Vixy
e4294b57e6
- 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>
73 lines
2.1 KiB
Python
Executable File
73 lines
2.1 KiB
Python
Executable File
"""
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DreamTail Configuration
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Configuration for SDXL image generation service running on AGX Orin.
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"""
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import os
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from pathlib import Path
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# Application settings
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APP_NAME = "DreamTail"
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APP_VERSION = "1.0.0"
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API_HOST = "0.0.0.0"
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API_PORT = 8765
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# Paths
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BASE_DIR = Path(__file__).parent
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STORAGE_DIR = Path(os.getenv("DREAMTAIL_STORAGE", "/app/storage"))
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MODELS_DIR = Path(os.getenv("DREAMTAIL_MODELS", "/app/models"))
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IMAGES_DIR = STORAGE_DIR / "images"
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# Ensure directories exist
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STORAGE_DIR.mkdir(parents=True, exist_ok=True)
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IMAGES_DIR.mkdir(parents=True, exist_ok=True)
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# Model settings
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SDXL_MODEL_ID = "SG161222/RealVisXL_V4.0"
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SDXL_REFINER_ID = "stabilityai/stable-diffusion-xl-refiner-1.0"
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USE_REFINER = False # Set to True to enable refiner (requires more VRAM)
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# IP-Adapter FaceID settings
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IP_ADAPTER_DIR = Path(os.getenv("DREAMTAIL_IP_ADAPTER", MODELS_DIR / "ip-adapter"))
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IP_ADAPTER_PATH = IP_ADAPTER_DIR / "ip-adapter-faceid_sdxl.bin"
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FACE_REFERENCE_DIR = STORAGE_DIR / "faces" # Directory for face reference images
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DEFAULT_FACE_STRENGTH = 0.6 # How strongly to apply face conditioning (0.0-1.0)
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# Ensure IP-Adapter directories exist
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IP_ADAPTER_DIR.mkdir(parents=True, exist_ok=True)
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FACE_REFERENCE_DIR.mkdir(parents=True, exist_ok=True)
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# Generation defaults
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DEFAULT_WIDTH = 1024
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DEFAULT_HEIGHT = 1024
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DEFAULT_STEPS = 30
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DEFAULT_GUIDANCE_SCALE = 7.5
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MIN_STEPS = 10
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MAX_STEPS = 100
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MIN_GUIDANCE = 1.0
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MAX_GUIDANCE = 20.0
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# Performance settings
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MAX_CONCURRENT_JOBS = 1 # AGX Orin can handle 1 SDXL generation at a time
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ENABLE_ATTENTION_SLICING = True
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ENABLE_VAE_SLICING = True
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ENABLE_CPU_OFFLOAD = False # Only if VRAM is insufficient
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USE_FP16 = True # Half precision for reduced VRAM usage
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# Queue settings
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MAX_QUEUE_SIZE = 50 # Maximum queued jobs
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JOB_TIMEOUT_SECONDS = 300 # 5 minutes max per job
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# Storage settings
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IMAGE_RETENTION_DAYS = 10
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CLEANUP_INTERVAL_HOURS = 24
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IMAGE_FORMAT = "PNG"
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IMAGE_QUALITY = 95 # For JPEG (not used for PNG)
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# Logging
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LOG_LEVEL = os.getenv("LOG_LEVEL", "INFO")
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LOG_FORMAT = "[%(asctime)s] %(levelname)s [%(name)s] %(message)s"
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LOG_DATE_FORMAT = "%H:%M:%S"
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