Merge branch 'main' of https://git.igny8.com/salman/igny8
This commit is contained in:
alorig
@@ -43,33 +43,21 @@ class AICore:
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self._load_account_settings()
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def _load_account_settings(self):
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"""Load API keys from IntegrationSettings for account only - no fallbacks"""
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def get_integration_key(integration_type: str, account):
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if not account:
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return None
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try:
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from igny8_core.modules.system.models import IntegrationSettings
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settings_obj = IntegrationSettings.objects.filter(
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integration_type=integration_type,
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account=account,
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is_active=True
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).first()
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if settings_obj and settings_obj.config:
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return settings_obj.config.get('apiKey')
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except Exception as e:
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logger.warning(f"Could not load {integration_type} settings for account {getattr(account, 'id', None)}: {e}", exc_info=True)
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return None
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# Load account-specific keys only - configure via Django admin
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if self.account:
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self._openai_api_key = get_integration_key('openai', self.account)
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self._runware_api_key = get_integration_key('runware', self.account)
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# Fallback to Django settings as last resort
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if not self._openai_api_key:
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self._openai_api_key = getattr(settings, 'OPENAI_API_KEY', None)
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if not self._runware_api_key:
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self._runware_api_key = getattr(settings, 'RUNWARE_API_KEY', None)
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"""Load API keys from GlobalIntegrationSettings (platform-wide, used by ALL accounts)"""
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try:
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from igny8_core.modules.system.global_settings_models import GlobalIntegrationSettings
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# Get global settings - single instance used by ALL accounts
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global_settings = GlobalIntegrationSettings.get_instance()
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# Load API keys from global settings (platform-wide)
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self._openai_api_key = global_settings.openai_api_key
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self._runware_api_key = global_settings.runware_api_key
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except Exception as e:
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logger.error(f"Could not load GlobalIntegrationSettings: {e}", exc_info=True)
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self._openai_api_key = None
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self._runware_api_key = None
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def get_api_key(self, integration_type: str = 'openai') -> Optional[str]:
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"""Get API key for integration type"""
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@@ -197,12 +197,12 @@ class GenerateImagePromptsFunction(BaseAIFunction):
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prompt_text = str(prompt_data)
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caption_text = ''
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heading = h2_headings[idx] if idx < len(h2_headings) else f"Section {idx + 1}"
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heading = h2_headings[idx] if idx < len(h2_headings) else f"Section {idx}"
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Images.objects.update_or_create(
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content=content,
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image_type='in_article',
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position=idx + 1,
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position=idx, # 0-based position matching section array indices
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defaults={
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'prompt': prompt_text,
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'caption': caption_text,
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@@ -218,27 +218,33 @@ class GenerateImagePromptsFunction(BaseAIFunction):
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# Helper methods
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def _get_max_in_article_images(self, account) -> int:
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"""Get max_in_article_images from AWS account IntegrationSettings only"""
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"""
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Get max_in_article_images from settings.
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Uses account's IntegrationSettings override, or GlobalIntegrationSettings.
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"""
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from igny8_core.modules.system.models import IntegrationSettings
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from igny8_core.auth.models import Account
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from igny8_core.modules.system.global_settings_models import GlobalIntegrationSettings
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# Only use system account (aws-admin) settings
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system_account = Account.objects.get(slug='aws-admin')
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settings = IntegrationSettings.objects.get(
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account=system_account,
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integration_type='image_generation',
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is_active=True
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)
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max_images = settings.config.get('max_in_article_images')
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if max_images is None:
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raise ValueError(
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"max_in_article_images not configured in aws-admin image_generation settings. "
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"Please set this value in the Integration Settings page."
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# Try account-specific override first
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try:
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settings = IntegrationSettings.objects.get(
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account=account,
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integration_type='image_generation',
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is_active=True
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)
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max_images = settings.config.get('max_in_article_images')
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if max_images is not None:
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max_images = int(max_images)
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logger.info(f"Using max_in_article_images={max_images} from account {account.id} IntegrationSettings override")
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return max_images
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except IntegrationSettings.DoesNotExist:
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logger.debug(f"No IntegrationSettings override for account {account.id}, using GlobalIntegrationSettings")
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max_images = int(max_images)
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logger.info(f"Using max_in_article_images={max_images} from aws-admin account")
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# Use GlobalIntegrationSettings default
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global_settings = GlobalIntegrationSettings.get_instance()
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max_images = global_settings.max_in_article_images
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logger.info(f"Using max_in_article_images={max_images} from GlobalIntegrationSettings (account {account.id})")
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return max_images
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def _extract_content_elements(self, content: Content, max_images: int) -> Dict:
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@@ -67,32 +67,40 @@ class GenerateImagesFunction(BaseAIFunction):
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if not tasks:
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raise ValueError("No tasks found")
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# Get image generation settings from aws-admin account only (global settings)
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# Get image generation settings
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# Try account-specific override, otherwise use GlobalIntegrationSettings
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from igny8_core.modules.system.models import IntegrationSettings
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from igny8_core.auth.models import Account
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from igny8_core.modules.system.global_settings_models import GlobalIntegrationSettings
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system_account = Account.objects.get(slug='aws-admin')
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integration = IntegrationSettings.objects.get(
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account=system_account,
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integration_type='image_generation',
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is_active=True
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)
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image_settings = integration.config or {}
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image_settings = {}
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try:
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integration = IntegrationSettings.objects.get(
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account=account,
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integration_type='image_generation',
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is_active=True
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)
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image_settings = integration.config or {}
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logger.info(f"Using image settings from account {account.id} IntegrationSettings override")
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except IntegrationSettings.DoesNotExist:
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logger.info(f"No IntegrationSettings override for account {account.id}, using GlobalIntegrationSettings")
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# Extract settings with defaults
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provider = image_settings.get('provider') or image_settings.get('service', 'openai')
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# Use GlobalIntegrationSettings for missing values
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global_settings = GlobalIntegrationSettings.get_instance()
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# Extract settings with defaults from global settings
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provider = image_settings.get('provider') or image_settings.get('service') or global_settings.default_image_service
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if provider == 'runware':
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model = image_settings.get('model') or image_settings.get('runwareModel', 'runware:97@1')
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model = image_settings.get('model') or image_settings.get('runwareModel') or global_settings.runware_model
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else:
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model = image_settings.get('model', 'dall-e-3')
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model = image_settings.get('model') or global_settings.dalle_model
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return {
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'tasks': tasks,
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'account': account,
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'provider': provider,
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'model': model,
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'image_type': image_settings.get('image_type', 'realistic'),
