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image s imsages images model fixes new model see dream

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IGNY8 VPS (Salman)
2026-01-10 13:16:05 +00:00
parent 6fb0411f56
commit 854b3efd45
9 changed files with 582 additions and 66 deletions
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15
backend/igny8_core/ai/ai_core.py
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@@ -1028,9 +1028,18 @@ class AICore:
print(f"[AI][{function_name}] Using Nano Banana config: resolution=1k (no width/height)")
elif runware_model.startswith('bytedance:'):
# Seedream 4.5 (bytedance:seedream@4.5) - High quality ByteDance model
# Uses basic format with just width/height - no steps, CFGScale, or special providerSettings needed
# Just use the base inference_task as-is
print(f"[AI][{function_name}] Using Seedream 4.5 config: basic format, width={width}, height={height}")
# Uses basic format - no steps, CFGScale, negativePrompt, or special providerSettings needed
# Remove negativePrompt as it's not supported
if 'negativePrompt' in inference_task:
del inference_task['negativePrompt']
# Enforce minimum size for Seedream (min 3,686,400 pixels ~ 1920x1920)
current_pixels = width * height
if current_pixels < 3686400:
# Use default Seedream square size
inference_task['width'] = 2048
inference_task['height'] = 2048
width, height = 2048, 2048
print(f"[AI][{function_name}] Using Seedream 4.5 config: basic format (no negativePrompt), width={inference_task['width']}, height={inference_task['height']}")
elif runware_model.startswith('runware:'):
# Hi Dream Full (runware:97@1) - General diffusion, steps 20, CFGScale 7
inference_task['steps'] = 20

62
backend/igny8_core/ai/tasks.py
View File

@@ -187,22 +187,42 @@ def process_image_generation_queue(self, image_ids: list, account_id: int = None
logger.info("[process_image_generation_queue] Step 1: Loading image generation settings")
from igny8_core.modules.system.ai_settings import AISettings
from igny8_core.ai.model_registry import ModelRegistry
from igny8_core.business.billing.models import AIModelConfig
# Get effective settings
image_type = AISettings.get_effective_image_style(account)
image_format = 'webp' # Default format
# Get default image model from database
default_model = ModelRegistry.get_default_model('image')
if default_model:
model_config = ModelRegistry.get_model(default_model)
provider = model_config.provider if model_config else 'openai'
model = default_model
# Get user's selected quality tier (from account settings)
quality_tier = AISettings.get_effective_quality_tier(account)
logger.info(f"[process_image_generation_queue] User's quality tier: {quality_tier}")
# Find image model based on quality tier (DYNAMIC from database)
model_config = None
if quality_tier:
model_config = AIModelConfig.objects.filter(
model_type='image',
quality_tier=quality_tier,
is_active=True
).first()
# Fallback to default image model if no tier match
if not model_config:
default_model = ModelRegistry.get_default_model('image')
if default_model:
model_config = ModelRegistry.get_model(default_model)
# Set provider and model from database config
if model_config:
provider = model_config.provider or 'openai'
model = model_config.model_name
else:
# Ultimate fallback (should never happen if database is configured)
logger.warning("[process_image_generation_queue] No image model found in database, using fallback")
provider = 'openai'
model = 'dall-e-3'
logger.info(f"[process_image_generation_queue] Using PROVIDER: {provider}, MODEL: {model} from settings")
logger.info(f"[process_image_generation_queue] Using PROVIDER: {provider}, MODEL: {model} from AIModelConfig")
# Style to prompt enhancement mapping
# These style descriptors are added to the image prompt for better results
@@ -225,25 +245,23 @@ def process_image_generation_queue(self, image_ids: list, account_id: int = None
style_description = STYLE_PROMPT_MAP.get(image_type, STYLE_PROMPT_MAP.get('photorealistic'))
logger.info(f"[process_image_generation_queue] Style: {image_type} -> prompt enhancement: {style_description[:50]}...")
# Model-specific landscape sizes (square is always 1024x1024)
# For Runware models - based on Runware documentation for optimal results per model
# For OpenAI DALL-E 3 - uses 1792x1024 for landscape
MODEL_LANDSCAPE_SIZES = {
'runware:97@1': '1280x768', # Hi Dream Full landscape
'bria:10@1': '1344x768', # Bria 3.2 landscape (16:9)
'google:4@2': '1376x768', # Nano Banana landscape (16:9)
'dall-e-3': '1792x1024', # DALL-E 3 landscape
'dall-e-2': '1024x1024', # DALL-E 2 only supports square
}
DEFAULT_SQUARE_SIZE = '1024x1024'
# Get model-specific landscape size for featured images
model_landscape_size = MODEL_LANDSCAPE_SIZES.get(model, '1792x1024' if provider == 'openai' else '1280x768')
# Load image sizes from AIModelConfig (DYNAMIC from database)
# model_config was loaded above based on quality tier
if model_config:
# Get sizes from database (single source of truth)
model_landscape_size = model_config.landscape_size or '1792x1024'
model_square_size = model_config.square_size or '1024x1024'
logger.info(f"[process_image_generation_queue] Loaded sizes from AIModelConfig: landscape={model_landscape_size}, square={model_square_size}")
else:
# Fallback sizes if no model config (should never happen)
model_landscape_size = '1792x1024'
model_square_size = '1024x1024'
logger.warning(f"[process_image_generation_queue] No model config, using fallback sizes")
# Featured image always uses model-specific landscape size
featured_image_size = model_landscape_size
# In-article images: alternating square/landscape based on position (handled in image loop)
in_article_square_size = DEFAULT_SQUARE_SIZE
in_article_square_size = model_square_size
in_article_landscape_size = model_landscape_size
logger.info(f"[process_image_generation_queue] Settings loaded:")