More ruff stuff

Author: DJSaunders1997

backend/fastapi_generate_quiz.py

@@ -75,15 +75,9 @@
 
 @app.get("/GenerateQuiz")
 async def generate_quiz_endpoint(
-    topic: str = Query(
-        ..., description="The subject for the quiz (e.g., 'UK History')"
-    ),
-    difficulty: str = Query(
-        ..., description="The desired difficulty (e.g., 'easy', 'medium', 'hard')"
-    ),
-    n_questions: int = Query(
-        10, description="Number of questions to generate (defaults to 10)"
-    ),
+    topic: str = Query(..., description="The subject for the quiz (e.g., 'UK History')"),
+    difficulty: str = Query(..., description="The desired difficulty (e.g., 'easy', 'medium', 'hard')"),
+    n_questions: int = Query(10, description="Number of questions to generate (defaults to 10)"),
     model: Optional[str] = Query(
         None,
         description="The model to use. If not provided, the default from QuizGenerator is used",
@@ -101,14 +95,9 @@ async def generate_quiz_endpoint(
     Returns:
       - StreamingResponse: Streams quiz questions in SSE format.
     """
-    logger.info(
-        f"Quiz request: topic={topic}, difficulty={difficulty}, "
-        f"n_questions={n_questions}, model={model}"
-    )
-
-    logging.info(
-        f"Generating quiz with: {topic=}, {difficulty=}, {n_questions=}, {model=}."
-    )
+    logger.info(f"Quiz request: topic={topic}, difficulty={difficulty}, n_questions={n_questions}, model={model}")
+
+    logging.info(f"Generating quiz with: {topic=}, {difficulty=}, {n_questions=}, {model=}.")
 
     # Create a QuizGenerator instance.
     # TODO: rename to quiz creator ?

backend/generate_image.py

@@ -5,9 +5,7 @@
 from openai import OpenAI
 
 logger = logging.getLogger(__name__)
-logging.basicConfig(
-    level=logging.INFO, format="%(asctime)s - %(levelname)s - %(message)s"
-)
+logging.basicConfig(level=logging.INFO, format="%(asctime)s - %(levelname)s - %(message)s")
 
 
 class ImageGenerator:
@@ -23,10 +21,7 @@ def get_api_key_from_env(cls) -> str:
         """
         api_key = os.getenv("OPENAI_API_KEY")
         if not api_key:
-            raise ValueError(
-                "Environment variable OPENAI_API_KEY is not set. "
-                "Please ensure it's set and try again."
-            )
+            raise ValueError("Environment variable OPENAI_API_KEY is not set. Please ensure it's set and try again.")
         return api_key
 
     def __init__(self, api_key: Optional[str] = None):
@@ -43,9 +38,7 @@ def __init__(self, api_key: Optional[str] = None):
 
         self.client = OpenAI(api_key=api_key)
 
-    def generate_image(
-        self, prompt: str, n: int = 1, size: str = "256x256"
-    ) -> Optional[str]:
+    def generate_image(self, prompt: str, n: int = 1, size: str = "256x256") -> Optional[str]:
         """Generates an image based on the provided prompt.
 
         Args:
@@ -84,10 +77,6 @@ def _get_image_url(self, prompt: str, n: int, size: str) -> Optional[str]:
 
 if __name__ == "__main__":
     # Example usage:
-    image_generator = (
-        ImageGenerator()
-    )  # Uses environment variable if no API key is provided
-    prompt_text = (
-        "Crested Gecko showcasing its distinct crests and colouration. Pixel Art"
-    )
+    image_generator = ImageGenerator()  # Uses environment variable if no API key is provided
+    prompt_text = "Crested Gecko showcasing its distinct crests and colouration. Pixel Art"
     image_url = image_generator.generate_image(prompt_text)

backend/generate_quiz.py

@@ -100,9 +100,7 @@ def check_model_is_supported(model: str) -> str:
             str: A supported model name.
         """
         if model not in QuizGenerator.SUPPORTED_MODELS:
-            logger.warning(
-                f"Model '{model}' is not supported. Defaulting to 'gpt-4-turbo'."
-            )
+            logger.warning(f"Model '{model}' is not supported. Defaulting to 'gpt-4-turbo'.")
             return "gpt-4-turbo"
         return model
 