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'max_in_article_images': int(image_settings.get('max_in_article_images')),
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'image_type': image_settings.get('image_type') or global_settings.image_style,
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'max_in_article_images': int(image_settings.get('max_in_article_images') or global_settings.max_in_article_images),
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'desktop_enabled': image_settings.get('desktop_enabled', True),
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'mobile_enabled': image_settings.get('mobile_enabled', True),
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}
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@@ -181,41 +181,47 @@ def process_image_generation_queue(self, image_ids: list, account_id: int = None
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failed = 0
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results = []
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# Get image generation settings from IntegrationSettings
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# Always use system account settings (aws-admin) for global configuration
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logger.info("[process_image_generation_queue] Step 1: Loading image generation settings from aws-admin")
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from igny8_core.auth.models import Account
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# Get image generation settings
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# Try account-specific override, otherwise use GlobalIntegrationSettings
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logger.info("[process_image_generation_queue] Step 1: Loading image generation settings")
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from igny8_core.modules.system.global_settings_models import GlobalIntegrationSettings
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config = {}
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try:
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system_account = Account.objects.get(slug='aws-admin')
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image_settings = IntegrationSettings.objects.get(
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account=system_account,
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account=account,
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integration_type='image_generation',
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is_active=True
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)
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logger.info(f"[process_image_generation_queue] Using system account (aws-admin) settings")
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logger.info(f"[process_image_generation_queue] Using account {account.id} IntegrationSettings override")
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config = image_settings.config or {}
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except (Account.DoesNotExist, IntegrationSettings.DoesNotExist):
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logger.error("[process_image_generation_queue] ERROR: Image generation settings not found in aws-admin account")
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return {'success': False, 'error': 'Image generation settings not found in aws-admin account'}
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except IntegrationSettings.DoesNotExist:
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logger.info(f"[process_image_generation_queue] No IntegrationSettings override for account {account.id}, using GlobalIntegrationSettings")
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except Exception as e:
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logger.error(f"[process_image_generation_queue] ERROR loading image generation settings: {e}", exc_info=True)
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return {'success': False, 'error': f'Error loading image generation settings: {str(e)}'}
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# Use GlobalIntegrationSettings for missing values
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global_settings = GlobalIntegrationSettings.get_instance()
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logger.info(f"[process_image_generation_queue] Image generation settings loaded. Config keys: {list(config.keys())}")
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logger.info(f"[process_image_generation_queue] Full config: {config}")
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# Get provider and model from config (respect user settings)
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provider = config.get('provider', 'openai')
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# Get model - try 'model' first, then 'imageModel' as fallback
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model = config.get('model') or config.get('imageModel') or 'dall-e-3'
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# Get provider and model from config with global fallbacks
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provider = config.get('provider') or global_settings.default_image_service
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if provider == 'runware':
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model = config.get('model') or config.get('imageModel') or global_settings.runware_model
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else:
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model = config.get('model') or config.get('imageModel') or global_settings.dalle_model
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logger.info(f"[process_image_generation_queue] Using PROVIDER: {provider}, MODEL: {model} from settings")
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image_type = config.get('image_type', 'realistic')
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image_type = config.get('image_type') or global_settings.image_style
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image_format = config.get('image_format', 'webp')
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desktop_enabled = config.get('desktop_enabled', True)
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mobile_enabled = config.get('mobile_enabled', True)
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# Get image sizes from config, with fallback defaults
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featured_image_size = config.get('featured_image_size') or ('1280x832' if provider == 'runware' else '1024x1024')
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desktop_image_size = config.get('desktop_image_size') or '1024x1024'
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desktop_image_size = config.get('desktop_image_size') or global_settings.desktop_image_size
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in_article_image_size = config.get('in_article_image_size') or '512x512' # Default to 512x512
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logger.info(f"[process_image_generation_queue] Settings loaded:")
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@@ -226,44 +232,22 @@ def process_image_generation_queue(self, image_ids: list, account_id: int = None
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logger.info(f" - Desktop enabled: {desktop_enabled}")
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logger.info(f" - Mobile enabled: {mobile_enabled}")
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# Get provider API key (using same approach as test image generation)
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# Note: API key is stored as 'apiKey' (camelCase) in IntegrationSettings.config
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# Normal users use system account settings (aws-admin) via fallback
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logger.info(f"[process_image_generation_queue] Step 2: Loading {provider.upper()} API key")
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try:
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provider_settings = IntegrationSettings.objects.get(
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account=account,
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||||
integration_type=provider, # Use the provider from settings
|
||||
is_active=True
|
||||
)
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logger.info(f"[process_image_generation_queue] {provider.upper()} integration settings found for account {account.id}")
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||||
except IntegrationSettings.DoesNotExist:
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||||
# Fallback to system account (aws-admin) settings
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logger.info(f"[process_image_generation_queue] No {provider.upper()} settings for account {account.id}, falling back to system account")
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from igny8_core.auth.models import Account
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||||
try:
|
||||
system_account = Account.objects.get(slug='aws-admin')
|
||||
provider_settings = IntegrationSettings.objects.get(
|
||||
account=system_account,
|
||||
integration_type=provider,
|
||||
is_active=True
|
||||
)
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logger.info(f"[process_image_generation_queue] Using system account (aws-admin) {provider.upper()} settings")
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||||
except (Account.DoesNotExist, IntegrationSettings.DoesNotExist):
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||||
logger.error(f"[process_image_generation_queue] ERROR: {provider.upper()} integration settings not found in system account either")
|
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return {'success': False, 'error': f'{provider.upper()} integration not found or not active'}
|
||||
except Exception as e:
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||||
logger.error(f"[process_image_generation_queue] ERROR getting {provider.upper()} API key: {e}", exc_info=True)
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||||
return {'success': False, 'error': f'Error retrieving {provider.upper()} API key: {str(e)}'}
|
||||
# Get provider API key
|
||||
# API keys are ALWAYS from GlobalIntegrationSettings (accounts cannot override API keys)
|
||||
# Account IntegrationSettings only store provider preference, NOT API keys
|
||||
logger.info(f"[process_image_generation_queue] Step 2: Loading {provider.upper()} API key from GlobalIntegrationSettings")
|
||||
|
||||
# Extract API key from provider settings
|
||||
logger.info(f"[process_image_generation_queue] {provider.upper()} config keys: {list(provider_settings.config.keys()) if provider_settings.config else 'None'}")
|
||||
# Get API key from GlobalIntegrationSettings
|
||||
if provider == 'runware':
|
||||
api_key = global_settings.runware_api_key
|
||||
elif provider == 'openai':
|
||||
api_key = global_settings.dalle_api_key or global_settings.openai_api_key
|
||||
else:
|
||||
api_key = None
|
||||
|
||||
api_key = provider_settings.config.get('apiKey') if provider_settings.config else None
|
||||
if not api_key:
|
||||
logger.error(f"[process_image_generation_queue] {provider.upper()} API key not found in config")
|
||||
logger.error(f"[process_image_generation_queue] {provider.upper()} config: {provider_settings.config}")
|
||||
return {'success': False, 'error': f'{provider.upper()} API key not configured'}
|
||||
logger.error(f"[process_image_generation_queue] {provider.upper()} API key not configured in GlobalIntegrationSettings")
|
||||
return {'success': False, 'error': f'{provider.upper()} API key not configured in GlobalIntegrationSettings'}
|
||||
|
||||
# Log API key presence (but not the actual key for security)
|
||||
api_key_preview = f"{api_key[:10]}...{api_key[-4:]}" if len(api_key) > 14 else "***"
|
||||
|
||||
@@ -5,6 +5,7 @@ import time
|
||||
import logging
|
||||
from typing import List, Dict, Any, Optional, Callable
|
||||
from datetime import datetime
|
||||
from decimal import Decimal
|
||||
from igny8_core.ai.constants import DEBUG_MODE
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
@@ -195,24 +196,35 @@ class CostTracker:
|
||||
"""Tracks API costs and token usage"""
|
||||
|
||||
def __init__(self):
|
||||
self.total_cost = 0.0
|
||||
self.total_cost = Decimal('0.0')
|
||||
self.total_tokens = 0
|
||||
self.operations = []
|
||||
|
||||
def record(self, function_name: str, cost: float, tokens: int, model: str = None):
|
||||
"""Record an API call cost"""
|
||||
def record(self, function_name: str, cost, tokens: int, model: str = None):
|
||||
"""Record an API call cost
|
||||
|
||||
Args:
|
||||
function_name: Name of the AI function
|
||||
cost: Cost value (can be float or Decimal)
|
||||
tokens: Number of tokens used
|
||||
model: Model name
|
||||
"""
|
||||
# Convert cost to Decimal if it's a float to avoid type mixing
|
||||
if not isinstance(cost, Decimal):
|
||||
cost = Decimal(str(cost))
|
||||
|
||||
self.total_cost += cost
|
||||
self.total_tokens += tokens
|
||||
self.operations.append({
|
||||
'function': function_name,
|
||||
'cost': cost,
|
||||
'cost': float(cost), # Store as float for JSON serialization
|
||||
'tokens': tokens,
|
||||
'model': model
|
||||
})
|
||||
|
||||
def get_total(self) -> float:
|
||||
"""Get total cost"""
|
||||
return self.total_cost
|
||||
def get_total(self):
|
||||
"""Get total cost (returns float for JSON serialization)"""
|
||||
return float(self.total_cost)
|
||||
|
||||
def get_total_tokens(self) -> int:
|
||||
"""Get total tokens"""
|
||||
|
||||
@@ -135,7 +135,7 @@ def validate_api_key(api_key: Optional[str], integration_type: str = 'openai') -
|
||||
|
||||
def validate_model(model: str, model_type: str = 'text') -> Dict[str, Any]:
|
||||
"""
|
||||
Validate that model is in supported list.
