#!/usr/bin/env python3
"""
Art DAG L1 Server
Manages rendering runs and provides access to the cache.
- POST /runs - start a run (recipe + inputs)
- GET /runs/{run_id} - get run status/result
- GET /cache/{content_hash} - get cached content
"""
import hashlib
import json
import os
import uuid
from datetime import datetime, timezone
from pathlib import Path
from typing import Optional
from fastapi import FastAPI, HTTPException, UploadFile, File
from fastapi.responses import FileResponse, HTMLResponse
from pydantic import BaseModel
import redis
from urllib.parse import urlparse
from celery_app import app as celery_app
from tasks import render_effect
# Cache directory (use /data/cache in Docker, ~/.artdag/cache locally)
CACHE_DIR = Path(os.environ.get("CACHE_DIR", str(Path.home() / ".artdag" / "cache")))
CACHE_DIR.mkdir(parents=True, exist_ok=True)
# Redis for persistent run storage
REDIS_URL = os.environ.get('REDIS_URL', 'redis://localhost:6379/5')
parsed = urlparse(REDIS_URL)
redis_client = redis.Redis(
host=parsed.hostname or 'localhost',
port=parsed.port or 6379,
db=int(parsed.path.lstrip('/') or 0)
)
RUNS_KEY_PREFIX = "artdag:run:"
def save_run(run: "RunStatus"):
"""Save run to Redis."""
redis_client.set(f"{RUNS_KEY_PREFIX}{run.run_id}", run.model_dump_json())
def load_run(run_id: str) -> Optional["RunStatus"]:
"""Load run from Redis."""
data = redis_client.get(f"{RUNS_KEY_PREFIX}{run_id}")
if data:
return RunStatus.model_validate_json(data)
return None
def list_all_runs() -> list["RunStatus"]:
"""List all runs from Redis."""
runs = []
for key in redis_client.scan_iter(f"{RUNS_KEY_PREFIX}*"):
data = redis_client.get(key)
if data:
runs.append(RunStatus.model_validate_json(data))
return sorted(runs, key=lambda r: r.created_at, reverse=True)
app = FastAPI(
title="Art DAG L1 Server",
description="Distributed rendering server for Art DAG",
version="0.1.0"
)
class RunRequest(BaseModel):
"""Request to start a run."""
recipe: str # Recipe name (e.g., "dog", "identity")
inputs: list[str] # List of content hashes
output_name: Optional[str] = None
class RunStatus(BaseModel):
"""Status of a run."""
run_id: str
status: str # pending, running, completed, failed
recipe: str
inputs: list[str]
output_name: str
created_at: str
completed_at: Optional[str] = None
output_hash: Optional[str] = None
error: Optional[str] = None
celery_task_id: Optional[str] = None
def file_hash(path: Path) -> str:
"""Compute SHA3-256 hash of a file."""
hasher = hashlib.sha3_256()
with open(path, "rb") as f:
for chunk in iter(lambda: f.read(65536), b""):
hasher.update(chunk)
return hasher.hexdigest()
def cache_file(source: Path) -> str:
"""Copy file to cache, return content hash."""
content_hash = file_hash(source)
cache_path = CACHE_DIR / content_hash
if not cache_path.exists():
import shutil
shutil.copy2(source, cache_path)
return content_hash
@app.get("/api")
async def api_info():
"""Server info (JSON)."""
return {
"name": "Art DAG L1 Server",
"version": "0.1.0",
"cache_dir": str(CACHE_DIR),
"runs_count": len(list_all_runs())
}
HOME_HTML = """
Art DAG L1 Server
Art DAG L1 Server
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
API Endpoints
Method Path Description
GET /uiWeb UI for viewing runs
POST /runsStart a rendering run
GET /runsList all runs
GET /runs/{run_id}Get run status
GET /cacheList cached content hashes
GET /cache/{hash}Download cached content
POST /cache/uploadUpload file to cache
GET /assetsList known assets
Start a Run
curl -X POST /runs \\
-H "Content-Type: application/json" \\
-d '{"recipe": "dog", "inputs": ["33268b6e..."]}'
Provenance
Every render produces a provenance record linking inputs, effects, and infrastructure:
{
"output": {"content_hash": "..."},
"inputs": [...],
"effects": [...],
"infrastructure": {...}
}
"""
@app.get("/", response_class=HTMLResponse)
async def root():
"""Home page."""
