Jenesyx/reel-setup

Arta Edit Studio — setup

Get a fresh clone ready for /reel-story and /reel-split, then personalise it. Explain each step in one plain sentence before running it — many users are not developers. Ask before anything that downloads or installs (packages, fonts, model weights) and say roughly how big it is.

Arguments: $ARGUMENTS

1. Check the machine — report as a ✅ / ❌ table

Need	Check	Fix if missing
Python ≥ 3.10	python --version	python.org
Node ≥ 18	node --version	nodejs.org (LTS)
ffmpeg with zscale	ffmpeg -hide_banner -filters contains zscale	Windows: gyan.dev "full" build · macOS: brew install ffmpeg
NVIDIA GPU (optional)	nvidia-smi	none → Whisper runs on CPU, ~10× slower
Chrome for rendering	npx hyperframes doctor (after step 2)	doctor says what to do

2. Install (ask first)

1. python -m venv .venv
2. PyTorch — the command from pytorch.org for this OS; with an NVIDIA GPU pick the CUDA build (~2.5 GB), else CPU.
3. .venv/Scripts/python -m pip install -r requirements.txt (macOS/Linux: .venv/bin/python).
4. npm install (HyperFrames renderer, GSAP, Lucide icons).
5. npx hyperframes doctor — fix what it flags.
6. Tell the user: the Whisper large-v3 model (~3 GB) downloads on the first transcription.

3. Fonts

Read fonts in the config. For each file missing from font/, tell the user where the free default comes from and offer to download it (ask first):

• Farsi Vazirmatn-Medium.ttf — github.com/rastikerdar/vazirmatn (releases), OFL
• Latin Poppins-SemiBold.ttf and display Poppins-Black.ttf — fonts.google.com/specimen/Poppins, OFL

Any other font works: put the file in font/ and change the path in the config.

4. Personal config

If reel.config.json does not exist, copy reel.config.example.json to it, then ask in one message (skip what the arguments already answered):

• name and Instagram handle (for the follow card)
• spoken language of the videos (fa, en, ar, de, …)
• brand / product name (optional) and its colours — or a logo file to pick colours from
• mascot / character images (optional) → put them in assets/mascot/; a logo → assets/brand/logo.png
• where their B-roll clips are (default assets/broll/)

Write the answers into reel.config.json (keep every key the example has).

5. Smoke test

• .venv/Scripts/python -X utf8 -c "import sys; sys.path.insert(0,'tools'); import config, story_build, showcase_build; print('tools ok')"
• If a video is already in raw/: $PY tools/face_track.py <take> should print a face position.

6. Hand-off

Print a short "how to use" with one example each, in the user's language: /reel-story <take> <topic, comment keyword, names> and /reel-split <take> ….