forked from Archives/langchain
44 lines
1.4 KiB
Python
44 lines
1.4 KiB
Python
import pandas as pd
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import pytest
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from langchain.document_loaders import DataFrameLoader
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from langchain.schema import Document
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@pytest.fixture
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def sample_data_frame() -> pd.DataFrame:
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data = {
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"text": ["Hello", "World"],
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"author": ["Alice", "Bob"],
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"date": ["2022-01-01", "2022-01-02"],
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}
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return pd.DataFrame(data)
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def test_load_returns_list_of_documents(sample_data_frame: pd.DataFrame) -> None:
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loader = DataFrameLoader(sample_data_frame)
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docs = loader.load()
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assert isinstance(docs, list)
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assert all(isinstance(doc, Document) for doc in docs)
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assert len(docs) == 2
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def test_load_converts_dataframe_columns_to_document_metadata(
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sample_data_frame: pd.DataFrame,
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) -> None:
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loader = DataFrameLoader(sample_data_frame)
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docs = loader.load()
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for i, doc in enumerate(docs):
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assert doc.metadata["author"] == sample_data_frame.loc[i, "author"]
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assert doc.metadata["date"] == sample_data_frame.loc[i, "date"]
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def test_load_uses_page_content_column_to_create_document_text(
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sample_data_frame: pd.DataFrame,
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) -> None:
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sample_data_frame = sample_data_frame.rename(columns={"text": "dummy_test_column"})
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loader = DataFrameLoader(sample_data_frame, page_content_column="dummy_test_column")
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docs = loader.load()
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assert docs[0].page_content == "Hello"
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assert docs[1].page_content == "World"
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