46 lines
1.5 KiB
Python
46 lines
1.5 KiB
Python
import os
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import uuid
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import pytest
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from cognee.modules.data.processing.document_types.TextDocument import TextDocument
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GROUND_TRUTH = {
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"code.txt": [
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{"word_count": 205, "len_text": 1024, "cut_type": "sentence_cut"},
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{"word_count": 104, "len_text": 833, "cut_type": "paragraph_end"},
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],
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"Natural_language_processing.txt": [
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{"word_count": 128, "len_text": 984, "cut_type": "paragraph_end"},
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{"word_count": 1, "len_text": 1, "cut_type": "paragraph_end"},
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],
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}
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@pytest.mark.parametrize(
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"input_file,chunk_size",
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[("code.txt", 256), ("Natural_language_processing.txt", 128)],
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)
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def test_TextDocument(input_file, chunk_size):
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test_file_path = os.path.join(
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os.sep,
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*(os.path.dirname(__file__).split(os.sep)[:-2]),
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"test_data",
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input_file,
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)
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document = TextDocument(
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id=uuid.uuid4(), name=input_file, raw_data_location=test_file_path
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)
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for ground_truth, paragraph_data in zip(
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GROUND_TRUTH[input_file], document.read(chunk_size=chunk_size)
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):
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assert (
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ground_truth["word_count"] == paragraph_data.word_count
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), f'{ground_truth["word_count"] = } != {paragraph_data.word_count = }'
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assert ground_truth["len_text"] == len(
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paragraph_data.text
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), f'{ground_truth["len_text"] = } != {len(paragraph_data.text) = }'
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assert (
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ground_truth["cut_type"] == paragraph_data.cut_type
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), f'{ground_truth["cut_type"] = } != {paragraph_data.cut_type = }'
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