|
||||
Validate that model is in supported list using database.
|
||||
|
||||
Args:
|
||||
model: Model name to validate
|
||||
@@ -144,27 +144,59 @@ def validate_model(model: str, model_type: str = 'text') -> Dict[str, Any]:
|
||||
Returns:
|
||||
Dict with 'valid' (bool) and optional 'error' (str)
|
||||
"""
|
||||
from .constants import MODEL_RATES, VALID_OPENAI_IMAGE_MODELS
|
||||
|
||||
if model_type == 'text':
|
||||
if model not in MODEL_RATES:
|
||||
return {
|
||||
'valid': False,
|
||||
'error': f'Model "{model}" is not in supported models list'
|
||||
}
|
||||
elif model_type == 'image':
|
||||
if model not in VALID_OPENAI_IMAGE_MODELS:
|
||||
return {
|
||||
'valid': False,
|
||||
'error': f'Model "{model}" is not valid for OpenAI image generation. Only {", ".join(VALID_OPENAI_IMAGE_MODELS)} are supported.'
|
||||
}
|
||||
|
||||
return {'valid': True}
|
||||
try:
|
||||
# Try database first
|
||||
from igny8_core.business.billing.models import AIModelConfig
|
||||
|
||||
exists = AIModelConfig.objects.filter(
|
||||
model_name=model,
|
||||
model_type=model_type,
|
||||
is_active=True
|
||||
).exists()
|
||||
|
||||
if not exists:
|
||||
# Get available models for better error message
|
||||
available = list(AIModelConfig.objects.filter(
|
||||
model_type=model_type,
|
||||
is_active=True
|
||||
).values_list('model_name', flat=True))
|
||||
|
||||
if available:
|
||||
return {
|
||||
'valid': False,
|
||||
'error': f'Model "{model}" is not active or not found. Available {model_type} models: {", ".join(available)}'
|
||||
}
|
||||
else:
|
||||
return {
|
||||
'valid': False,
|
||||
'error': f'Model "{model}" is not found in database'
|
||||
}
|
||||
|
||||
return {'valid': True}
|
||||
|
||||
except Exception:
|
||||
# Fallback to constants if database fails
|
||||
from .constants import MODEL_RATES, VALID_OPENAI_IMAGE_MODELS
|
||||
|
||||
if model_type == 'text':
|
||||
if model not in MODEL_RATES:
|
||||
return {
|
||||
'valid': False,
|
||||
'error': f'Model "{model}" is not in supported models list'
|
||||
}
|
||||
elif model_type == 'image':
|
||||
if model not in VALID_OPENAI_IMAGE_MODELS:
|
||||
return {
|
||||
'valid': False,
|
||||
'error': f'Model "{model}" is not valid for OpenAI image generation. Only {", ".join(VALID_OPENAI_IMAGE_MODELS)} are supported.'
|
||||
}
|
||||
|
||||
return {'valid': True}
|
||||
|
||||
|
||||
def validate_image_size(size: str, model: str) -> Dict[str, Any]:
|
||||
"""
|
||||
Validate that image size is valid for the selected model.
|
||||
Validate that image size is valid for the selected model using database.
|
||||
|
||||
Args:
|
||||
size: Image size (e.g., '1024x1024')
|
||||
@@ -173,14 +205,40 @@ def validate_image_size(size: str, model: str) -> Dict[str, Any]:
|
||||
Returns:
|
||||
Dict with 'valid' (bool) and optional 'error' (str)
|
||||
"""
|
||||
from .constants import VALID_SIZES_BY_MODEL
|
||||
|
||||
valid_sizes = VALID_SIZES_BY_MODEL.get(model, [])
|
||||
if size not in valid_sizes:
|
||||
return {
|
||||
'valid': False,
|
||||
'error': f'Image size "{size}" is not valid for model "{model}". Valid sizes are: {", ".join(valid_sizes)}'
|
||||
}
|
||||
|
||||
return {'valid': True}
|
||||
try:
|
||||
# Try database first
|
||||
from igny8_core.business.billing.models import AIModelConfig
|
||||
|
||||
model_config = AIModelConfig.objects.filter(
|
||||
model_name=model,
|
||||
model_type='image',
|
||||
is_active=True
|
||||
).first()
|
||||
|
||||
if model_config:
|
||||
if not model_config.validate_size(size):
|
||||
valid_sizes = model_config.valid_sizes or []
|
||||
return {
|
||||
'valid': False,
|
||||
'error': f'Image size "{size}" is not valid for model "{model}". Valid sizes are: {", ".join(valid_sizes)}'
|
||||
}
|
||||
return {'valid': True}
|
||||
else:
|
||||
return {
|
||||
'valid': False,
|
||||
'error': f'Image model "{model}" not found in database'
|
||||
}
|
||||
|
||||
except Exception:
|
||||
# Fallback to constants if database fails
|
||||
from .constants import VALID_SIZES_BY_MODEL
|
||||
|
||||
valid_sizes = VALID_SIZES_BY_MODEL.get(model, [])
|
||||
if size not in valid_sizes:
|
||||
return {
|
||||
'valid': False,
|
||||
'error': f'Image size "{size}" is not valid for model "{model}". Valid sizes are: {", ".join(valid_sizes)}'
|
||||
}
|
||||
|
||||
return {'valid': True}
|
||||
|
||||
|
||||
@@ -791,3 +791,238 @@ class AccountPaymentMethod(AccountBaseModel):
|
||||
|
||||
def __str__(self):
|
||||
return f"{self.account_id} - {self.display_name} ({self.type})"
|
||||
|
||||
|
||||
class AIModelConfig(models.Model):
|
||||
"""
|
||||
AI Model Configuration - Database-driven model pricing and capabilities.
