Remove mkdocs, cleanup Makefile, move test (#11)

* cleaned up a bit
* various cleanup
* move test

Author: fpgmaas

Makefile

@@ -24,18 +24,14 @@ build: ## Build wheel file using poetry
 	@echo "🚀 Creating wheel file"
 	@poetry build
 
-.PHONY: docs-test
-docs-test: ## Test if documentation can be built without warnings or errors
-	@poetry run mkdocs build -s
-
-.PHONY: docs
-docs: ## Build and serve the documentation
-	@poetry run mkdocs serve
-
 .PHONY: serve
-serve: ## Serve API with uvicorn
+serve: ## Serve API with uvicorn in development mode
 	@poetry run uvicorn pypi_scout.api.main:app --reload
 
+.PHONY: frontend
+frontend: ## Serve frontend in development mode
+	@cd frontend; npm run dev
+
 .PHONY: help
 help:
 	@grep -E '^[a-zA-Z_-]+:.*?## .*$$' $(MAKEFILE_LIST) | awk 'BEGIN {FS = ":.*?## "}; {printf "\033[36m%-20s\033[0m %s\n", $$1, $$2}'

poetry.lock

@@ -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"]

pyproject.toml

@@ -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)