git clone https://github.com/RitikPatill/synthetic-sentinel.git
cd synthetic-sentinel

# Install PyTorch CPU wheel first to avoid pulling in the large CUDA binaries
pip install torch==2.3.1 --index-url https://download.pytorch.org/whl/cpu

# Install the package and dev dependencies
pip install -e ".[dev]"

# Verify everything is wired up
pytest tests/

# Run the REST API
python -m sentinel.api          # listens on http://localhost:8000

# Or launch the interactive UI
streamlit run sentinel/app.py

sentinel photo.jpg ai_art.png https://example.com/image.jpg
sentinel --threshold 0.7 photo.jpg

curl -X POST http://localhost:8000/detect \
  -H "Content-Type: application/json" \
  -d '{"url": "https://example.com/photo.jpg"}'

{
  "score": 0.76,
  "label": "AI",
  "signals": {
    "exif_absence": 0.8,
    "dct_artifacts": 0.65,
    "noise_floor": 0.72,
    "ml_classifier": 0.81,
    "ml_available": true
  },
  "reasoning": "Scored 0.73 (AI): no camera EXIF metadata, unnaturally smooth noise floor. | ML classifier scored 0.81 (AI)."
}

{
  "mcpServers": {
    "synthetic-sentinel": {
      "command": "python",
      "args": ["-m", "sentinel.mcp_server"]
    }
  }
}

┌──────────┐  ┌───────────┐  ┌──────────────┐  ┌────────────┐
│   CLI    │  │ Streamlit │  │  FastAPI     │  │ MCP server │
│ cli.py   │  │  app.py   │  │  /detect     │  │  stdio     │
└────┬─────┘  └─────┬─────┘  └──────┬───────┘  └─────┬──────┘
     └──────────────┴───────────────┴─────────────────┘
                              │
                       ┌──────▼──────┐
                       │  Detector   │
                       │  (weighted  │
                       │   fusion)   │
                       └──────┬──────┘
                  ┌───────────┴───────────┐
           ┌──────▼──────┐         ┌──────▼──────┐
           │ Heuristics  │         │     ML      │
           │ EXIF / DCT  │         │  classifier │
           │ noise floor │         │ (HuggingFace│
           └─────────────┘         └─────────────┘

synthetic-sentinel/
├── sentinel/
│   ├── detector.py      # weighted fusion of both layers; primary public API
│   ├── heuristics.py    # EXIF absence, DCT artifact, noise-floor scorers
│   ├── ml.py            # HuggingFace pipeline wrapper with graceful fallback
│   ├── api.py           # FastAPI app; POST /detect
│   ├── mcp_server.py    # MCP stdio server; exposes detect_image tool
│   ├── cli.py           # argparse CLI; multi-target, exit-code contract
│   ├── app.py           # Streamlit demo UI
│   └── eval.py          # batch evaluation script; outputs accuracy/F1
├── tests/
│   ├── fixtures/        # real.jpg (camera EXIF present) + synthetic.jpg (none)
│   └── test_*.py        # unit + integration tests for every layer
├── docs/
│   └── demo.gif
├── pyproject.toml       # hatchling build; `sentinel` CLI entry point
├── requirements.txt     # pinned runtime deps; see torch note above
└── LICENSE