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https://github.com/khoj-ai/khoj.git
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79913d4c17
* Apply isort to the entire repository * Fix missing import issues in text_to_entries * Fix imports in migration files
162 lines
6.4 KiB
Python
162 lines
6.4 KiB
Python
# Standard Modules
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import logging
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from pathlib import Path
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import pytest
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from PIL import Image
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from khoj.search_type import image_search
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from khoj.utils.config import SearchModels
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from khoj.utils.constants import web_directory
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from khoj.utils.helpers import resolve_absolute_path
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from khoj.utils.rawconfig import ContentConfig, SearchConfig
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from khoj.utils.state import content_index, search_models
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# Test
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# ----------------------------------------------------------------------------------------------------
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def test_image_search_setup(content_config: ContentConfig, search_models: SearchModels):
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# Act
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# Regenerate image search embeddings during image setup
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image_search_model = image_search.setup(
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content_config.image, search_models.image_search.image_encoder, regenerate=True
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)
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# Assert
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assert len(image_search_model.image_names) == 3
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assert len(image_search_model.image_embeddings) == 3
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# ----------------------------------------------------------------------------------------------------
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def test_image_metadata(content_config: ContentConfig):
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"Verify XMP Description and Subjects Extracted from Image"
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# Arrange
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expected_metadata_image_name_pairs = [
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(["Billi Ka Bacha.", "Cat", "Grass"], "kitten_park.jpg"),
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(["Pasture.", "Horse", "Dog"], "horse_dog.jpg"),
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(["Guinea Pig Eating Celery.", "Rodent", "Whiskers"], "guineapig_grass.jpg"),
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]
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test_image_paths = [
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Path(content_config.image.input_directories[0] / image_name[1])
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for image_name in expected_metadata_image_name_pairs
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]
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for expected_metadata, test_image_path in zip(expected_metadata_image_name_pairs, test_image_paths):
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# Act
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actual_metadata = image_search.extract_metadata(test_image_path)
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# Assert
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for expected_snippet in expected_metadata[0]:
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assert expected_snippet in actual_metadata
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# ----------------------------------------------------------------------------------------------------
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@pytest.mark.anyio
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async def test_image_search(content_config: ContentConfig, search_config: SearchConfig):
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# Arrange
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search_models.image_search = image_search.initialize_model(search_config.image)
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content_index.image = image_search.setup(
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content_config.image, search_models.image_search.image_encoder, regenerate=False
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)
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output_directory = resolve_absolute_path(web_directory)
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query_expected_image_pairs = [
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("kitten", "kitten_park.jpg"),
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("horse and dog in a farm", "horse_dog.jpg"),
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("A guinea pig eating grass", "guineapig_grass.jpg"),
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]
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# Act
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for query, expected_image_name in query_expected_image_pairs:
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hits = await image_search.query(
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query, count=1, search_model=search_models.image_search, content=content_index.image
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)
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results = image_search.collate_results(
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hits,
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content_index.image.image_names,
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output_directory=output_directory,
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image_files_url="/static/images",
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count=1,
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)
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actual_image_path = output_directory.joinpath(Path(results[0].entry).name)
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actual_image = Image.open(actual_image_path)
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expected_image = Image.open(content_config.image.input_directories[0].joinpath(expected_image_name))
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# Assert
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assert expected_image == actual_image
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# Cleanup
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# Delete the image files copied to results directory
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actual_image_path.unlink()
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# ----------------------------------------------------------------------------------------------------
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@pytest.mark.anyio
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async def test_image_search_query_truncated(content_config: ContentConfig, search_config: SearchConfig, caplog):
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# Arrange
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search_models.image_search = image_search.initialize_model(search_config.image)
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content_index.image = image_search.setup(
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content_config.image, search_models.image_search.image_encoder, regenerate=False
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)
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max_words_supported = 10
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query = " ".join(["hello"] * 100)
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truncated_query = " ".join(["hello"] * max_words_supported)
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# Act
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try:
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with caplog.at_level(logging.INFO, logger="khoj.search_type.image_search"):
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await image_search.query(
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query, count=1, search_model=search_models.image_search, content=content_index.image
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)
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# Assert
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except RuntimeError as e:
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if "The size of tensor a (102) must match the size of tensor b (77)" in str(e):
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assert False, f"Query length exceeds max tokens supported by model\n"
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assert f"Find Images by Text: {truncated_query}" in caplog.text, "Query not truncated"
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# ----------------------------------------------------------------------------------------------------
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@pytest.mark.anyio
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async def test_image_search_by_filepath(content_config: ContentConfig, search_config: SearchConfig, caplog):
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# Arrange
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search_models.image_search = image_search.initialize_model(search_config.image)
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content_index.image = image_search.setup(
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content_config.image, search_models.image_search.image_encoder, regenerate=False
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)
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output_directory = resolve_absolute_path(web_directory)
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image_directory = content_config.image.input_directories[0]
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query = f"file:{image_directory.joinpath('kitten_park.jpg')}"
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expected_image_path = f"{image_directory.joinpath('kitten_park.jpg')}"
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# Act
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with caplog.at_level(logging.INFO, logger="khoj.search_type.image_search"):
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hits = await image_search.query(
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query, count=1, search_model=search_models.image_search, content=content_index.image
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)
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results = image_search.collate_results(
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hits,
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content_index.image.image_names,
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output_directory=output_directory,
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image_files_url="/static/images",
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count=1,
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)
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actual_image_path = output_directory.joinpath(Path(results[0].entry).name)
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actual_image = Image.open(actual_image_path)
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expected_image = Image.open(expected_image_path)
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# Assert
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# Ensure file search triggered instead of query with file path as string
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assert (
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f"Find Images by Image: {resolve_absolute_path(expected_image_path)}" in caplog.text
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), "File search not triggered"
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# Ensure the correct image is returned
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assert expected_image == actual_image, "Incorrect image returned by file search"
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# Cleanup
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# Delete the image files copied to results directory
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actual_image_path.unlink()
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