|
||||
Replaces hardcoded MODEL_RATES and IMAGE_MODEL_RATES from constants.py
|
||||
|
||||
Two pricing models:
|
||||
- Text models: Cost per 1M tokens (input/output), credits calculated AFTER AI call
|
||||
- Image models: Cost per image, credits calculated BEFORE AI call
|
||||
"""
|
||||
|
||||
MODEL_TYPE_CHOICES = [
|
||||
('text', 'Text Generation'),
|
||||
('image', 'Image Generation'),
|
||||
('embedding', 'Embedding'),
|
||||
]
|
||||
|
||||
PROVIDER_CHOICES = [
|
||||
('openai', 'OpenAI'),
|
||||
('anthropic', 'Anthropic'),
|
||||
('runware', 'Runware'),
|
||||
('google', 'Google'),
|
||||
]
|
||||
|
||||
# Basic Information
|
||||
model_name = models.CharField(
|
||||
max_length=100,
|
||||
unique=True,
|
||||
db_index=True,
|
||||
help_text="Model identifier used in API calls (e.g., 'gpt-4o-mini', 'dall-e-3')"
|
||||
)
|
||||
|
||||
display_name = models.CharField(
|
||||
max_length=200,
|
||||
help_text="Human-readable name shown in UI (e.g., 'GPT-4o mini - Fast & Affordable')"
|
||||
)
|
||||
|
||||
model_type = models.CharField(
|
||||
max_length=20,
|
||||
choices=MODEL_TYPE_CHOICES,
|
||||
db_index=True,
|
||||
help_text="Type of model - determines which pricing fields are used"
|
||||
)
|
||||
|
||||
provider = models.CharField(
|
||||
max_length=50,
|
||||
choices=PROVIDER_CHOICES,
|
||||
db_index=True,
|
||||
help_text="AI provider (OpenAI, Anthropic, etc.)"
|
||||
)
|
||||
|
||||
# Text Model Pricing (Only for model_type='text')
|
||||
input_cost_per_1m = models.DecimalField(
|
||||
max_digits=10,
|
||||
decimal_places=4,
|
||||
null=True,
|
||||
blank=True,
|
||||
validators=[MinValueValidator(Decimal('0.0001'))],
|
||||
help_text="Cost per 1 million input tokens (USD). For text models only."
|
||||
)
|
||||
|
||||
output_cost_per_1m = models.DecimalField(
|
||||
max_digits=10,
|
||||
decimal_places=4,
|
||||
null=True,
|
||||
blank=True,
|
||||
validators=[MinValueValidator(Decimal('0.0001'))],
|
||||
help_text="Cost per 1 million output tokens (USD). For text models only."
|
||||
)
|
||||
|
||||
context_window = models.IntegerField(
|
||||
null=True,
|
||||
blank=True,
|
||||
validators=[MinValueValidator(1)],
|
||||
help_text="Maximum input tokens (context length). For text models only."
|
||||
)
|
||||
|
||||
max_output_tokens = models.IntegerField(
|
||||
null=True,
|
||||
blank=True,
|
||||
validators=[MinValueValidator(1)],
|
||||
help_text="Maximum output tokens per request. For text models only."
|
||||
)
|
||||
|
||||
# Image Model Pricing (Only for model_type='image')
|
||||
cost_per_image = models.DecimalField(
|
||||
max_digits=10,
|
||||
decimal_places=4,
|
||||
null=True,
|
||||
blank=True,
|
||||
validators=[MinValueValidator(Decimal('0.0001'))],
|
||||
help_text="Fixed cost per image generation (USD). For image models only."
|
||||
)
|
||||
|
||||
valid_sizes = models.JSONField(
|
||||
null=True,
|
||||
blank=True,
|
||||
help_text='Array of valid image sizes (e.g., ["1024x1024", "1024x1792"]). For image models only.'
|
||||
)
|
||||
|
||||
# Capabilities
|
||||
supports_json_mode = models.BooleanField(
|
||||
default=False,
|
||||
help_text="True for models with JSON response format support"
|
||||
)
|
||||
|
||||
supports_vision = models.BooleanField(
|
||||
default=False,
|
||||
help_text="True for models that can analyze images"
|
||||
)
|
||||
|
||||
supports_function_calling = models.BooleanField(
|
||||
default=False,
|
||||
help_text="True for models with function calling capability"
|
||||
)
|
||||
|
||||
# Status & Configuration
|
||||
is_active = models.BooleanField(
|
||||
default=True,
|
||||
db_index=True,
|
||||
help_text="Enable/disable model without deleting"
|
||||
)
|
||||
|
||||
is_default = models.BooleanField(
|
||||
default=False,
|
||||
db_index=True,
|
||||
help_text="Mark as default model for its type (only one per type)"
|
||||
)
|
||||
|
||||
sort_order = models.IntegerField(
|
||||
default=0,
|
||||
help_text="Control order in dropdown lists (lower numbers first)"
|
||||
)
|
||||
|
||||
# Metadata
|
||||
description = models.TextField(
|
||||
blank=True,
|
||||
help_text="Admin notes about model usage, strengths, limitations"
|
||||
)
|
||||
|
||||
release_date = models.DateField(
|
||||
null=True,
|
||||
blank=True,
|
||||
help_text="When model was released/added"
|
||||
)
|
||||
|
||||
deprecation_date = models.DateField(
|
||||
null=True,
|
||||
blank=True,
|
||||
help_text="When model will be removed"
|
||||
)
|
||||
|
||||
# Audit Fields
|
||||
created_at = models.DateTimeField(auto_now_add=True)
|
||||
updated_at = models.DateTimeField(auto_now=True)
|
||||
updated_by = models.ForeignKey(
|
||||
settings.AUTH_USER_MODEL,
|
||||
null=True,
|
||||
blank=True,
|
||||
on_delete=models.SET_NULL,
|
||||
related_name='ai_model_updates',
|
||||
help_text="Admin who last updated"
|
||||
)
|
||||
|
||||
# History tracking
|
||||
history = HistoricalRecords()
|
||||
|
||||
class Meta:
|
||||
app_label = 'billing'
|
||||
db_table = 'igny8_ai_model_config'
|
||||
verbose_name = 'AI Model Configuration'
|
||||
verbose_name_plural = 'AI Model Configurations'
|
||||
ordering = ['model_type', 'sort_order', 'model_name']
|
||||
indexes = [
|
||||
models.Index(fields=['model_type', 'is_active']),
|
||||
models.Index(fields=['provider', 'is_active']),
|
||||
models.Index(fields=['is_default', 'model_type']),
|
||||
]
|
||||
|
||||
def __str__(self):
|
||||
return self.display_name
|
||||
|
||||
def save(self, *args, **kwargs):
|
||||
"""Ensure only one is_default per model_type"""
|
||||
if self.is_default:
|
||||
# Unset other defaults for same model_type
|
||||
AIModelConfig.objects.filter(
|
||||
model_type=self.model_type,
|
||||
is_default=True
|
||||
).exclude(pk=self.pk).update(is_default=False)
|
||||
super().save(*args, **kwargs)
|
||||
|
||||
def get_cost_for_tokens(self, input_tokens, output_tokens):
|
||||
"""Calculate cost for text models based on token usage"""
|
||||
if self.model_type != 'text':
|
||||
raise ValueError("get_cost_for_tokens only applies to text models")
|
||||
|
||||
if not self.input_cost_per_1m or not self.output_cost_per_1m:
|
||||
raise ValueError(f"Model {self.model_name} missing cost_per_1m values")
|
||||
|
||||
cost = (
|
||||
(Decimal(input_tokens) * self.input_cost_per_1m) +
|
||||
(Decimal(output_tokens) * self.output_cost_per_1m)
|
||||
) / Decimal('1000000')
|
||||
|
||||
return cost
|
||||
|
||||
def get_cost_for_images(self, num_images):
|
||||
"""Calculate cost for image models"""
|
||||
if self.model_type != 'image':
|
||||
raise ValueError("get_cost_for_images only applies to image models")
|
||||
|
||||
