mirror of
https://github.com/khoj-ai/khoj.git
synced 2024-11-23 23:48:56 +01:00
228 lines
7.5 KiB
Python
228 lines
7.5 KiB
Python
# Standard Modules
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from pathlib import Path
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# External Packages
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import pytest
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from fastapi.testclient import TestClient
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# Internal Packages
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from src.main import app, search_config, model
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from src.search_type import asymmetric, image_search
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from src.utils.config import SearchConfig, TextSearchConfig, ImageSearchConfig
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from src.utils.helpers import resolve_absolute_path
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# Arrange
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# ----------------------------------------------------------------------------------------------------
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client = TestClient(app)
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# Test
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# ----------------------------------------------------------------------------------------------------
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def test_search_with_invalid_search_type():
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# Arrange
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user_query = "How to call semantic search from Emacs?"
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# Act
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response = client.get(f"/search?q={user_query}&t=invalid_search_type")
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# Assert
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assert response.status_code == 422
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# ----------------------------------------------------------------------------------------------------
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def test_search_with_valid_search_type():
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# Arrange
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for search_type in ["notes", "ledger", "music", "image"]:
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# Act
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response = client.get(f"/search?q=random&t={search_type}")
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# Assert
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assert response.status_code == 200
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# ----------------------------------------------------------------------------------------------------
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def test_regenerate_with_invalid_search_type():
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# Act
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response = client.get(f"/regenerate?t=invalid_search_type")
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# Assert
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assert response.status_code == 422
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# ----------------------------------------------------------------------------------------------------
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def test_regenerate_with_valid_search_type():
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# Arrange
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for search_type in ["notes", "ledger", "music", "image"]:
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# Act
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response = client.get(f"/regenerate?t={search_type}")
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# Assert
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assert response.status_code == 200
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# ----------------------------------------------------------------------------------------------------
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def test_notes_search():
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# Arrange
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search_config = SearchConfig()
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search_config.notes = TextSearchConfig(
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input_files = [Path('tests/data/main_readme.org'), Path('tests/data/interface_emacs_readme.org')],
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input_filter = None,
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compressed_jsonl = Path('tests/data/.test.jsonl.gz'),
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embeddings_file = Path('tests/data/.test_embeddings.pt'),
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verbose = 0)
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# Act
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# Regenerate embeddings during asymmetric setup
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notes_model = asymmetric.setup(search_config.notes, regenerate=True)
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# Assert
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assert len(notes_model.entries) == 10
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assert len(notes_model.corpus_embeddings) == 10
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# Arrange
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model.notes_search = notes_model
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user_query = "How to git install application?"
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# Act
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response = client.get(f"/search?q={user_query}&n=1&t=notes")
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# Assert
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assert response.status_code == 200
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# assert actual_data contains "Semantic Search via Emacs"
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search_result = response.json()[0]["Entry"]
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assert "git clone" in search_result
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# ----------------------------------------------------------------------------------------------------
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def test_notes_search_with_include_filter():
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# Arrange
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search_config = SearchConfig()
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search_config.notes = TextSearchConfig(
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input_files = [Path('tests/data/main_readme.org'), Path('tests/data/interface_emacs_readme.org')],
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input_filter = None,
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compressed_jsonl = Path('tests/data/.test.jsonl.gz'),
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embeddings_file = Path('tests/data/.test_embeddings.pt'),
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verbose = 0)
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# Act
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# Regenerate embeddings during asymmetric setup
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notes_model = asymmetric.setup(search_config.notes, regenerate=True)
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# Assert
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assert len(notes_model.entries) == 10
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assert len(notes_model.corpus_embeddings) == 10
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# Arrange
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model.notes_search = notes_model
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user_query = "How to git install application? +Emacs"
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# Act
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response = client.get(f"/search?q={user_query}&n=1&t=notes")
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# Assert
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assert response.status_code == 200
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# assert actual_data does not contains explicitly excluded word "Emacs"
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search_result = response.json()[0]["Entry"]
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assert "Emacs" in search_result
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# ----------------------------------------------------------------------------------------------------
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def test_notes_search_with_exclude_filter():
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# Arrange
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search_config = SearchConfig()
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search_config.notes = TextSearchConfig(
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input_files = [Path('tests/data/main_readme.org'), Path('tests/data/interface_emacs_readme.org')],
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input_filter = None,
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compressed_jsonl = Path('tests/data/.test.jsonl.gz'),
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embeddings_file = Path('tests/data/.test_embeddings.pt'),
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verbose = 0)
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# Act
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# Regenerate embeddings during asymmetric setup
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notes_model = asymmetric.setup(search_config.notes, regenerate=True)
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# Assert
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assert len(notes_model.entries) == 10
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assert len(notes_model.corpus_embeddings) == 10
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# Arrange
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model.notes_search = notes_model
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user_query = "How to git install application? -clone"
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# Act
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response = client.get(f"/search?q={user_query}&n=1&t=notes")
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# Assert
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assert response.status_code == 200
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# assert actual_data does not contains explicitly excluded word "Emacs"
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search_result = response.json()[0]["Entry"]
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assert "clone" not in search_result
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# ----------------------------------------------------------------------------------------------------
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def test_image_search():
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# Arrange
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search_config = SearchConfig()
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search_config.image = ImageSearchConfig(
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input_directory = Path('tests/data'),
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embeddings_file = Path('tests/data/.image_embeddings.pt'),
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batch_size = 10,
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use_xmp_metadata = False,
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verbose = 2)
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# Act
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model.image_search = image_search.setup(search_config.image, regenerate=True)
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# Assert
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assert len(model.image_search.image_names) == 3
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assert len(model.image_search.image_embeddings) == 3
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# Arrange
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for query, expected_image_name in [("kitten in a park", "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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# Act
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hits = image_search.query(
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query,
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count = 1,
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model = model.image_search)
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results = image_search.collate_results(
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hits,
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model.image_search.image_names,
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search_config.image.input_directory,
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count=1)
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actual_image = results[0]["Entry"]
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expected_image = resolve_absolute_path(search_config.image.input_directory.joinpath(expected_image_name))
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# Assert
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assert expected_image == actual_image
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# ----------------------------------------------------------------------------------------------------
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def test_notes_regenerate():
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# Arrange
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search_config = SearchConfig()
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search_config.notes = TextSearchConfig(
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input_files = [Path('tests/data/main_readme.org'), Path('tests/data/interface_emacs_readme.org')],
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input_filter = None,
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compressed_jsonl = Path('tests/data/.test.jsonl.gz'),
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embeddings_file = Path('tests/data/.test_embeddings.pt'),
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verbose = 0)
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# Act
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# Regenerate embeddings during asymmetric setup
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notes_model = asymmetric.setup(search_config.notes, regenerate=True)
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# Assert
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assert len(notes_model.entries) == 10
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assert len(notes_model.corpus_embeddings) == 10
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# Arrange
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model.notes_search = notes_model
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# Act
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response = client.get(f"/regenerate?t=notes")
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# Assert
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assert response.status_code == 200
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