local (default, free): scene illustrations from Stable Diffusion on your own GPU, narration from local text to speech, slow pan and stitch with ffmpeg. No API costs and no quotas.
veo (optional, paid): true AI video from Google's Veo through the Gemini API. Needs billing enabled.

Scripts and tags always come from a local Ollama model, so text generation is free either way.

Requirements

Python 3.10+, ffmpeg, Ollama (installed by install.sh)
Ollama models: llama3.1:8b for text, llama3.2-vision for kids frame checks
For the local engine: about 15 GB of disk for torch and the image model
For the veo engine: a Gemini API key with billing enabled
Google Cloud project with YouTube Data API v3 enabled

Google OAuth setup

Google Cloud Console: enable YouTube Data API v3.
Create an OAuth client of type Web application.
Add redirect URI http://localhost:8000/auth/callback.
Download the JSON at creation time, rename it client_secret.json, and put it next to app.py.
Add your Google account as a test user, or publish the app so logins do not expire weekly.

Install and run

chmod +x install.sh run.sh install-local.sh
./install.sh
./install-local.sh
./run.sh

Open http://localhost:8000

Settings: set the folders, pick the video engine, adjust the profile, then Save.
Dashboard: Link YouTube channel to this profile.
Click GO.

Folders

All large writes are configurable in Settings, so nothing has to land on a small internal disk:

Storage folder: job folders and finished videos
Models folder: AI model downloads (several GB)
Temp folder: scratch space during rendering

Layout under the storage folder:

output/<profile>/<job>/      in progress or failed jobs
published/<profile>/<job>/   uploaded to YouTube

App settings, profiles, OAuth tokens, and logs live in data/. The log file is data/logs/app.log.

To keep the virtual environment off the internal disk:

mv .venv /Volumes/YourDisk/shorts-autopilot/venv
ln -s /Volumes/YourDisk/shorts-autopilot/venv .venv

Profiles

Each profile has its own audience settings and its own linked YouTube channel. Generation settings and folders are shared. Use one profile per channel and switch with the dropdown.

Made for kids

When enabled on a profile:

Uploads are flagged as made for kids and as AI generated
Scripts pass hard-coded word and call-to-action filters
An LLM reviews each script in advisory, block, or off mode
Every generated scene is checked by a local vision model
Uploads are held as private for manual review by default

Also set the channel audience to made for kids in YouTube Studio.

Notes

Uploads cost about 1,600 of the default 10,000 daily API quota units.
Uploads from unverified Google API projects are locked to private until the project passes Google's audit.
If Ollama stops responding, restart it: brew services restart ollama on macOS, sudo systemctl restart ollama on Linux.