return HOME_HTML
@app.post("/runs", response_model=RunStatus)
async def create_run(request: RunRequest):
"""Start a new rendering run."""
run_id = str(uuid.uuid4())
# Generate output name if not provided
output_name = request.output_name or f"{request.recipe}-{run_id[:8]}"
# Create run record
run = RunStatus(
run_id=run_id,
status="pending",
recipe=request.recipe,
inputs=request.inputs,
output_name=output_name,
created_at=datetime.now(timezone.utc).isoformat()
)
# Submit to Celery
# For now, we only support single-input recipes
if len(request.inputs) != 1:
raise HTTPException(400, "Currently only single-input recipes supported")
input_hash = request.inputs[0]
task = render_effect.delay(input_hash, request.recipe, output_name)
run.celery_task_id = task.id
run.status = "running"
save_run(run)
return run
@app.get("/runs/{run_id}", response_model=RunStatus)
async def get_run(run_id: str):
"""Get status of a run."""
run = load_run(run_id)
if not run:
raise HTTPException(404, f"Run {run_id} not found")
# Check Celery task status if running
if run.status == "running" and run.celery_task_id:
task = celery_app.AsyncResult(run.celery_task_id)
if task.ready():
if task.successful():
result = task.result
run.status = "completed"
run.completed_at = datetime.now(timezone.utc).isoformat()
run.output_hash = result.get("output", {}).get("content_hash")
# Cache the output
output_path = Path(result.get("output", {}).get("local_path", ""))
if output_path.exists():
cache_file(output_path)
else:
run.status = "failed"
run.error = str(task.result)
# Save updated status
save_run(run)
return run
@app.get("/runs")
async def list_runs():
"""List all runs."""
return list_all_runs()
@app.get("/cache/{content_hash}")
async def get_cached(content_hash: str):
"""Get cached content by hash."""
cache_path = CACHE_DIR / content_hash
if not cache_path.exists():
raise HTTPException(404, f"Content {content_hash} not in cache")
return FileResponse(cache_path)
@app.get("/cache")
async def list_cache():
"""List cached content hashes."""
return [f.name for f in CACHE_DIR.iterdir() if f.is_file()]
# Known assets (bootstrap data)
KNOWN_ASSETS = {
"cat": "33268b6e167deaf018cc538de12dbe562612b33e89a749391cef855b320a269b",
}
@app.get("/assets")
async def list_assets():
"""List known assets."""
return KNOWN_ASSETS
@app.post("/cache/import")
async def import_to_cache(path: str):
"""Import a local file to cache."""
source = Path(path)
if not source.exists():
raise HTTPException(404, f"File not found: {path}")
content_hash = cache_file(source)
return {"content_hash": content_hash, "cached": True}
@app.post("/cache/upload")
async def upload_to_cache(file: UploadFile = File(...)):
"""Upload a file to cache."""
# Write to temp file first
import tempfile
with tempfile.NamedTemporaryFile(delete=False) as tmp:
content = await file.read()
tmp.write(content)
tmp_path = Path(tmp.name)
# Hash and move to cache
content_hash = file_hash(tmp_path)
cache_path = CACHE_DIR / content_hash
if not cache_path.exists():
import shutil
shutil.move(str(tmp_path), cache_path)
else:
tmp_path.unlink()
return {"content_hash": content_hash, "filename": file.filename, "size": len(content)}
def detect_media_type(cache_path: Path) -> str:
"""Detect if file is image or video based on magic bytes."""
