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{file = "websocket_client-1.8.0.tar.gz", hash = "sha256:3239df9f44da632f96012472805d40a23281a991027ce11d2f45a6f24ac4c3da"}, -] - -[package.extras] -docs = ["Sphinx (>=6.0)", "myst-parser (>=2.0.0)", "sphinx-rtd-theme (>=1.1.0)"] -optional = ["python-socks", "wsaccel"] -test = ["websockets"] - [[package]] name = "websockets" version = "12.0" @@ -5053,4 +3305,4 @@ test = ["big-O", "importlib-resources", "jaraco.functools", "jaraco.itertools", [metadata] lock-version = "2.0" python-versions = ">=3.9,<4.0" -content-hash = "de83ca89b79716cfc21e06d916d81963401155a517238f9ff066b31ef349a160" +content-hash = "32f2cd0f5a83447abbe6aceece708ca2ac68784b17f229e003e2c521b829ec44" diff --git a/pyproject.toml b/pyproject.toml index 7d51b9d..ebe5d94 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -35,12 +35,6 @@ pytest-mock = "^3.14.0" deptry = "^0.12.0" pre-commit = "^3.4.0" tox = "^4.11.1" -jupyterlab = "^4.2.2" - -[tool.poetry.group.docs.dependencies] -mkdocs = "^1.4.2" -mkdocs-material = "^9.2.7" -mkdocstrings = {extras = ["python"], version = "^0.23.0"} [build-system] requires = ["poetry-core>=1.0.0"] diff --git a/tests/test_vdb.py b/tests/embeddings/test_simple_vector_database.py similarity index 79% rename from tests/test_vdb.py rename to tests/embeddings/test_simple_vector_database.py index ea40271..4d50e00 100644 --- a/tests/test_vdb.py +++ b/tests/embeddings/test_simple_vector_database.py @@ -33,9 +33,7 @@ def vector_db(mock_model, df_embeddings): def test_embeddings_matrix_creation(vector_db): - expected_matrix = np.array( - [[0.1, 0.2, 0.3], [0.4, 0.5, 0.6], [0.7, 0.8, 0.9]], dtype=np.float32 - ) # Ensure the expected matrix has dtype float32 + expected_matrix = np.array([[0.1, 0.2, 0.3], [0.4, 0.5, 0.6], [0.7, 0.8, 0.9]], dtype=np.float32) np.testing.assert_allclose(vector_db.embeddings_matrix, expected_matrix, rtol=1e-6, atol=1e-8) @@ -44,13 +42,10 @@ def test_find_similar(vector_db): query = "Hello" result = vector_db.find_similar(query, top_k=2) - # Check that the result has the expected number of rows assert result.shape[0] == 2 - # Check that the similarity scores are between 0 and 1 assert result["similarity"].min() >= 0 assert result["similarity"].max() <= 1 - # Check that the result contains the expected columns expected_columns = ["id", "text", "similarity"] assert set(result.columns) == set(expected_columns)