langchain/libs/community/tests/unit_tests/retrievers/test_tfidf.py
Eugene Yurtsev 0e52961562
community[patch]: Patch tdidf retriever (CVE-2024-2057) (#18695)
This is a patch for `CVE-2024-2057`:
https://www.cve.org/CVERecord?id=CVE-2024-2057

This affects users that: 

* Use the  `TFIDFRetriever`
* Attempt to de-serialize it from an untrusted source that contains a
malicious payload
2024-03-06 15:49:04 -05:00

67 lines
2.5 KiB
Python

import os
from datetime import datetime
from tempfile import TemporaryDirectory
import pytest
from langchain_core.documents import Document
from langchain_community.retrievers.tfidf import TFIDFRetriever
@pytest.mark.requires("sklearn")
def test_from_texts() -> None:
input_texts = ["I have a pen.", "Do you have a pen?", "I have a bag."]
tfidf_retriever = TFIDFRetriever.from_texts(texts=input_texts)
assert len(tfidf_retriever.docs) == 3
assert tfidf_retriever.tfidf_array.toarray().shape == (3, 5)
@pytest.mark.requires("sklearn")
def test_from_texts_with_tfidf_params() -> None:
input_texts = ["I have a pen.", "Do you have a pen?", "I have a bag."]
tfidf_retriever = TFIDFRetriever.from_texts(
texts=input_texts, tfidf_params={"min_df": 2}
)
# should count only multiple words (have, pan)
assert tfidf_retriever.tfidf_array.toarray().shape == (3, 2)
@pytest.mark.requires("sklearn")
def test_from_documents() -> None:
input_docs = [
Document(page_content="I have a pen."),
Document(page_content="Do you have a pen?"),
Document(page_content="I have a bag."),
]
tfidf_retriever = TFIDFRetriever.from_documents(documents=input_docs)
assert len(tfidf_retriever.docs) == 3
assert tfidf_retriever.tfidf_array.toarray().shape == (3, 5)
@pytest.mark.requires("sklearn")
def test_save_local_load_local() -> None:
input_texts = ["I have a pen.", "Do you have a pen?", "I have a bag."]
tfidf_retriever = TFIDFRetriever.from_texts(texts=input_texts)
file_name = "tfidf_vectorizer"
temp_timestamp = datetime.utcnow().strftime("%Y%m%d-%H%M%S")
with TemporaryDirectory(suffix="_" + temp_timestamp + "/") as temp_folder:
tfidf_retriever.save_local(
folder_path=temp_folder,
file_name=file_name,
)
assert os.path.exists(os.path.join(temp_folder, f"{file_name}.joblib"))
assert os.path.exists(os.path.join(temp_folder, f"{file_name}.pkl"))
loaded_tfidf_retriever = TFIDFRetriever.load_local(
folder_path=temp_folder,
file_name=file_name,
# Not a realistic security risk in this case.
# OK to allow for testing purposes.
# If the file has been compromised during this test, there's
# a much bigger problem.
allow_dangerous_deserialization=True,
)
assert len(loaded_tfidf_retriever.docs) == 3
assert loaded_tfidf_retriever.tfidf_array.toarray().shape == (3, 5)