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25a749ca1d
- Why The khoj pypi packages should be installed in `khoj' directory. Previously it was being installed into `src' directory, which is a generic top level directory name that is discouraged from being used - Changes - move src/* to src/khoj/* - update `setup.py' to `find_packages' in `src' instead of project root - rename imports to form `from khoj.*' in complete project - update `constants.web_directory' path to use `khoj' directory - rename root logger to `khoj' in `main.py' - fix image_search tests to use the newly rename `khoj' logger - update config, docs, workflows to reference new path `src/khoj'
87 lines
No EOL
3 KiB
Python
87 lines
No EOL
3 KiB
Python
# External Packages
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from copy import deepcopy
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from pathlib import Path
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import pytest
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# Internal Packages
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from khoj.search_type import image_search, text_search
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from khoj.utils.helpers import resolve_absolute_path
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from khoj.utils.rawconfig import ContentConfig, TextContentConfig, ImageContentConfig, SearchConfig, TextSearchConfig, ImageSearchConfig
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from khoj.processor.org_mode.org_to_jsonl import OrgToJsonl
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from khoj.search_filter.date_filter import DateFilter
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from khoj.search_filter.word_filter import WordFilter
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from khoj.search_filter.file_filter import FileFilter
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@pytest.fixture(scope='session')
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def search_config() -> SearchConfig:
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model_dir = resolve_absolute_path('~/.khoj/search')
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model_dir.mkdir(parents=True, exist_ok=True)
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search_config = SearchConfig()
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search_config.symmetric = TextSearchConfig(
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encoder = "sentence-transformers/all-MiniLM-L6-v2",
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cross_encoder = "cross-encoder/ms-marco-MiniLM-L-6-v2",
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model_directory = model_dir / 'symmetric/'
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)
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search_config.asymmetric = TextSearchConfig(
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encoder = "sentence-transformers/multi-qa-MiniLM-L6-cos-v1",
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cross_encoder = "cross-encoder/ms-marco-MiniLM-L-6-v2",
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model_directory = model_dir / 'asymmetric/'
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)
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search_config.image = ImageSearchConfig(
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encoder = "sentence-transformers/clip-ViT-B-32",
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model_directory = model_dir / 'image/'
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)
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return search_config
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@pytest.fixture(scope='session')
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def content_config(tmp_path_factory, search_config: SearchConfig):
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content_dir = tmp_path_factory.mktemp('content')
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# Generate Image Embeddings from Test Images
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content_config = ContentConfig()
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content_config.image = ImageContentConfig(
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input_directories = ['tests/data/images'],
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embeddings_file = content_dir.joinpath('image_embeddings.pt'),
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batch_size = 1,
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use_xmp_metadata = False)
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image_search.setup(content_config.image, search_config.image, regenerate=False)
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# Generate Notes Embeddings from Test Notes
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content_config.org = TextContentConfig(
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input_files = None,
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input_filter = ['tests/data/org/*.org'],
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compressed_jsonl = content_dir.joinpath('notes.jsonl.gz'),
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embeddings_file = content_dir.joinpath('note_embeddings.pt'))
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filters = [DateFilter(), WordFilter(), FileFilter()]
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text_search.setup(OrgToJsonl, content_config.org, search_config.asymmetric, regenerate=False, filters=filters)
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return content_config
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@pytest.fixture(scope='function')
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def new_org_file(content_config: ContentConfig):
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# Setup
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new_org_file = Path(content_config.org.input_filter[0]).parent / "new_file.org"
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new_org_file.touch()
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yield new_org_file
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# Cleanup
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if new_org_file.exists():
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new_org_file.unlink()
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@pytest.fixture(scope='function')
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def org_config_with_only_new_file(content_config: ContentConfig, new_org_file: Path):
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new_org_config = deepcopy(content_config.org)
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new_org_config.input_files = [f'{new_org_file}']
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new_org_config.input_filter = None
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return new_org_config |