len(svm_retriever.texts) == 3
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@pytest.mark.requires("sklearn")
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def test_from_documents(self) -> None:
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input_docs = [
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Document(page_content="I have a pen.", metadata={"foo": "bar"}),
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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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svm_retriever = SVMRetriever.from_documents(
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documents=input_docs, embeddings=FakeEmbeddings(size=100)
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)
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assert len(svm_retriever.texts) == 3
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@pytest.mark.requires("sklearn")
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def test_metadata_persists(self) -> None:
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input_docs = [
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Document(page_content="I have a pen.", metadata={"foo": "bar"}),
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Document(page_content="How about you?", metadata={"foo": "baz"}),
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Document(page_content="I have a bag.", metadata={"foo": "qux"}),
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]
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svm_retriever = SVMRetriever.from_documents(
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documents=input_docs, embeddings=FakeEmbeddings(size=100)
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)
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query = "Have anything?"
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output_docs = svm_retriever.invoke(query)
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for doc in output_docs:
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assert "foo" in doc.metadata
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