pyproject.toml

[project]
name = "medea"
version = "0.1.0"
description = "AI-generated YouTube video detector. Multi-modal embedding + vector search + classifier head."
requires-python = ">=3.12,<3.13"
dependencies = [
    # Ingest
    "yt-dlp>=2026.1.0",
    "ffmpeg-python>=0.2.0",
    "imageio-ffmpeg>=0.5.1",
    # Core ML
    "torch>=2.5.0",
    "torchvision>=0.20.0",
    "torchaudio>=2.5.0",
    "numpy>=1.26",
    "pandas>=2.2",
    "pyarrow>=15.0",
    "scikit-learn>=1.5",
    # Embeddings
    "open-clip-torch>=2.30.0",
    "faster-whisper>=1.1.0",
    "transformers>=4.45",
    "sentence-transformers>=3.2",
    # Audio
    "soundfile>=0.12",
    "librosa>=0.10",
    # Video frame sampling
    "opencv-python>=4.10",
    "pillow>=10.4",
    # Vector DB
    "chromadb>=0.5.20",
    # Tracking
    "mlflow>=2.18",
    # CLI / API
    "typer>=0.13",
    "fastapi>=0.115",
    "uvicorn>=0.32",
    "pydantic>=2.9",
    # Utility
    "rich>=13.9",
    "tqdm>=4.66",
    # Local-LLM RAG rationale (no API keys; talks to localhost:11434).
    # Install Ollama from https://ollama.com/download and pull the default
    # model via `ollama pull qwen2.5:7b-instruct-q4_K_M` to enable the LLM
    # render path. Falls back to a deterministic rule-based rationale when
    # the daemon isn't running.
    "ollama>=0.4",
    # Notebook / viz (used by exploration notebook in M5)
    "jupyter>=1.1",
    "umap-learn>=0.5",
    "matplotlib>=3.9",
    # CUDA libs needed by ctranslate2 (faster-whisper backend) on Windows GPU
    "nvidia-cublas-cu12; platform_system == 'Windows'",
    "nvidia-cudnn-cu12>=9,<10; platform_system == 'Windows'",
]

[project.scripts]
medea = "medea.cli:app"

[build-system]
requires = ["hatchling"]
build-backend = "hatchling.build"

[tool.hatch.build.targets.wheel]
packages = ["src/medea"]

# CUDA-enabled PyTorch from the official index.
# Comment these blocks out if you want CPU-only torch (works but slow).
[[tool.uv.index]]
name = "pytorch-cu121"
url = "https://download.pytorch.org/whl/cu121"
explicit = true

[tool.uv.sources]
torch = { index = "pytorch-cu121" }
torchvision = { index = "pytorch-cu121" }
torchaudio = { index = "pytorch-cu121" }