This guide is the shortest path from a fresh checkout to a running development build. For a fuller setup guide, see docs/installation.md.
- Python 3.11 recommended
- FFmpeg available on
PATH - macOS, Linux, or Windows, depending on the model backend you use
- Internet access for first-time model weight downloads
On macOS, install FFmpeg with Homebrew if needed:
brew install ffmpegOn Ubuntu:
sudo apt update
sudo apt install ffmpeggit clone https://github.com/hockeytek/KeyFlowStudio.git
cd KeyFlowStudio
python3 -m venv .venv
source .venv/bin/activate
pip install --upgrade pip
pip install -r requirements.txtYou can also run the helper script from the repository root:
bash setup.shThe helper checks Python and FFmpeg, creates .venv when needed, installs requirements.txt, and offers optional MatAnyone2 package installation.
python main.pyOr use the repository helper:
bash run.sh- Open KeyFlow Studio.
- Load source media through the app UI or a Load/Source node.
- Open the node graph editor.
- Use a built-in preset or connect a minimal graph such as
Source/Load -> keying or matting node -> Write. - Run the graph and check diagnostics, preview, and write outputs.
For node compatibility and runtime behavior, see docs/NODE_GRAPH_STANDARD.md and docs/node-rules/.
Model weights are not stored in Git. KeyFlow Studio uses the configured model cache and downloads supported weights automatically when the upstream source allows it.
Use KEYFLOW_MODELS_DIR when you want an explicit local cache location:
export KEYFLOW_MODELS_DIR="$HOME/.local/share/com.keyflow.studio/models"
python main.pySome models may still require manual license acceptance, private tokens, or local source installation. See docs/models.md.
Run the lightweight UI smoke test:
PYTHONPATH="$PWD" python -m pytest tests/test_node_graph_dialog_smoke.py -qRun the P1 regression helper:
./run_p1.shOptional device override:
./run_p1.sh --device cpu
./run_p1.sh --device mps
./run_p1.sh --device auto