500e57b9a4
- celery_app.py: Celery configuration with Redis broker - tasks.py: render_effect task with full provenance tracking - render.py: CLI for submitting render jobs - Successfully renders cat → dog with provenance chain 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
1.4 KiB
1.4 KiB
Art Celery
Distributed rendering for the Art DAG system using Celery.
Dependencies
- artdag (GitHub): Core DAG execution engine
- artdag-effects (rose-ash): Effect implementations
- Redis: Message broker and result backend
Setup
# Install Redis
sudo apt install redis-server
# Install Python dependencies
pip install -r requirements.txt
# Start a worker
celery -A celery_app worker --loglevel=info
Usage
# Render cat through dog effect
python render.py dog cat --sync
# Render cat through identity effect
python render.py identity cat --sync
# Submit async (don't wait)
python render.py dog cat
Architecture
render.py (CLI)
│
▼
celery_app.py (Celery broker)
│
▼
tasks.py (render_effect task)
│
├── artdag (GitHub) - DAG execution
└── artdag-effects (rose-ash) - Effect implementations
│
▼
Provenance JSON + Output file
Provenance
Every render produces a provenance record:
{
"task_id": "celery-task-uuid",
"rendered_at": "2026-01-07T...",
"rendered_by": "@giles@artdag.rose-ash.com",
"output": {"name": "...", "content_hash": "..."},
"inputs": [...],
"effects": [...],
"infrastructure": {
"software": {"name": "infra:artdag", "content_hash": "..."},
"hardware": {"name": "infra:giles-hp", "content_hash": "..."}
}
}