Base code
This commit is contained in:
Kunthawat Greethong
656
backend/config/stability_config.py
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656
backend/config/stability_config.py
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"""Configuration settings for Stability AI integration."""
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import os
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from typing import Dict, Any, List, Optional
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from dataclasses import dataclass
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from enum import Enum
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class StabilityEndpoint(Enum):
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"""Stability AI API endpoints."""
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# Generate endpoints
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GENERATE_ULTRA = "/v2beta/stable-image/generate/ultra"
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GENERATE_CORE = "/v2beta/stable-image/generate/core"
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GENERATE_SD3 = "/v2beta/stable-image/generate/sd3"
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# Edit endpoints
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EDIT_ERASE = "/v2beta/stable-image/edit/erase"
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EDIT_INPAINT = "/v2beta/stable-image/edit/inpaint"
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EDIT_OUTPAINT = "/v2beta/stable-image/edit/outpaint"
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EDIT_SEARCH_REPLACE = "/v2beta/stable-image/edit/search-and-replace"
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EDIT_SEARCH_RECOLOR = "/v2beta/stable-image/edit/search-and-recolor"
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EDIT_REMOVE_BACKGROUND = "/v2beta/stable-image/edit/remove-background"
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EDIT_REPLACE_BACKGROUND = "/v2beta/stable-image/edit/replace-background-and-relight"
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# Upscale endpoints
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UPSCALE_FAST = "/v2beta/stable-image/upscale/fast"
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UPSCALE_CONSERVATIVE = "/v2beta/stable-image/upscale/conservative"
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UPSCALE_CREATIVE = "/v2beta/stable-image/upscale/creative"
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# Control endpoints
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CONTROL_SKETCH = "/v2beta/stable-image/control/sketch"
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CONTROL_STRUCTURE = "/v2beta/stable-image/control/structure"
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CONTROL_STYLE = "/v2beta/stable-image/control/style"
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CONTROL_STYLE_TRANSFER = "/v2beta/stable-image/control/style-transfer"
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# 3D endpoints
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STABLE_FAST_3D = "/v2beta/3d/stable-fast-3d"
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STABLE_POINT_AWARE_3D = "/v2beta/3d/stable-point-aware-3d"
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# Audio endpoints
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AUDIO_TEXT_TO_AUDIO = "/v2beta/audio/stable-audio-2/text-to-audio"
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AUDIO_AUDIO_TO_AUDIO = "/v2beta/audio/stable-audio-2/audio-to-audio"
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AUDIO_INPAINT = "/v2beta/audio/stable-audio-2/inpaint"
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# Results endpoint
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RESULTS = "/v2beta/results/{id}"
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# Legacy V1 endpoints
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V1_TEXT_TO_IMAGE = "/v1/generation/{engine_id}/text-to-image"
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V1_IMAGE_TO_IMAGE = "/v1/generation/{engine_id}/image-to-image"
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V1_MASKING = "/v1/generation/{engine_id}/image-to-image/masking"
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# User endpoints
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USER_ACCOUNT = "/v1/user/account"
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USER_BALANCE = "/v1/user/balance"
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ENGINES_LIST = "/v1/engines/list"
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@dataclass
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class StabilityConfig:
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"""Configuration for Stability AI service."""