@@ -129,9 +127,7 @@ def __init__(
         # Use the separate parser class to handle the stream.
         self.parser = ResponseStreamParser()
 
-    def generate_quiz(
-        self, topic: str, difficulty: str, n_questions: int = 10
-    ) -> Generator[str, None, None]:
+    def generate_quiz(self, topic: str, difficulty: str, n_questions: int = 10) -> Generator[str, None, None]:
         """
         Generate a quiz based on the provided topic and difficulty using litellm.
 

backend/pyproject.toml

@@ -25,7 +25,7 @@ dev = [
 dev = "uvicorn fastapi_generate_quiz:app --reload --host 0.0.0.0 --port 8000"
 
 [tool.ruff]
-line-length = 88
+line-length = 120
 target-version = "py310"
 
 [tool.ruff.lint]

backend/tests/conftest.py

@@ -3,6 +3,4 @@
 
 # Add backend directory explicitly
 sys.path.insert(0, os.path.abspath(os.path.dirname(__file__)))  # Add tests directory
-sys.path.insert(
-    0, os.path.abspath(os.path.join(os.path.dirname(__file__), ".."))
-)  # Add backend directory
+sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), "..")))  # Add backend directory

backend/tests/test_generate_image.py

@@ -31,32 +31,22 @@ def test_generate_image_success(self, mocker, image_generator):
         """Test generate_image with a successful API response."""
         # Create a mock response simulating the structure returned by OpenAI.
         mock_response = mocker.Mock()
-        mock_response.data = [
-            SimpleNamespace(url="https://example.com/generated_image.png")
-        ]
+        mock_response.data = [SimpleNamespace(url="https://example.com/generated_image.png")]
 
         # Patch the generate method of the images client.
-        mocker.patch.object(
-            image_generator.client.images, "generate", return_value=mock_response
-        )
+        mocker.patch.object(image_generator.client.images, "generate", return_value=mock_response)
 
         url = image_generator.generate_image("A test prompt")
         assert url == "https://example.com/generated_image.png"
 
     def test_generate_image_custom_size(self, mocker, image_generator):
         """Test generate_image with a custom image size."""
         mock_response = mocker.Mock()
-        mock_response.data = [
-            SimpleNamespace(url="https://example.com/custom_size_image.png")
-        ]
+        mock_response.data = [SimpleNamespace(url="https://example.com/custom_size_image.png")]
 
-        mocker.patch.object(
-            image_generator.client.images, "generate", return_value=mock_response
-        )
+        mocker.patch.object(image_generator.client.images, "generate", return_value=mock_response)
 
-        url = image_generator.generate_image(
-            "A dragon flying over mountains", size="512x512"
-        )
+        url = image_generator.generate_image("A dragon flying over mountains", size="512x512")
         assert url == "https://example.com/custom_size_image.png"
 
     def test_generate_image_api_failure(self, mocker, image_generator):
@@ -85,9 +75,7 @@ def test_openai_api_key_not_set(self, mocker):
         # Clear environment variables to simulate missing API key.
         mocker.patch.dict(os.environ, {}, clear=True)
 
-        with pytest.raises(
-            ValueError, match="Environment variable OPENAI_API_KEY is not set"
-        ):
+        with pytest.raises(ValueError, match="Environment variable OPENAI_API_KEY is not set"):
             ImageGenerator()
 
     def test_logging_when_api_fails(self, mocker, image_generator):

backend/tests/test_generate_quiz.py

@@ -36,12 +36,8 @@ class TestQuizGenerator:
 
     def test_check_model_is_supported(self):
         """Test that unsupported models default to 'gpt-4-turbo'."""
-        assert (
-            QuizGenerator.check_model_is_supported("unsupported-model") == "gpt-4-turbo"
-        )
-        assert (
-            QuizGenerator.check_model_is_supported("gpt-3.5-turbo") == "gpt-3.5-turbo"
-        )
+        assert QuizGenerator.check_model_is_supported("unsupported-model") == "gpt-4-turbo"
+        assert QuizGenerator.check_model_is_supported("gpt-3.5-turbo") == "gpt-3.5-turbo"
 
