# Art Celery

L1 rendering server for the Art DAG system. Manages distributed rendering jobs via Celery workers.

## Dependencies

- **artdag** (GitHub): Core DAG execution engine
- **artdag-effects** (rose-ash): Effect implementations
- **Redis**: Message broker, result backend, and run persistence

## Setup

```bash
# 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

# Start the L1 server
python server.py
```

## L1 Server API

Interactive docs: http://localhost:8100/docs

### Endpoints

| Method | Path | Description |
|--------|------|-------------|
| GET | `/` | Server info |
| POST | `/runs` | Start a rendering run |
| GET | `/runs` | List all runs |
| GET | `/runs/{run_id}` | Get run status |
| GET | `/cache` | List cached content hashes |
| GET | `/cache/{hash}` | Download cached content |
| POST | `/cache/import?path=` | Import local file to cache |
| GET | `/assets` | List known assets |

### Start a run

```bash
curl -X POST http://localhost:8100/runs \
  -H "Content-Type: application/json" \
  -d '{"recipe": "dog", "inputs": ["33268b6e..."], "output_name": "my-output"}'
```

### Check run status

```bash
curl http://localhost:8100/runs/{run_id}
```

## Storage

- **Cache**: `~/.artdag/cache/` (content-addressed files)
- **Runs**: Redis db 5, keys `artdag:run:*` (persists across restarts)

## CLI Usage

```bash
# 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

```
server.py (L1 Server - FastAPI)
    │
    ├── POST /runs → Submit job
    │       │
    │       ▼
    │   celery_app.py (Celery broker)
    │       │
    │       ▼
    │   tasks.py (render_effect task)
    │       │
    │       ├── artdag (GitHub) - DAG execution
    │       └── artdag-effects (rose-ash) - Effects
    │               │
    │               ▼
    │           Output + Provenance
    │
    └── GET /cache/{hash} → Retrieve output
```

## Provenance

Every render produces a provenance record:

```json
{
  "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": "..."}
  }
}
```