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api_key: str
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base_url: str = "https://api.stability.ai"
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timeout: int = 300
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max_retries: int = 3
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rate_limit_requests: int = 150
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rate_limit_window: int = 10 # seconds
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max_file_size: int = 10 * 1024 * 1024 # 10MB
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supported_image_formats: List[str] = None
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supported_audio_formats: List[str] = None
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def __post_init__(self):
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if self.supported_image_formats is None:
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self.supported_image_formats = ["jpeg", "jpg", "png", "webp"]
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if self.supported_audio_formats is None:
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self.supported_audio_formats = ["mp3", "wav"]
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# Model pricing information
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MODEL_PRICING = {
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"generate": {
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"ultra": 8,
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"core": 3,
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"sd3.5-large": 6.5,
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"sd3.5-large-turbo": 4,
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"sd3.5-medium": 3.5,
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"sd3.5-flash": 2.5
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},
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"edit": {
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"erase": 5,
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"inpaint": 5,
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"outpaint": 4,
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"search_and_replace": 5,
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"search_and_recolor": 5,
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"remove_background": 5,
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"replace_background_and_relight": 8
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},
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"upscale": {
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"fast": 2,
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"conservative": 40,
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"creative": 60
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},
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"control": {
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"sketch": 5,
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"structure": 5,
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"style": 5,
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"style_transfer": 8
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},
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"3d": {
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"stable_fast_3d": 10,
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"stable_point_aware_3d": 4
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},
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"audio": {
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"text_to_audio": 20,
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"audio_to_audio": 20,
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"inpaint": 20
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}
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}
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# Image dimension limits
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IMAGE_LIMITS = {
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"generate": {
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"min_pixels": 4096,
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"max_pixels": 16777216, # 16MP
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"min_dimension": 64,
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"max_dimension": 16384
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},
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"edit": {
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"min_pixels": 4096,
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"max_pixels": 9437184, # ~9.4MP
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"min_dimension": 64,
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"aspect_ratio_min": 0.4, # 1:2.5
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"aspect_ratio_max": 2.5 # 2.5:1
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},
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"upscale": {
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"fast": {
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"min_width": 32,
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"max_width": 1536,
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"min_height": 32,
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"max_height": 1536,
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"min_pixels": 1024,
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"max_pixels": 1048576
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},
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"conservative": {
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"min_pixels": 4096,
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"max_pixels": 9437184,
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"min_dimension": 64
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},
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"creative": {
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"min_pixels": 4096,
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"max_pixels": 1048576,
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"min_dimension": 64
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}
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},
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"control": {
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"min_pixels": 4096,
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"max_pixels": 9437184,
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"min_dimension": 64,
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"aspect_ratio_min": 0.4,
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"aspect_ratio_max": 2.5
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},
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"3d": {
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"min_pixels": 4096,
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"max_pixels": 4194304, # 4MP
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"min_dimension": 64
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}
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}
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# Audio limits
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AUDIO_LIMITS = {
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"min_duration": 6,
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"max_duration": 190,
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"max_file_size": 50 * 1024 * 1024, # 50MB
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"supported_formats": ["mp3", "wav"]
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}
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# Style preset descriptions
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STYLE_PRESET_DESCRIPTIONS = {
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"enhance": "Enhance the natural qualities of the image",
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"anime": "Japanese animation style",
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"photographic": "Realistic photographic style",
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"digital-art": "Digital artwork style",
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"comic-book": "Comic book illustration style",
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"fantasy-art": "Fantasy and magical themes",
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"line-art": "Clean line art style",
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"analog-film": "Vintage film photography style",
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"neon-punk": "Cyberpunk with neon lighting",
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"isometric": "Isometric 3D perspective",
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"low-poly": "Low polygon 3D style",
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"origami": "Paper folding art style",
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"modeling-compound": "Clay or modeling compound style",
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"cinematic": "Movie-like cinematic style",
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"3d-model": "3D rendered model style",
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"pixel-art": "Retro pixel art style",
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"tile-texture": "Seamless tile texture style"
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}
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# Default parameters for different operations
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DEFAULT_PARAMETERS = {
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"generate": {
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"ultra": {
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"aspect_ratio": "1:1",
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"output_format": "png"
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},
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"core": {
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"aspect_ratio": "1:1",
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"output_format": "png"
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},
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"sd3": {
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"model": "sd3.5-large",
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"mode": "text-to-image",
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"aspect_ratio": "1:1",
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"output_format": "png"
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}
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},
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"edit": {
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"erase": {
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"grow_mask": 5,
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"output_format": "png"
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},
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"inpaint": {
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"grow_mask": 5,
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"output_format": "png"
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},
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"outpaint": {
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"creativity": 0.5,
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"output_format": "png"
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}
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},
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"upscale": {
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"fast": {
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"output_format": "png"
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},
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"conservative": {
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"creativity": 0.35,