if not self.cost_per_image:
|
||||
raise ValueError(f"Model {self.model_name} missing cost_per_image")
|
||||
|
||||
return self.cost_per_image * Decimal(num_images)
|
||||
|
||||
def validate_size(self, size):
|
||||
"""Check if size is valid for this image model"""
|
||||
if self.model_type != 'image':
|
||||
raise ValueError("validate_size only applies to image models")
|
||||
|
||||
if not self.valid_sizes:
|
||||
return True # No size restrictions
|
||||
|
||||
return size in self.valid_sizes
|
||||
|
||||
def get_display_with_pricing(self):
|
||||
"""For dropdowns: show model with pricing"""
|
||||
if self.model_type == 'text':
|
||||
return f"{self.display_name} - ${self.input_cost_per_1m}/${self.output_cost_per_1m} per 1M"
|
||||
elif self.model_type == 'image':
|
||||
return f"{self.display_name} - ${self.cost_per_image} per image"
|
||||
return self.display_name
|
||||
|
||||
@@ -3,97 +3,116 @@ Credit Service for managing credit transactions and deductions
|
||||
"""
|
||||
from django.db import transaction
|
||||
from django.utils import timezone
|
||||
from decimal import Decimal
|
||||
import math
|
||||
from igny8_core.business.billing.models import CreditTransaction, CreditUsageLog, AIModelConfig
|
||||
from igny8_core.business.billing.models import CreditTransaction, CreditUsageLog
|
||||
from igny8_core.business.billing.constants import CREDIT_COSTS
|
||||
from igny8_core.business.billing.exceptions import InsufficientCreditsError, CreditCalculationError
|
||||
from igny8_core.auth.models import Account
|
||||
|
||||
|
||||
class CreditService:
|
||||
"""Service for managing credits"""
|
||||
"""Service for managing credits - Token-based only"""
|
||||
|
||||
@staticmethod
|
||||
def get_credit_cost(operation_type, amount=None):
|
||||
def calculate_credits_from_tokens(operation_type, tokens_input, tokens_output):
|
||||
"""
|
||||
Get credit cost for operation.
|
||||
Now checks database config first, falls back to constants.
|
||||
Calculate credits from actual token usage using configured ratio.
|
||||
This is the ONLY way credits are calculated in the system.
|
||||
|
||||
Args:
|
||||
operation_type: Type of operation (from CREDIT_COSTS)
|
||||
amount: Optional amount (word count, image count, etc.)
|
||||
operation_type: Type of operation
|
||||
tokens_input: Input tokens used
|
||||
tokens_output: Output tokens used
|
||||
|
||||
Returns:
|
||||
int: Number of credits required
|
||||
|
||||
int: Credits to deduct
|
||||
|
||||
Raises:
|
||||
CreditCalculationError: If operation type is unknown
|
||||
CreditCalculationError: If configuration error
|
||||
"""
|
||||
import logging
|
||||
import math
|
||||
from igny8_core.business.billing.models import CreditCostConfig, BillingConfiguration
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
# Try to get from database config first
|
||||
try:
|
||||
from igny8_core.business.billing.models import CreditCostConfig
|
||||
|
||||
config = CreditCostConfig.objects.filter(
|
||||
operation_type=operation_type,
|
||||
is_active=True
|
||||
).first()
|
||||
|
||||
if config:
|
||||
base_cost = config.credits_cost
|
||||
|
||||
# Apply unit-based calculation
|
||||
if config.unit == 'per_100_words' and amount:
|
||||
return max(1, int(base_cost * (amount / 100)))
|
||||
elif config.unit == 'per_200_words' and amount:
|
||||
return max(1, int(base_cost * (amount / 200)))
|
||||
elif config.unit in ['per_item', 'per_image'] and amount:
|
||||
return base_cost * amount
|
||||
else:
|
||||
return base_cost
|
||||
# Get operation config (use global default if not found)
|
||||
config = CreditCostConfig.objects.filter(
|
||||
operation_type=operation_type,
|
||||
is_active=True
|
||||
).first()
|
||||
|
||||
except Exception as e:
|
||||
logger.warning(f"Failed to get cost from database, using constants: {e}")
|
||||
if not config:
|
||||
# Use global billing config as fallback
|
||||
billing_config = BillingConfiguration.get_config()
|
||||
tokens_per_credit = billing_config.default_tokens_per_credit
|
||||
min_credits = 1
|
||||
logger.info(f"No config for {operation_type}, using default: {tokens_per_credit} tokens/credit")
|
||||
else:
|
||||
tokens_per_credit = config.tokens_per_credit
|
||||
min_credits = config.min_credits
|
||||
|
||||
# Fallback to hardcoded constants
|
||||
base_cost = CREDIT_COSTS.get(operation_type, 0)
|
||||
if base_cost == 0:
|
||||
raise CreditCalculationError(f"Unknown operation type: {operation_type}")
|
||||
# Calculate total tokens
|
||||
total_tokens = (tokens_input or 0) + (tokens_output or 0)
|
||||
|
||||
# Variable cost operations (legacy logic)
|
||||
if operation_type == 'content_generation' and amount:
|
||||
# Per 100 words
|
||||
return max(1, int(base_cost * (amount / 100)))
|
||||
elif operation_type == 'optimization' and amount:
|
||||
# Per 200 words
|
||||
return max(1, int(base_cost * (amount / 200)))
|
||||
elif operation_type == 'image_generation' and amount:
|
||||
# Per image
|
||||
return base_cost * amount
|
||||
elif operation_type == 'idea_generation' and amount:
|
||||
# Per idea
|
||||
return base_cost * amount
|
||||
# Calculate credits (fractional)
|
||||
if tokens_per_credit <= 0:
|
||||
raise CreditCalculationError(f"Invalid tokens_per_credit: {tokens_per_credit}")
|
||||
|
||||
# Fixed cost operations
|
||||
return base_cost
|
||||
credits_float = total_tokens / tokens_per_credit
|
||||
|
||||
# Get rounding mode from global config
|
||||
billing_config = BillingConfiguration.get_config()
|
||||
rounding_mode = billing_config.credit_rounding_mode
|
||||
|
||||
if rounding_mode == 'up':
|
||||
credits = math.ceil(credits_float)
|
||||
elif rounding_mode == 'down':
|
||||
credits = math.floor(credits_float)
|
||||
else: # nearest
|
||||
credits = round(credits_float)
|
||||
|
||||
# Apply minimum
|
||||
credits = max(credits, min_credits)
|
||||
|
||||
logger.info(
|
||||
f"Calculated credits for {operation_type}: "
|
||||
f"{total_tokens} tokens ({tokens_input} in, {tokens_output} out) "
|
||||
f"÷ {tokens_per_credit} = {credits} credits"
|
||||
)
|
||||
|
||||
return credits
|
||||
|
||||
@staticmethod
|
||||
def check_credits(account, operation_type, amount=None):
|
||||
def check_credits(account, operation_type, estimated_amount=None):
|
||||
"""
|
||||
Check if account has sufficient credits for an operation.
|
||||
For token-based operations, this is an estimate check only.
|
||||
Actual deduction happens after AI call with real token usage.
|
||||
|
||||
Args:
|
||||
account: Account instance
|
||||
operation_type: Type of operation
|
||||
amount: Optional amount (word count, image count, etc.)
