mirror of
https://github.com/khoj-ai/khoj.git
synced 2024-11-23 15:38:55 +01:00
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
|
|
import logging
|
|
from pathlib import Path
|
|
|
|
import pytest
|
|
from PIL import Image
|
|
|
|
from khoj.search_type import image_search
|
|
from khoj.utils.config import SearchModels
|
|
from khoj.utils.constants import web_directory
|
|
from khoj.utils.helpers import resolve_absolute_path
|
|
from khoj.utils.rawconfig import ContentConfig, SearchConfig
|
|
from khoj.utils.state import content_index, search_models
|
|
|
|
|
|
# Test
|
|
# ----------------------------------------------------------------------------------------------------
|
|
def test_image_search_setup(content_config: ContentConfig, search_models: SearchModels):
|
|
# Act
|
|
# Regenerate image search embeddings during image setup
|
|
image_search_model = image_search.setup(
|
|
content_config.image, search_models.image_search.image_encoder, regenerate=True
|
|
)
|
|
|
|
# Assert
|
|
assert len(image_search_model.image_names) == 3
|
|
assert len(image_search_model.image_embeddings) == 3
|
|
|
|
|
|
# ----------------------------------------------------------------------------------------------------
|
|
def test_image_metadata(content_config: ContentConfig):
|
|
"Verify XMP Description and Subjects Extracted from Image"
|
|
# Arrange
|
|
expected_metadata_image_name_pairs = [
|
|
(["Billi Ka Bacha.", "Cat", "Grass"], "kitten_park.jpg"),
|
|
(["Pasture.", "Horse", "Dog"], "horse_dog.jpg"),
|
|
(["Guinea Pig Eating Celery.", "Rodent", "Whiskers"], "guineapig_grass.jpg"),
|
|
]
|
|
|
|
test_image_paths = [
|
|
Path(content_config.image.input_directories[0] / image_name[1])
|
|
for image_name in expected_metadata_image_name_pairs
|
|
]
|
|
|
|
for expected_metadata, test_image_path in zip(expected_metadata_image_name_pairs, test_image_paths):
|
|
# Act
|
|
actual_metadata = image_search.extract_metadata(test_image_path)
|
|
|
|
# Assert
|
|
for expected_snippet in expected_metadata[0]:
|
|
assert expected_snippet in actual_metadata
|
|
|
|
|
|
# ----------------------------------------------------------------------------------------------------
|
|
@pytest.mark.anyio
|
|
async def test_image_search(content_config: ContentConfig, search_config: SearchConfig):
|
|
# Arrange
|
|
search_models.image_search = image_search.initialize_model(search_config.image)
|
|
content_index.image = image_search.setup(
|
|
content_config.image, search_models.image_search.image_encoder, regenerate=False
|
|
)
|
|
output_directory = resolve_absolute_path(web_directory)
|
|
query_expected_image_pairs = [
|
|
("kitten", "kitten_park.jpg"),
|
|
("horse and dog in a farm", "horse_dog.jpg"),
|
|
("A guinea pig eating grass", "guineapig_grass.jpg"),
|
|
]
|
|
|
|
# Act
|
|
for query, expected_image_name in query_expected_image_pairs:
|
|
hits = await image_search.query(
|
|
query, count=1, search_model=search_models.image_search, content=content_index.image
|
|
)
|
|
|
|
results = image_search.collate_results(
|
|
hits,
|
|
content_index.image.image_names,
|
|
output_directory=output_directory,
|
|
image_files_url="/static/images",
|
|
count=1,
|
|
)
|
|
|
|
actual_image_path = output_directory.joinpath(Path(results[0].entry).name)
|
|
actual_image = Image.open(actual_image_path)
|
|
expected_image = Image.open(content_config.image.input_directories[0].joinpath(expected_image_name))
|
|
|
|
# Assert
|
|
assert expected_image == actual_image
|
|
|
|
# Cleanup
|
|
# Delete the image files copied to results directory
|
|
actual_image_path.unlink()
|
|
|
|
|
|
# ----------------------------------------------------------------------------------------------------
|
|
@pytest.mark.anyio
|
|
async def test_image_search_query_truncated(content_config: ContentConfig, search_config: SearchConfig, caplog):
|
|
# Arrange
|
|
search_models.image_search = image_search.initialize_model(search_config.image)
|
|
content_index.image = image_search.setup(
|
|
content_config.image, search_models.image_search.image_encoder, regenerate=False
|
|
)
|
|
max_words_supported = 10
|
|
query = " ".join(["hello"] * 100)
|
|
truncated_query = " ".join(["hello"] * max_words_supported)
|
|
|
|
# Act
|
|
try:
|
|
with caplog.at_level(logging.INFO, logger="khoj.search_type.image_search"):
|
|
await image_search.query(
|
|
query, count=1, search_model=search_models.image_search, content=content_index.image
|
|
)
|
|
# Assert
|
|
except RuntimeError as e:
|
|
if "The size of tensor a (102) must match the size of tensor b (77)" in str(e):
|
|
assert False, f"Query length exceeds max tokens supported by model\n"
|
|
assert f"Find Images by Text: {truncated_query}" in caplog.text, "Query not truncated"
|
|
|
|
|
|
# ----------------------------------------------------------------------------------------------------
|
|
@pytest.mark.anyio
|
|
async def test_image_search_by_filepath(content_config: ContentConfig, search_config: SearchConfig, caplog):
|
|
# Arrange
|
|
search_models.image_search = image_search.initialize_model(search_config.image)
|
|
content_index.image = image_search.setup(
|
|
content_config.image, search_models.image_search.image_encoder, regenerate=False
|
|
)
|
|
output_directory = resolve_absolute_path(web_directory)
|
|
image_directory = content_config.image.input_directories[0]
|
|
|
|
query = f"file:{image_directory.joinpath('kitten_park.jpg')}"
|
|
expected_image_path = f"{image_directory.joinpath('kitten_park.jpg')}"
|
|
|
|
# Act
|
|
with caplog.at_level(logging.INFO, logger="khoj.search_type.image_search"):
|
|
hits = await image_search.query(
|
|
query, count=1, search_model=search_models.image_search, content=content_index.image
|
|
)
|
|
|
|
results = image_search.collate_results(
|
|
hits,
|
|
content_index.image.image_names,
|
|
output_directory=output_directory,
|
|
image_files_url="/static/images",
|
|
count=1,
|
|
)
|
|
|
|
actual_image_path = output_directory.joinpath(Path(results[0].entry).name)
|
|
actual_image = Image.open(actual_image_path)
|
|
expected_image = Image.open(expected_image_path)
|
|
|
|
# Assert
|
|
# Ensure file search triggered instead of query with file path as string
|
|
assert (
|
|
f"Find Images by Image: {resolve_absolute_path(expected_image_path)}" in caplog.text
|
|
), "File search not triggered"
|
|
# Ensure the correct image is returned
|
|
assert expected_image == actual_image, "Incorrect image returned by file search"
|
|
|
|
# Cleanup
|
|
# Delete the image files copied to results directory
|
|
actual_image_path.unlink()
|