| # LLM Hallucination Detector Guidelines | |
| ## Commands | |
| - Setup: `pip install -r requirements.txt` | |
| - Configure: Set environment variables `HF_MISTRAL_API_KEY` and `HF_OPENAI_API_KEY` | |
| - Run: `python app.py` | |
| - Lint: `ruff check app.py` | |
| - Format: `black app.py` | |
| - Type check: `mypy app.py` | |
| ## Code Style | |
| - Follow PEP 8 conventions with 4-space indentation | |
| - Use type hints with Pydantic for data validation | |
| - Write descriptive docstrings using triple quotes | |
| - Name variables/functions in snake_case, classes in PascalCase | |
| - Organize imports: stdlib first, then third-party, then local | |
| - Exception handling: use try/except blocks with specific exceptions | |
| - Constants should be UPPERCASE and defined at class/module level | |
| - Prefer f-strings over other string formatting methods | |
| ## Architecture | |
| - App uses Gradio for UI, SQLite for persistence | |
| - LLM integration with Mistral Large and OpenAI o3-mini | |
| - Paraphrase-based approach for hallucination detection | |
| - Maintain clean separation between UI and backend logic |