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"output_format": "png"
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},
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"creative": {
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"creativity": 0.3,
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"output_format": "png"
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}
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},
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"control": {
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"sketch": {
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"control_strength": 0.7,
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"output_format": "png"
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},
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"structure": {
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"control_strength": 0.7,
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"output_format": "png"
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},
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"style": {
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"aspect_ratio": "1:1",
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"fidelity": 0.5,
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"output_format": "png"
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}
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},
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"3d": {
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"stable_fast_3d": {
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"texture_resolution": "1024",
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"foreground_ratio": 0.85,
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"remesh": "none",
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"vertex_count": -1
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},
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"stable_point_aware_3d": {
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"texture_resolution": "1024",
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"foreground_ratio": 1.3,
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"remesh": "none",
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"target_type": "none",
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"target_count": 1000,
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"guidance_scale": 3
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}
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},
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"audio": {
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"text_to_audio": {
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"duration": 190,
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"model": "stable-audio-2",
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"output_format": "mp3"
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},
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"audio_to_audio": {
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"duration": 190,
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"model": "stable-audio-2",
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"output_format": "mp3",
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"strength": 1
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},
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"inpaint": {
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"duration": 190,
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"steps": 8,
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"output_format": "mp3",
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"mask_start": 30,
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"mask_end": 190
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}
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}
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}
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# Rate limiting configuration
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RATE_LIMIT_CONFIG = {
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"requests_per_window": 150,
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"window_seconds": 10,
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"timeout_seconds": 60,
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"burst_allowance": 10 # Allow brief bursts above limit
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}
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# Content moderation settings
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CONTENT_MODERATION = {
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"enabled": True,
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"blocked_keywords": [
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# This would contain actual blocked keywords in production
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],
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"warning_keywords": [
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# Keywords that trigger warnings but don't block
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]
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}
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# Quality settings for different use cases
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QUALITY_PRESETS = {
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"draft": {
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"model": "core",
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"steps": None, # Use model defaults
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"cfg_scale": None,
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"description": "Fast generation for drafts and iterations"
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},
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"standard": {
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"model": "sd3.5-medium",
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"steps": None,
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"cfg_scale": 4,
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"description": "Balanced quality and speed"
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},
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"premium": {
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"model": "ultra",
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"steps": None,
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"cfg_scale": None,
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"description": "Highest quality for final outputs"
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},
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"professional": {
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"model": "sd3.5-large",
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"steps": None,
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"cfg_scale": 4,
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"style_preset": "photographic",
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"description": "Professional photography style"
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}
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}
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# Workflow templates
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WORKFLOW_TEMPLATES = {
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"portrait_enhancement": {
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"description": "Enhance portrait photos with professional quality",
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"steps": [
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{"operation": "upscale_conservative", "params": {"creativity": 0.2}},
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{"operation": "inpaint", "params": {"prompt": "professional portrait, high quality"}}
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]
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},
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"art_creation": {
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"description": "Create artistic images from sketches",
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"steps": [
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{"operation": "control_sketch", "params": {"control_strength": 0.8}},
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{"operation": "upscale_fast", "params": {}}
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]
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},
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"product_photography": {
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"description": "Create professional product images",
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"steps": [
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{"operation": "remove_background", "params": {}},
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{"operation": "replace_background_and_relight", "params": {"background_prompt": "professional studio lighting, white background"}}
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]
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},
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"creative_exploration": {
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"description": "Explore different creative interpretations",
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"steps": [
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{"operation": "generate_core", "params": {}},
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{"operation": "control_style", "params": {"fidelity": 0.7}},
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{"operation": "upscale_creative", "params": {"creativity": 0.4}}
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]
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}
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}
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def get_stability_config() -> StabilityConfig:
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"""Get Stability AI configuration from environment variables.
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Returns:
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StabilityConfig instance
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"""
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api_key = os.getenv("STABILITY_API_KEY")
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if not api_key:
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raise ValueError("STABILITY_API_KEY environment variable is required")
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return StabilityConfig(
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api_key=api_key,
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base_url=os.getenv("STABILITY_BASE_URL", "https://api.stability.ai"),
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timeout=int(os.getenv("STABILITY_TIMEOUT", "300")),
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max_retries=int(os.getenv("STABILITY_MAX_RETRIES", "3")),
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max_file_size=int(os.getenv("STABILITY_MAX_FILE_SIZE", str(10 * 1024 * 1024)))
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)
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def validate_image_requirements(
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width: int,
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height: int,
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operation: str
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) -> Dict[str, Any]:
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"""Validate image requirements for specific operations.
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Args:
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width: Image width
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height: Image height
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operation: Operation type (generate, edit, upscale, etc.)