with open(cache_path, "rb") as f:
header = f.read(32)
# Video signatures
if header[:4] == b'\x1a\x45\xdf\xa3': # WebM/MKV
return "video"
if header[4:8] == b'ftyp': # MP4/MOV
return "video"
if header[:4] == b'RIFF' and header[8:12] == b'AVI ': # AVI
return "video"
# Image signatures
if header[:8] == b'\x89PNG\r\n\x1a\n': # PNG
return "image"
if header[:2] == b'\xff\xd8': # JPEG
return "image"
if header[:6] in (b'GIF87a', b'GIF89a'): # GIF
return "image"
if header[:4] == b'RIFF' and header[8:12] == b'WEBP': # WebP
return "image"
return "unknown"
UI_HTML = """
Art DAG L1 Server
Art DAG L1 Server
Refresh
Loading...
"""
@app.get("/ui", response_class=HTMLResponse)
async def ui_index():
"""Web UI for viewing runs."""
return UI_HTML
@app.get("/ui/runs", response_class=HTMLResponse)
async def ui_runs():
"""HTMX partial: list of runs."""
runs = list_all_runs()
if not runs:
return 'No runs yet.
'
html_parts = ['']
for run in runs[:20]: # Limit to 20 most recent
status_class = run.status
html_parts.append(f'''
Created: {run.created_at[:19].replace('T', ' ')}
''')
# Show input
if run.inputs:
input_hash = run.inputs[0]
html_parts.append(f'
Input: {input_hash[:32]}...
')
input_cache_path = CACHE_DIR / input_hash
if input_cache_path.exists():
input_media_type = detect_media_type(input_cache_path)
html_parts.append('
')
# Show output if completed
if run.status == "completed" and run.output_hash:
cache_path = CACHE_DIR / run.output_hash
if cache_path.exists():
media_type = detect_media_type(cache_path)
html_parts.append(f'
Output: {run.output_hash[:32]}...
')
html_parts.append('
')
# Show error if failed
if run.status == "failed" and run.error:
html_parts.append(f'
Error: {run.error}
')
html_parts.append('
')
html_parts.append('
')
return '\n'.join(html_parts)
@app.get("/ui/run/{run_id}", response_class=HTMLResponse)
async def ui_run_detail(run_id: str):
"""HTMX partial: single run (for polling updates)."""
run = load_run(run_id)
if not run:
return 'Run not found
'
# Check Celery task status if running
if run.status == "running" and run.celery_task_id:
task = celery_app.AsyncResult(run.celery_task_id)
if task.ready():
if task.successful():
result = task.result
run.status = "completed"
run.completed_at = datetime.now(timezone.utc).isoformat()
run.output_hash = result.get("output", {}).get("content_hash")
output_path = Path(result.get("output", {}).get("local_path", ""))
if output_path.exists():
cache_file(output_path)
else:
run.status = "failed"
run.error = str(task.result)
save_run(run)
status_class = run.status
poll_attr = 'hx-get="/ui/run/{}" hx-trigger="every 2s" hx-swap="outerHTML"'.format(run_id) if run.status == "running" else ""
html = f'''
Created: {run.created_at[:19].replace('T', ' ')}
'''
if run.inputs:
input_hash = run.inputs[0]
html += f'
Input: {input_hash[:32]}...
'
input_cache_path = CACHE_DIR / input_hash
if input_cache_path.exists():
input_media_type = detect_media_type(input_cache_path)
html += '
'
if run.status == "completed" and run.output_hash:
cache_path = CACHE_DIR / run.output_hash
if cache_path.exists():
media_type = detect_media_type(cache_path)
html += f'
Output: {run.output_hash[:32]}...
'
html += '
'
if run.status == "failed" and run.error:
html += f'
Error: {run.error}
'
html += '
'
return html
if __name__ == "__main__":
import uvicorn
uvicorn.run(app, host="0.0.0.0", port=8100)