|
||||
estimated_amount: Optional estimated amount (for non-token operations)
|
||||
|
||||
Raises:
|
||||
InsufficientCreditsError: If account doesn't have enough credits
|
||||
"""
|
||||
required = CreditService.get_credit_cost(operation_type, amount)
|
||||
from igny8_core.business.billing.models import CreditCostConfig
|
||||
from igny8_core.business.billing.constants import CREDIT_COSTS
|
||||
|
||||
# Get operation config
|
||||
config = CreditCostConfig.objects.filter(
|
||||
operation_type=operation_type,
|
||||
is_active=True
|
||||
).first()
|
||||
|
||||
if config:
|
||||
# Use minimum credits as estimate for token-based operations
|
||||
required = config.min_credits
|
||||
else:
|
||||
# Fallback to constants
|
||||
required = CREDIT_COSTS.get(operation_type, 1)
|
||||
|
||||
if account.credits < required:
|
||||
raise InsufficientCreditsError(
|
||||
f"Insufficient credits. Required: {required}, Available: {account.credits}"
|
||||
@@ -101,28 +120,50 @@ class CreditService:
|
||||
return True
|
||||
|
||||
@staticmethod
|
||||
def check_credits_legacy(account, required_credits):
|
||||
def check_credits_legacy(account, amount):
|
||||
"""
|
||||
Legacy method: Check if account has enough credits (for backward compatibility).
|
||||
Legacy method to check credits for a known amount.
|
||||
Used internally by deduct_credits.
|
||||
|
||||
Args:
|
||||
account: Account instance
|
||||
required_credits: Number of credits required
|
||||
amount: Required credits amount
|
||||
|
||||
Raises:
|
||||
InsufficientCreditsError: If account doesn't have enough credits
|
||||
"""
|
||||
if account.credits < required_credits:
|
||||
if account.credits < amount:
|
||||
raise InsufficientCreditsError(
|
||||
f"Insufficient credits. Required: {required_credits}, Available: {account.credits}"
|
||||
f"Insufficient credits. Required: {amount}, Available: {account.credits}"
|
||||
)
|
||||
return True
|
||||
|
||||
@staticmethod
|
||||
def check_credits_for_tokens(account, operation_type, estimated_tokens_input, estimated_tokens_output):
|
||||
"""
|
||||
Check if account has sufficient credits based on estimated token usage.
|
||||
|
||||
Args:
|
||||
account: Account instance
|
||||
operation_type: Type of operation
|
||||
estimated_tokens_input: Estimated input tokens
|
||||
estimated_tokens_output: Estimated output tokens
|
||||
|
||||
Raises:
|
||||
InsufficientCreditsError: If account doesn't have enough credits
|
||||
"""
|
||||
required = CreditService.calculate_credits_from_tokens(
|
||||
operation_type, estimated_tokens_input, estimated_tokens_output
|
||||
)
|
||||
if account.credits < required:
|
||||
raise InsufficientCreditsError(
|
||||
f"Insufficient credits. Required: {required}, Available: {account.credits}"
|
||||
)
|
||||
return True
|
||||
|
||||
@staticmethod
|
||||
@transaction.atomic
|
||||
def deduct_credits(account, amount, operation_type, description, metadata=None,
|
||||
cost_usd_input=None, cost_usd_output=None, cost_usd_total=None,
|
||||
model_config=None, tokens_input=None, tokens_output=None,
|
||||
related_object_type=None, related_object_id=None):
|
||||
def deduct_credits(account, amount, operation_type, description, metadata=None, cost_usd=None, model_used=None, tokens_input=None, tokens_output=None, related_object_type=None, related_object_id=None):
|
||||
"""
|
||||
Deduct credits and log transaction.
|
||||
|
||||
@@ -132,10 +173,8 @@ class CreditService:
|
||||
operation_type: Type of operation (from CreditUsageLog.OPERATION_TYPE_CHOICES)
|
||||
description: Description of the transaction
|
||||
metadata: Optional metadata dict
|
||||
cost_usd_input: Optional input cost in USD
|
||||
cost_usd_output: Optional output cost in USD
|
||||
cost_usd_total: Optional total cost in USD
|
||||
model_config: Optional AIModelConfig instance
|
||||
cost_usd: Optional cost in USD
|
||||
model_used: Optional AI model used
|
||||
tokens_input: Optional input tokens
|
||||
tokens_output: Optional output tokens
|
||||
related_object_type: Optional related object type
|
||||
@@ -161,93 +200,83 @@ class CreditService:
|
||||
metadata=metadata or {}
|
||||
)
|
||||
|
||||
# Create CreditUsageLog with new model_config FK
|
||||
log_data = {
|
||||
'account': account,
|
||||
'operation_type': operation_type,
|
||||
'credits_used': amount,
|
||||
'tokens_input': tokens_input,
|
||||
'tokens_output': tokens_output,
|
||||
'related_object_type': related_object_type or '',
|
||||
'related_object_id': related_object_id,
|
||||
'metadata': metadata or {},
|
||||
}
|
||||
|
||||
# Add model tracking (new FK)
|
||||
if model_config:
|
||||
log_data['model_config'] = model_config
|
||||
log_data['model_name'] = model_config.model_name
|
||||
|
||||
# Add cost tracking (new fields)
|
||||
if cost_usd_input is not None:
|
||||
log_data['cost_usd_input'] = cost_usd_input
|
||||
if cost_usd_output is not None:
|
||||
log_data['cost_usd_output'] = cost_usd_output
|
||||
if cost_usd_total is not None:
|
||||
log_data['cost_usd_total'] = cost_usd_total
|
||||
|
||||
# Legacy cost_usd field (backward compatibility)
|
||||
if cost_usd_total is not None:
|
||||
log_data['cost_usd'] = cost_usd_total
|
||||
|
||||
CreditUsageLog.objects.create(**log_data)
|
||||
# Create CreditUsageLog
|
||||
CreditUsageLog.objects.create(
|
||||
account=account,
|
||||
operation_type=operation_type,
|
||||
credits_used=amount,
|
||||
cost_usd=cost_usd,
|
||||
model_used=model_used or '',
|
||||
tokens_input=tokens_input,
|
||||
tokens_output=tokens_output,
|
||||
related_object_type=related_object_type or '',
|
||||
related_object_id=related_object_id,
|
||||
metadata=metadata or {}
|
||||
)
|
||||
|
||||
return account.credits
|
||||
|
||||
@staticmethod
|
||||
@transaction.atomic
|
||||
def deduct_credits_for_operation(account, operation_type, amount=None, description=None,
|
||||
metadata=None, cost_usd_input=None, cost_usd_output=None,
|
||||
cost_usd_total=None, model_config=None, tokens_input=None,
|
||||
tokens_output=None, related_object_type=None, related_object_id=None):
|
||||
def deduct_credits_for_operation(
|
||||
account,
|
||||
operation_type,
|
||||
tokens_input,
|
||||
tokens_output,
|
||||
description=None,
|
||||
metadata=None,
|
||||
cost_usd=None,
|
||||
model_used=None,
|
||||
related_object_type=None,
|
||||
related_object_id=None
|
||||
):
|
||||
"""
|
||||
Deduct credits for an operation (convenience method that calculates cost automatically).
|
||||
Deduct credits for an operation based on actual token usage.
|
||||
This is the ONLY way to deduct credits in the token-based system.
