DreamTail v1.0.0 with IP-Adapter FaceID support
- SDXL image generation using RealVisXL_V4.0 - IP-Adapter FaceID integration for consistent face generation - Simplified API (removed client_id requirement) - New params: face_image, face_strength - 'vixy' shortcut for face-locked generation - Queue-based async job processing - FastAPI with proper error handling Co-authored-by: Alex <alex@k4zka.online>
This commit is contained in:
216
main.py
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216
main.py
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"""
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DreamTail - SDXL Image Generation Service
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Main application entry point.
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"""
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import sys
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import os
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from pathlib import Path
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# Add app directory to Python path
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sys.path.insert(0, str(Path(__file__).parent))
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import asyncio
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import logging
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import time
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from contextlib import asynccontextmanager
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from fastapi import FastAPI
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from fastapi.middleware.cors import CORSMiddleware
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import uvicorn
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from api.routes import router
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from worker.queue_manager import queue_manager
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from worker.generator import generator
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from dreamtail_storage.file_manager import file_manager
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from dreamtail_storage.cleanup_task import cleanup_task
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import config
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# Configure logging
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logging.basicConfig(
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level=getattr(logging, config.LOG_LEVEL),
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format=config.LOG_FORMAT,
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datefmt=config.LOG_DATE_FORMAT
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)
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logger = logging.getLogger(__name__)
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# Track application start time
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start_time = time.time()
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async def process_jobs():
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"""
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Background worker that processes jobs from the queue.
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"""
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logger.info("Job processor started")
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while True:
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try:
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# Get next job from queue (blocks until available)
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job_id = await queue_manager.get_next_job()
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if not job_id:
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continue
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job = queue_manager.get_job(job_id)
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if not job:
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logger.warning(f"Job {job_id} not found in queue")
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continue
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# Mark job as started
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await queue_manager.start_job(job_id)
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logger.info(f"Processing job {job_id}")
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try:
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# Progress callback
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async def update_progress(progress: int):
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await queue_manager.update_progress(job_id, progress)
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# Resolve face image path if specified
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face_image = job.params.get("face_image")
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if face_image:
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# Handle "vixy" shortcut for default face
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if face_image.lower() == "vixy":
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# Use all faces in the vixy directory
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vixy_faces = list(config.FACE_REFERENCE_DIR.glob("*.jpg")) + \
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list(config.FACE_REFERENCE_DIR.glob("*.png"))
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if vixy_faces:
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face_image = [str(f) for f in vixy_faces]
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logger.info(f"Using {len(face_image)} Vixy reference faces")
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else:
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logger.warning("No Vixy faces found, generating without face lock")
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face_image = None
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else:
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# Look for specific face file
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face_path = config.FACE_REFERENCE_DIR / face_image
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if face_path.exists():
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face_image = str(face_path)
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else:
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logger.warning(f"Face image {face_image} not found, generating without face lock")
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face_image = None
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# Generate image
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image = await generator.generate_image(
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prompt=job.prompt,
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negative_prompt=job.negative_prompt,
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width=job.params.get("width", config.DEFAULT_WIDTH),
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height=job.params.get("height", config.DEFAULT_HEIGHT),
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num_inference_steps=job.params.get("num_inference_steps", config.DEFAULT_STEPS),
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guidance_scale=job.params.get("guidance_scale", config.DEFAULT_GUIDANCE_SCALE),
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seed=job.params.get("seed"),
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progress_callback=update_progress,
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face_image=face_image,
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face_strength=job.params.get("face_strength", config.DEFAULT_FACE_STRENGTH),
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)
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# Save image to disk
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result_path = await file_manager.save_image(job_id, image)
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# Mark job as completed
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await queue_manager.complete_job(job_id, result_path)
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logger.info(f"Job {job_id} completed successfully")
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except Exception as e:
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logger.error(f"Job {job_id} failed: {e}")
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await queue_manager.fail_job(job_id, str(e))
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except asyncio.CancelledError:
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logger.info("Job processor cancelled")
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break
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except Exception as e:
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logger.error(f"Error in job processor: {e}")
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await asyncio.sleep(5) # Wait before retrying
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@asynccontextmanager
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async def lifespan(app: FastAPI):
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"""
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Lifespan context manager for startup and shutdown.
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"""
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# Startup
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logger.info(f"🎨 Starting {config.APP_NAME} v{config.APP_VERSION}")
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logger.info(f"Storage: {config.STORAGE_DIR}")
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logger.info(f"Models: {config.MODELS_DIR}")
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# Initialize SDXL model
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try:
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await generator.initialize()
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except Exception as e:
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logger.error(f"Failed to initialize SDXL model: {e}")
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logger.warning("Service will start but generation will fail until model is loaded")
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# Start background tasks
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worker_task = asyncio.create_task(process_jobs())
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await cleanup_task.start()
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logger.info(f"✅ {config.APP_NAME} ready on http://{config.API_HOST}:{config.API_PORT}")
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yield
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# Shutdown
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logger.info(f"🛑 Shutting down {config.APP_NAME}...")
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# Cancel worker task
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worker_task.cancel()
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try:
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await worker_task
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except asyncio.CancelledError:
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pass
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# Stop cleanup task
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await cleanup_task.stop()
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logger.info("✅ Shutdown complete")
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# Create FastAPI application
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app = FastAPI(
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title=config.APP_NAME,
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version=config.APP_VERSION,
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description="SDXL Image Generation Service for Jetson AGX Orin",
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lifespan=lifespan
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)
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# Add CORS middleware (allow all origins for multi-client support)
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app.add_middleware(
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CORSMiddleware,
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allow_origins=["*"],
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allow_credentials=True,
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allow_methods=["*"],
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allow_headers=["*"],
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)
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# Include API routes
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app.include_router(router)
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@app.get("/")
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async def root():
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"""Root endpoint with service information."""
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return {
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"service": config.APP_NAME,
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"version": config.APP_VERSION,
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"status": "running",
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"model": config.SDXL_MODEL_ID,
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"endpoints": {
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"generate": "POST /generate",
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"status": "GET /status/{job_id}",
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"result": "GET /result/{job_id}",
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"health": "GET /health",
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"models": "GET /models"
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}
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}
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if __name__ == "__main__":
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# Run with uvicorn
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uvicorn.run(
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"main:app",
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host=config.API_HOST,
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port=config.API_PORT,
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log_level=config.LOG_LEVEL.lower()
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)
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