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Returns:
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Validation result with success status and any issues
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"""
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issues = []
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limits = IMAGE_LIMITS.get(operation, IMAGE_LIMITS["generate"])
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total_pixels = width * height
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# Check minimum requirements
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if "min_pixels" in limits and total_pixels < limits["min_pixels"]:
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issues.append(f"Image must have at least {limits['min_pixels']} pixels")
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if "max_pixels" in limits and total_pixels > limits["max_pixels"]:
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issues.append(f"Image must have at most {limits['max_pixels']} pixels")
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if "min_dimension" in limits:
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if width < limits["min_dimension"] or height < limits["min_dimension"]:
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issues.append(f"Both dimensions must be at least {limits['min_dimension']} pixels")
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# Check aspect ratio for operations that require it
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if "aspect_ratio_min" in limits and "aspect_ratio_max" in limits:
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aspect_ratio = width / height
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if aspect_ratio < limits["aspect_ratio_min"] or aspect_ratio > limits["aspect_ratio_max"]:
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issues.append(f"Aspect ratio must be between {limits['aspect_ratio_min']}:1 and {limits['aspect_ratio_max']}:1")
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return {
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"is_valid": len(issues) == 0,
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"issues": issues,
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"total_pixels": total_pixels,
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"aspect_ratio": round(width / height, 3)
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}
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def get_model_recommendations(
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use_case: str,
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quality_preference: str = "standard",
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speed_preference: str = "balanced"
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) -> Dict[str, Any]:
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"""Get model recommendations based on use case and preferences.
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Args:
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use_case: Type of use case (portrait, landscape, art, product, etc.)
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quality_preference: Quality preference (draft, standard, premium)
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speed_preference: Speed preference (fast, balanced, quality)
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Returns:
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Model recommendations with explanations
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"""
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recommendations = {}
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# Base recommendations by use case
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if use_case == "portrait":
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recommendations["primary"] = "ultra"
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recommendations["alternative"] = "sd3.5-large"
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recommendations["style_preset"] = "photographic"
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elif use_case == "art":
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recommendations["primary"] = "sd3.5-large"
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recommendations["alternative"] = "ultra"
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recommendations["style_preset"] = "digital-art"
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elif use_case == "product":
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recommendations["primary"] = "ultra"
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recommendations["alternative"] = "sd3.5-large"
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recommendations["style_preset"] = "photographic"
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elif use_case == "concept":
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recommendations["primary"] = "core"
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recommendations["alternative"] = "sd3.5-medium"
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recommendations["style_preset"] = "enhance"
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else:
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recommendations["primary"] = "core"
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recommendations["alternative"] = "sd3.5-medium"
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# Adjust based on preferences
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if speed_preference == "fast":
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if recommendations["primary"] == "ultra":
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recommendations["primary"] = "core"
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elif recommendations["primary"] == "sd3.5-large":
|
||||
recommendations["primary"] = "sd3.5-medium"
|
||||
elif speed_preference == "quality":
|
||||
if recommendations["primary"] == "core":
|
||||
recommendations["primary"] = "ultra"
|
||||
elif recommendations["primary"] == "sd3.5-medium":
|
||||
recommendations["primary"] = "sd3.5-large"
|
||||
|
||||
# Add quality preset
|
||||
if quality_preference in QUALITY_PRESETS:
|
||||
recommendations.update(QUALITY_PRESETS[quality_preference])
|
||||
|
||||
return recommendations
|
||||
|
||||
|
||||
def get_optimal_parameters(
|
||||
operation: str,
|
||||
image_info: Optional[Dict[str, Any]] = None,
|
||||
user_preferences: Optional[Dict[str, Any]] = None
|
||||
) -> Dict[str, Any]:
|
||||
"""Get optimal parameters for a specific operation.
|
||||
|
||||
Args:
|
||||
operation: Operation type
|
||||
image_info: Information about input image
|
||||
user_preferences: User preferences
|
||||
|
||||
Returns:
|
||||
Optimal parameters for the operation
|
||||
"""
|
||||
# Start with defaults
|
||||
params = DEFAULT_PARAMETERS.get(operation, {}).copy()
|
||||
|
||||
# Adjust based on image characteristics
|
||||
if image_info:
|
||||
total_pixels = image_info.get("total_pixels", 0)
|
||||
|
||||
# Adjust creativity based on image quality
|
||||
if "creativity" in params:
|
||||
if total_pixels < 100000: # Very low res
|
||||
params["creativity"] = min(params["creativity"] + 0.1, 0.5)
|
||||
elif total_pixels > 2000000: # High res
|
||||
params["creativity"] = max(params["creativity"] - 0.1, 0.1)
|
||||
|
||||
# Apply user preferences
|
||||
if user_preferences:
|
||||
for key, value in user_preferences.items():
|
||||
if key in params:
|
||||
params[key] = value
|
||||
|
||||
return params
|
||||
|
||||
|
||||
def calculate_estimated_cost(
|
||||
operation: str,
|
||||
model: Optional[str] = None,
|
||||
steps: Optional[int] = None
|
||||
) -> float:
|
||||
"""Calculate estimated cost in credits for an operation.