|
||||
|
||||
Args:
|
||||
account: Account instance
|
||||
operation_type: Type of operation
|
||||
amount: Optional amount (word count, image count, etc.)
|
||||
tokens_input: REQUIRED - Actual input tokens used
|
||||
tokens_output: REQUIRED - Actual output tokens used
|
||||
description: Optional description (auto-generated if not provided)
|
||||
metadata: Optional metadata dict
|
||||
cost_usd_input: Optional input cost in USD
|
||||
cost_usd_output: Optional output cost in USD
|
||||
cost_usd_total: Optional total cost in USD
|
||||
model_config: Optional AIModelConfig instance
|
||||
tokens_input: Optional input tokens
|
||||
tokens_output: Optional output tokens
|
||||
cost_usd: Optional cost in USD
|
||||
model_used: Optional AI model used
|
||||
related_object_type: Optional related object type
|
||||
related_object_id: Optional related object ID
|
||||
|
||||
Returns:
|
||||
int: New credit balance
|
||||
|
||||
Raises:
|
||||
ValueError: If tokens_input or tokens_output not provided
|
||||
"""
|
||||
# Calculate credit cost - use token-based if tokens provided
|
||||
if tokens_input is not None and tokens_output is not None and model_config:
|
||||
credits_required = CreditService.calculate_credits_from_tokens(
|
||||
operation_type, tokens_input, tokens_output, model_config
|
||||
# Validate token inputs
|
||||
if tokens_input is None or tokens_output is None:
|
||||
raise ValueError(
|
||||
f"tokens_input and tokens_output are REQUIRED for credit deduction. "
|
||||
f"Got: tokens_input={tokens_input}, tokens_output={tokens_output}"
|
||||
)
|
||||
else:
|
||||
credits_required = CreditService.get_credit_cost(operation_type, amount)
|
||||
|
||||
# Calculate credits from actual token usage
|
||||
credits_required = CreditService.calculate_credits_from_tokens(
|
||||
operation_type, tokens_input, tokens_output
|
||||
)
|
||||
|
||||
# Check sufficient credits
|
||||
CreditService.check_credits_legacy(account, credits_required)
|
||||
if account.credits < credits_required:
|
||||
raise InsufficientCreditsError(
|
||||
f"Insufficient credits. Required: {credits_required}, Available: {account.credits}"
|
||||
)
|
||||
|
||||
# Auto-generate description if not provided
|
||||
if not description:
|
||||
model_name = model_config.display_name if model_config else "AI"
|
||||
if operation_type == 'clustering':
|
||||
description = f"Clustering operation ({model_name})"
|
||||
elif operation_type == 'idea_generation':
|
||||
description = f"Generated {amount or 1} idea(s) ({model_name})"
|
||||
elif operation_type == 'content_generation':
|
||||
if tokens_input and tokens_output:
|
||||
description = f"Generated content ({tokens_input + tokens_output} tokens, {model_name})"
|
||||
else:
|
||||
description = f"Generated content ({amount or 0} words, {model_name})"
|
||||
elif operation_type == 'image_generation':
|
||||
description = f"Generated {amount or 1} image(s) ({model_name})"
|
||||
else:
|
||||
description = f"{operation_type} operation ({model_name})"
|
||||
total_tokens = tokens_input + tokens_output
|
||||
description = (
|
||||
f"{operation_type}: {total_tokens} tokens "
|
||||
f"({tokens_input} in, {tokens_output} out) = {credits_required} credits"
|
||||
)
|
||||
|
||||
return CreditService.deduct_credits(
|
||||
account=account,
|
||||
@@ -255,10 +284,8 @@ class CreditService:
|
||||
operation_type=operation_type,
|
||||
description=description,
|
||||
metadata=metadata,
|
||||
cost_usd_input=cost_usd_input,
|
||||
cost_usd_output=cost_usd_output,
|
||||
cost_usd_total=cost_usd_total,
|
||||
model_config=model_config,
|
||||
cost_usd=cost_usd,
|
||||
model_used=model_used,
|
||||
tokens_input=tokens_input,
|
||||
tokens_output=tokens_output,
|
||||
related_object_type=related_object_type,
|
||||
@@ -296,188 +323,4 @@ class CreditService:
|
||||
)
|
||||
|
||||
return account.credits
|
||||
|
||||
@staticmethod
|
||||
def calculate_credits_for_operation(operation_type, **kwargs):
|
||||
"""
|
||||
Calculate credits needed for an operation.
|
||||
Legacy method - use get_credit_cost() instead.
|
||||
|
||||
Args:
|
||||
operation_type: Type of operation
|
||||
**kwargs: Operation-specific parameters
|
||||
|
||||
Returns:
|
||||
int: Number of credits required
|
||||
|
||||
Raises:
|
||||
CreditCalculationError: If calculation fails
|
||||
"""
|
||||
# Map legacy operation types
|
||||
if operation_type == 'ideas':
|
||||
operation_type = 'idea_generation'
|
||||
elif operation_type == 'content':
|
||||
operation_type = 'content_generation'
|
||||
elif operation_type == 'images':
|
||||
operation_type = 'image_generation'
|
||||
|
||||
# Extract amount from kwargs
|
||||
amount = None
|
||||
if 'word_count' in kwargs:
|
||||
amount = kwargs.get('word_count')
|
||||
elif 'image_count' in kwargs:
|
||||
amount = kwargs.get('image_count')
|
||||
elif 'idea_count' in kwargs:
|
||||
amount = kwargs.get('idea_count')
|
||||
|
||||
return CreditService.get_credit_cost(operation_type, amount)
|
||||
|
||||
|
||||
@staticmethod
|
||||
def calculate_credits_from_tokens(operation_type, tokens_input, tokens_output, model_config):
|
||||
"""
|
||||
Calculate credits based on actual token usage and AI model configuration.
|
||||
This is the new token-aware calculation method.
|
||||
|
||||
Args:
|
||||
operation_type: Type of operation (e.g., 'content_generation')
|
||||
tokens_input: Number of input tokens used
|
||||
tokens_output: Number of output tokens used
|
||||
model_config: AIModelConfig instance
|
||||
|
||||
Returns:
|
||||
int: Number of credits to deduct
|
||||
|
||||
Raises:
|
||||
CreditCalculationError: If calculation fails
|
||||
"""
|
||||
import logging
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
try:
|
||||
from igny8_core.business.billing.models import CreditCostConfig
|
||||
|
||||
# Get operation config
|
||||
config = CreditCostConfig.objects.filter(
|
||||
operation_type=operation_type,
|
||||
is_active=True
|
||||
).first()
|
||||
|
||||
if not config:
|
||||
raise CreditCalculationError(f"No active config found for operation: {operation_type}")
|
||||
|
||||
# Check if operation uses token-based billing
|
||||
if config.unit in ['per_100_tokens', 'per_1000_tokens']:
|
||||
total_tokens = tokens_input + tokens_output
|
||||
|
||||
# Get model's tokens-per-credit ratio
|
||||
tokens_per_credit = model_config.tokens_per_credit
|
||||
|
||||
if tokens_per_credit <= 0:
|
||||
raise CreditCalculationError(f"Invalid tokens_per_credit: {tokens_per_credit}")
|
||||
|
||||
# Calculate credits (float)
|
||||
credits_float = Decimal(total_tokens) / Decimal(tokens_per_credit)
|
||||
|
||||
# Apply rounding (always round up to avoid undercharging)
|
||||
credits = math.ceil(credits_float)
|
||||
|
||||
# Apply minimum cost from config (if set)
|
||||
credits = max(credits, config.credits_cost)
|
||||
|
||||
logger.info(
|
||||
f"Token-based calculation: {total_tokens} tokens / {tokens_per_credit} = {credits} credits "
|
||||
f"(model: {model_config.model_name}, operation: {operation_type})"
|
||||
)
|
||||
|
||||
return credits
|
||||
else:
|
||||
# Fall back to legacy calculation for non-token operations
|
||||
logger.warning(
|
||||
f"Operation {operation_type} uses unit {config.unit}, falling back to legacy calculation"
|
||||
)
|
||||
return config.credits_cost
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"Failed to calculate credits from tokens: {e}")
|
||||
raise CreditCalculationError(f"Credit calculation failed: {e}")
|
||||
|
||||
@staticmethod
|
||||
def get_model_for_operation(account, operation_type, task_model_override=None):
|
||||
"""
|
||||
Determine which AI model to use for an operation.