     def test_environment_variable_not_set(self, monkeypatch):
         """
@@ -79,9 +75,7 @@ def test_generate_quiz(self, mock_completion, quiz_generator):
         mock_completion.return_value = mock_stream
 
         parser_mock = MagicMock()
-        parser_mock.parse_stream.return_value = iter(
-            ['data: {"question": "What is 2+2?", "answer": "4"}\n\n']
-        )
+        parser_mock.parse_stream.return_value = iter(['data: {"question": "What is 2+2?", "answer": "4"}\n\n'])
 
         with patch.object(quiz_generator, "parser", parser_mock):
             generator = quiz_generator.generate_quiz("Math", "Easy", n_questions=1)
@@ -116,9 +110,7 @@ def test_model(self, model):
             pytest.skip("GEMINI_API_KEY not set")
         elif provider == "deepseek" and not os.getenv("DEEPSEEK_API_KEY"):
             pytest.skip("DEEPSEEK_API_KEY not set")
-        elif provider == "azure_ai" and (
-            not os.getenv("AZURE_AI_API_KEY") or not os.getenv("AZURE_AI_API_BASE")
-        ):
+        elif provider == "azure_ai" and (not os.getenv("AZURE_AI_API_KEY") or not os.getenv("AZURE_AI_API_BASE")):
             pytest.skip("Azure AI credentials not set")
 
         # Test the model

backend/tests/test_response_stream_parser.py

@@ -30,9 +30,7 @@ def test_extract_chunk_content_valid(self, response_parser):
         """
         Test extracting content from a valid chunk.
         """
-        chunk = SimpleNamespace(
-            choices=[SimpleNamespace(delta=SimpleNamespace(content="test content"))]
-        )
+        chunk = SimpleNamespace(choices=[SimpleNamespace(delta=SimpleNamespace(content="test content"))])
         content = response_parser._extract_chunk_content(chunk)
         assert content == "test content"
 
@@ -48,9 +46,7 @@ def test_split_buffer(self, response_parser):
         """
         Test splitting the buffer into complete lines and a remainder.
         """
-        response_parser.buffer = (
-            '{"question": "Who was ..."}\n{"question": "What is ..."}\nincomplete'
-        )
+        response_parser.buffer = '{"question": "Who was ..."}\n{"question": "What is ..."}\nincomplete'
 
         expected_complete_lines = [
             '{"question": "Who was ..."}',
@@ -63,13 +59,11 @@ def test_split_buffer(self, response_parser):
         print("Complete Lines:", complete_lines)
         print("Remainder:", remainder)
 
-        assert (
-            complete_lines == expected_complete_lines
-        ), f"Expected complete lines '{expected_complete_lines}', but got {complete_lines}"
+        assert complete_lines == expected_complete_lines, (
+            f"Expected complete lines '{expected_complete_lines}', but got {complete_lines}"
+        )
 
-        assert (
-            remainder == expected_remainder
-        ), f"Expected remainder '{expected_remainder}', but got {remainder}"
+        assert remainder == expected_remainder, f"Expected remainder '{expected_remainder}', but got {remainder}"
 
     def test_process_line_valid_json(self, response_parser):
         """
@@ -93,20 +87,8 @@ def test_parse_stream(self, response_parser):
         """
         fake_stream = iter(
             [
-                SimpleNamespace(
-                    choices=[
-                        SimpleNamespace(
-                            delta=SimpleNamespace(content='{"question": "First"}\n')
-                        )
-                    ]
-                ),
-                SimpleNamespace(
-                    choices=[
-                        SimpleNamespace(
-                            delta=SimpleNamespace(content='{"question": "Second"}\n')
-                        )
-                    ]
-                ),
+                SimpleNamespace(choices=[SimpleNamespace(delta=SimpleNamespace(content='{"question": "First"}\n'))]),
+                SimpleNamespace(choices=[SimpleNamespace(delta=SimpleNamespace(content='{"question": "Second"}\n'))]),
             ]
         )
         results = list(response_parser.parse_stream(fake_stream))