ba20c2dc63
- FastAPI server on port 8100
- POST /runs to start rendering jobs
- GET /runs/{id} to check status
- Cache and run persistence in Redis
- Auto-generated API docs at /docs
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
116 lines
2.6 KiB
Markdown
116 lines
2.6 KiB
Markdown
# Art Celery
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L1 rendering server for the Art DAG system. Manages distributed rendering jobs via Celery workers.
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## Dependencies
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- **artdag** (GitHub): Core DAG execution engine
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- **artdag-effects** (rose-ash): Effect implementations
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- **Redis**: Message broker, result backend, and run persistence
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## Setup
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```bash
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# Install Redis
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sudo apt install redis-server
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# Install Python dependencies
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pip install -r requirements.txt
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# Start a worker
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celery -A celery_app worker --loglevel=info
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# Start the L1 server
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python server.py
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```
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## L1 Server API
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Interactive docs: http://localhost:8100/docs
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### Endpoints
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| Method | Path | Description |
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|--------|------|-------------|
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| GET | `/` | Server info |
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| POST | `/runs` | Start a rendering run |
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| GET | `/runs` | List all runs |
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| GET | `/runs/{run_id}` | Get run status |
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| GET | `/cache` | List cached content hashes |
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| GET | `/cache/{hash}` | Download cached content |
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| POST | `/cache/import?path=` | Import local file to cache |
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| GET | `/assets` | List known assets |
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### Start a run
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```bash
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curl -X POST http://localhost:8100/runs \
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-H "Content-Type: application/json" \
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-d '{"recipe": "dog", "inputs": ["33268b6e..."], "output_name": "my-output"}'
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```
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### Check run status
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```bash
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curl http://localhost:8100/runs/{run_id}
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```
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## Storage
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- **Cache**: `~/.artdag/cache/` (content-addressed files)
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- **Runs**: Redis db 5, keys `artdag:run:*` (persists across restarts)
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## CLI Usage
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```bash
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# Render cat through dog effect
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python render.py dog cat --sync
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# Render cat through identity effect
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python render.py identity cat --sync
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# Submit async (don't wait)
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python render.py dog cat
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```
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## Architecture
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```
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server.py (L1 Server - FastAPI)
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│
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├── POST /runs → Submit job
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│ │
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│ ▼
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│ celery_app.py (Celery broker)
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│ │
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│ ▼
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│ tasks.py (render_effect task)
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│ │
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│ ├── artdag (GitHub) - DAG execution
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│ └── artdag-effects (rose-ash) - Effects
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│ │
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│ ▼
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│ Output + Provenance
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│
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└── GET /cache/{hash} → Retrieve output
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```
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## Provenance
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Every render produces a provenance record:
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```json
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{
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"task_id": "celery-task-uuid",
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"rendered_at": "2026-01-07T...",
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"rendered_by": "@giles@artdag.rose-ash.com",
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"output": {"name": "...", "content_hash": "..."},
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"inputs": [...],
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"effects": [...],
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"infrastructure": {
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"software": {"name": "infra:artdag", "content_hash": "..."},
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"hardware": {"name": "infra:giles-hp", "content_hash": "..."}
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}
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}
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```
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