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:
2026-01-01 19:54:59 -06:00
commit e4294b57e6
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main.py Executable file
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"""
DreamTail - SDXL Image Generation Service
Main application entry point.
"""
import sys
import os
from pathlib import Path
# Add app directory to Python path
sys.path.insert(0, str(Path(__file__).parent))
import asyncio
import logging
import time
from contextlib import asynccontextmanager
from fastapi import FastAPI
from fastapi.middleware.cors import CORSMiddleware
import uvicorn
from api.routes import router
from worker.queue_manager import queue_manager
from worker.generator import generator
from dreamtail_storage.file_manager import file_manager
from dreamtail_storage.cleanup_task import cleanup_task
import config
# Configure logging
logging.basicConfig(
level=getattr(logging, config.LOG_LEVEL),
format=config.LOG_FORMAT,
datefmt=config.LOG_DATE_FORMAT
)
logger = logging.getLogger(__name__)
# Track application start time
start_time = time.time()
async def process_jobs():
"""
Background worker that processes jobs from the queue.
"""
logger.info("Job processor started")
while True:
try:
# Get next job from queue (blocks until available)
job_id = await queue_manager.get_next_job()
if not job_id:
continue
job = queue_manager.get_job(job_id)
if not job:
logger.warning(f"Job {job_id} not found in queue")
continue
# Mark job as started
await queue_manager.start_job(job_id)
logger.info(f"Processing job {job_id}")
try:
# Progress callback
async def update_progress(progress: int):
await queue_manager.update_progress(job_id, progress)
# Resolve face image path if specified
face_image = job.params.get("face_image")
if face_image:
# Handle "vixy" shortcut for default face
if face_image.lower() == "vixy":
# Use all faces in the vixy directory
vixy_faces = list(config.FACE_REFERENCE_DIR.glob("*.jpg")) + \
list(config.FACE_REFERENCE_DIR.glob("*.png"))
if vixy_faces:
face_image = [str(f) for f in vixy_faces]
logger.info(f"Using {len(face_image)} Vixy reference faces")
else:
logger.warning("No Vixy faces found, generating without face lock")
face_image = None
else:
# Look for specific face file
face_path = config.FACE_REFERENCE_DIR / face_image
if face_path.exists():
face_image = str(face_path)
else:
logger.warning(f"Face image {face_image} not found, generating without face lock")
face_image = None
# Generate image
image = await generator.generate_image(
prompt=job.prompt,
negative_prompt=job.negative_prompt,
width=job.params.get("width", config.DEFAULT_WIDTH),
height=job.params.get("height", config.DEFAULT_HEIGHT),
num_inference_steps=job.params.get("num_inference_steps", config.DEFAULT_STEPS),
guidance_scale=job.params.get("guidance_scale", config.DEFAULT_GUIDANCE_SCALE),
seed=job.params.get("seed"),
progress_callback=update_progress,
face_image=face_image,
face_strength=job.params.get("face_strength", config.DEFAULT_FACE_STRENGTH),
)
# Save image to disk
result_path = await file_manager.save_image(job_id, image)
# Mark job as completed
await queue_manager.complete_job(job_id, result_path)
logger.info(f"Job {job_id} completed successfully")
except Exception as e:
logger.error(f"Job {job_id} failed: {e}")
await queue_manager.fail_job(job_id, str(e))
except asyncio.CancelledError:
logger.info("Job processor cancelled")
break
except Exception as e:
logger.error(f"Error in job processor: {e}")
await asyncio.sleep(5) # Wait before retrying
@asynccontextmanager
async def lifespan(app: FastAPI):
"""
Lifespan context manager for startup and shutdown.
"""
# Startup
logger.info(f"🎨 Starting {config.APP_NAME} v{config.APP_VERSION}")
logger.info(f"Storage: {config.STORAGE_DIR}")
logger.info(f"Models: {config.MODELS_DIR}")
# Initialize SDXL model
try:
await generator.initialize()
except Exception as e:
logger.error(f"Failed to initialize SDXL model: {e}")
logger.warning("Service will start but generation will fail until model is loaded")
# Start background tasks
worker_task = asyncio.create_task(process_jobs())
await cleanup_task.start()
logger.info(f"{config.APP_NAME} ready on http://{config.API_HOST}:{config.API_PORT}")
yield
# Shutdown
logger.info(f"🛑 Shutting down {config.APP_NAME}...")
# Cancel worker task
worker_task.cancel()
try:
await worker_task
except asyncio.CancelledError:
pass
# Stop cleanup task
await cleanup_task.stop()
logger.info("✅ Shutdown complete")
# Create FastAPI application
app = FastAPI(
title=config.APP_NAME,
version=config.APP_VERSION,
description="SDXL Image Generation Service for Jetson AGX Orin",
lifespan=lifespan
)
# Add CORS middleware (allow all origins for multi-client support)
app.add_middleware(
CORSMiddleware,
allow_origins=["*"],
allow_credentials=True,
allow_methods=["*"],
allow_headers=["*"],
)
# Include API routes
app.include_router(router)
@app.get("/")
async def root():
"""Root endpoint with service information."""
return {
"service": config.APP_NAME,
"version": config.APP_VERSION,
"status": "running",
"model": config.SDXL_MODEL_ID,
"endpoints": {
"generate": "POST /generate",
"status": "GET /status/{job_id}",
"result": "GET /result/{job_id}",
"health": "GET /health",
"models": "GET /models"
}
}
if __name__ == "__main__":
# Run with uvicorn
uvicorn.run(
"main:app",
host=config.API_HOST,
port=config.API_PORT,
log_level=config.LOG_LEVEL.lower()
)