Files
celery/server.py
gilesb ba20c2dc63 feat: L1 server with persistent run storage
- 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>
2026-01-07 10:45:30 +00:00

231 lines
6.0 KiB
Python

#!/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
from fastapi.responses import FileResponse
from pydantic import BaseModel
import redis
from celery_app import app as celery_app
from tasks import render_effect
# Cache directory
CACHE_DIR = Path.home() / ".artdag" / "cache"
CACHE_DIR.mkdir(parents=True, exist_ok=True)
# Redis for persistent run storage
redis_client = redis.Redis(host='localhost', port=6379, db=5)
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("/")
async def root():
"""Server info."""
return {
"name": "Art DAG L1 Server",
"version": "0.1.0",
"cache_dir": str(CACHE_DIR),
"runs_count": len(list_all_runs())
}
@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}
if __name__ == "__main__":
import uvicorn
uvicorn.run(app, host="0.0.0.0", port=8100)