|
||||
|
||||
Args:
|
||||
operation: Operation type
|
||||
model: Model name (if applicable)
|
||||
steps: Number of steps (for step-based pricing)
|
||||
|
||||
Returns:
|
||||
Estimated cost in credits
|
||||
"""
|
||||
if operation in MODEL_PRICING:
|
||||
if isinstance(MODEL_PRICING[operation], dict):
|
||||
if model and model in MODEL_PRICING[operation]:
|
||||
base_cost = MODEL_PRICING[operation][model]
|
||||
else:
|
||||
# Use default model cost
|
||||
base_cost = list(MODEL_PRICING[operation].values())[0]
|
||||
else:
|
||||
base_cost = MODEL_PRICING[operation]
|
||||
else:
|
||||
base_cost = 5 # Default cost
|
||||
|
||||
# Adjust for steps if applicable (mainly for audio)
|
||||
if steps and operation.startswith("audio") and model == "stable-audio-2":
|
||||
# Audio 2.0 uses formula: 17 + 0.06 * steps
|
||||
return 17 + 0.06 * steps
|
||||
|
||||
return base_cost
|
||||
|
||||
|
||||
def get_operation_limits(operation: str) -> Dict[str, Any]:
|
||||
"""Get limits and constraints for a specific operation.
|
||||
|
||||
Args:
|
||||
operation: Operation type
|
||||
|
||||
Returns:
|
||||
Limits and constraints
|
||||
"""
|
||||
limits = {
|
||||
"file_size_limit": 10 * 1024 * 1024, # 10MB default
|
||||
"timeout": 300,
|
||||
"rate_limit": True
|
||||
}
|
||||
|
||||
# Add operation-specific limits
|
||||
if operation in IMAGE_LIMITS:
|
||||
limits.update(IMAGE_LIMITS[operation])
|
||||
|
||||
if operation.startswith("audio"):
|
||||
limits.update(AUDIO_LIMITS)
|
||||
limits["file_size_limit"] = 50 * 1024 * 1024 # 50MB for audio
|
||||
|
||||
if operation.startswith("3d"):
|
||||
limits["file_size_limit"] = 10 * 1024 * 1024 # 10MB for 3D
|
||||
|
||||
return limits
|
||||
|
||||
|
||||
# Environment-specific configurations
|
||||
def get_environment_config() -> Dict[str, Any]:
|
||||
"""Get environment-specific configuration.
|
||||
|
||||
Returns:
|
||||
Environment configuration
|
||||
"""
|
||||
env = os.getenv("ENVIRONMENT", "development")
|
||||
|
||||
configs = {
|
||||
"development": {
|
||||
"debug_mode": True,
|
||||
"log_level": "DEBUG",
|
||||
"cache_results": False,
|
||||
"mock_responses": False
|
||||
},
|
||||
"staging": {
|
||||
"debug_mode": True,
|
||||
"log_level": "INFO",
|
||||
"cache_results": True,
|
||||
"mock_responses": False
|
||||
},
|
||||
"production": {
|
||||
"debug_mode": False,
|
||||
"log_level": "WARNING",
|
||||
"cache_results": True,
|
||||
"mock_responses": False
|
||||
}
|
||||
}
|
||||
|
||||
return configs.get(env, configs["development"])
|
||||
|
||||
|
||||
# Feature flags
|
||||
FEATURE_FLAGS = {
|
||||
"enable_batch_processing": True,
|
||||
"enable_webhooks": True,
|
||||
"enable_caching": True,
|
||||
"enable_analytics": True,
|
||||
"enable_experimental_endpoints": True,
|
||||
"enable_quality_analysis": True,
|
||||
"enable_prompt_optimization": True,
|
||||
"enable_workflow_templates": True
|
||||
}
|
||||
|
||||
|
||||
def is_feature_enabled(feature: str) -> bool:
|
||||
"""Check if a feature is enabled.
|
||||
|
||||
Args:
|
||||
feature: Feature name
|
||||
|
||||
Returns:
|
||||
True if feature is enabled
|
||||
"""
|
||||
return FEATURE_FLAGS.get(feature, False)
|
||||
Reference in New Issue
Block a user