|
||||
Priority: Task Override > Account Default > Operation Default > System Default
|
||||
|
||||
Args:
|
||||
account: Account instance
|
||||
operation_type: Type of operation
|
||||
task_model_override: Optional AIModelConfig instance from task
|
||||
|
||||
Returns:
|
||||
AIModelConfig: The model to use
|
||||
"""
|
||||
import logging
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
# 1. Task-level override (highest priority)
|
||||
if task_model_override:
|
||||
logger.info(f"Using task-level model override: {task_model_override.model_name}")
|
||||
return task_model_override
|
||||
|
||||
# 2. Account default model (from IntegrationSettings)
|
||||
try:
|
||||
from igny8_core.modules.system.models import IntegrationSettings
|
||||
from igny8_core.business.billing.models import CreditCostConfig
|
||||
|
||||
integration = IntegrationSettings.objects.filter(account=account).first()
|
||||
|
||||
if integration:
|
||||
# Determine if this is text or image operation
|
||||
config = CreditCostConfig.objects.filter(
|
||||
operation_type=operation_type,
|
||||
is_active=True
|
||||
).first()
|
||||
|
||||
if config and config.default_model:
|
||||
model_type = config.default_model.model_type
|
||||
|
||||
if model_type == 'text' and integration.default_text_model:
|
||||
logger.info(f"Using account default text model: {integration.default_text_model.model_name}")
|
||||
return integration.default_text_model
|
||||
elif model_type == 'image' and integration.default_image_model:
|
||||
logger.info(f"Using account default image model: {integration.default_image_model.model_name}")
|
||||
return integration.default_image_model
|
||||
except Exception as e:
|
||||
logger.warning(f"Failed to get account default model: {e}")
|
||||
|
||||
# 3. Operation default model
|
||||
try:
|
||||
from igny8_core.business.billing.models import CreditCostConfig
|
||||
|
||||
config = CreditCostConfig.objects.filter(
|
||||
operation_type=operation_type,
|
||||
is_active=True
|
||||
).first()
|
||||
|
||||
if config and config.default_model:
|
||||
logger.info(f"Using operation default model: {config.default_model.model_name}")
|
||||
return config.default_model
|
||||
except Exception as e:
|
||||
logger.warning(f"Failed to get operation default model: {e}")
|
||||
|
||||
# 4. System-wide default (fallback)
|
||||
try:
|
||||
default_model = AIModelConfig.objects.filter(
|
||||
is_default=True,
|
||||
is_active=True
|
||||
).first()
|
||||
|
||||
if default_model:
|
||||
logger.info(f"Using system default model: {default_model.model_name}")
|
||||
return default_model
|
||||
except Exception as e:
|
||||
logger.warning(f"Failed to get system default model: {e}")
|
||||
|
||||
# 5. Hard-coded fallback
|
||||
logger.warning("All model selection failed, using hard-coded fallback: gpt-4o-mini")
|
||||
return AIModelConfig.objects.filter(model_name='gpt-4o-mini').first()
|
||||
|
||||
@@ -13,6 +13,7 @@ from igny8_core.modules.billing.views import (
|
||||
CreditBalanceViewSet,
|
||||
CreditUsageViewSet,
|
||||
CreditTransactionViewSet,
|
||||
AIModelConfigViewSet,
|
||||
)
|
||||
|
||||
router = DefaultRouter()
|
||||
@@ -21,6 +22,8 @@ router.register(r'admin', BillingViewSet, basename='billing-admin')
|
||||
router.register(r'credits/balance', CreditBalanceViewSet, basename='credit-balance')
|
||||
router.register(r'credits/usage', CreditUsageViewSet, basename='credit-usage')
|
||||
router.register(r'credits/transactions', CreditTransactionViewSet, basename='credit-transactions')
|
||||
# AI Models endpoint
|
||||
router.register(r'ai/models', AIModelConfigViewSet, basename='ai-models')
|
||||
# User-facing billing endpoints
|
||||
router.register(r'invoices', InvoiceViewSet, basename='invoices')
|
||||
router.register(r'payments', PaymentViewSet, basename='payments')
|
||||
|
||||
@@ -8,16 +8,17 @@ from unfold.admin import ModelAdmin
|
||||
from simple_history.admin import SimpleHistoryAdmin
|
||||
from igny8_core.admin.base import AccountAdminMixin, Igny8ModelAdmin
|
||||
from igny8_core.business.billing.models import (
|
||||
AIModelConfig,
|
||||
CreditCostConfig,
|
||||
BillingConfiguration,
|
||||
Invoice,
|
||||
Payment,
|
||||
CreditPackage,
|
||||
PaymentMethodConfig,
|
||||
PlanLimitUsage,
|
||||
AIModelConfig,
|
||||
)
|
||||
from .models import CreditTransaction, CreditUsageLog, AccountPaymentMethod
|
||||
from import_export.admin import ExportMixin
|
||||
from import_export.admin import ExportMixin, ImportExportMixin
|
||||
from import_export import resources
|
||||
from rangefilter.filters import DateRangeFilter
|
||||
|
||||
@@ -50,43 +51,21 @@ class CreditTransactionAdmin(ExportMixin, AccountAdminMixin, Igny8ModelAdmin):
|
||||
get_account_display.short_description = 'Account'
|
||||
|
||||
|
||||
@admin.register(AIModelConfig)
|
||||
class AIModelConfigAdmin(Igny8ModelAdmin):
|
||||
list_display = ['display_name', 'model_name', 'provider', 'model_type', 'tokens_per_credit', 'cost_per_1k_input_tokens', 'cost_per_1k_output_tokens', 'is_active', 'is_default']
|
||||
list_filter = ['provider', 'model_type', 'is_active', 'is_default']
|
||||
search_fields = ['model_name', 'display_name', 'description']
|
||||
readonly_fields = ['created_at', 'updated_at']
|
||||
fieldsets = (
|
||||
('Model Information', {
|
||||
'fields': ('model_name', 'display_name', 'description', 'provider', 'model_type')
|
||||
}),
|
||||
('Pricing', {
|
||||
'fields': ('cost_per_1k_input_tokens', 'cost_per_1k_output_tokens', 'tokens_per_credit')
|
||||
}),
|
||||
('Status', {
|
||||
'fields': ('is_active', 'is_default')
|
||||
}),
|
||||
('Timestamps', {
|
||||
'fields': ('created_at', 'updated_at'),
|
||||
'classes': ('collapse',)
|
||||
}),
|
||||
)
|
||||
|
||||
def save_model(self, request, obj, form, change):
|
||||
# If setting as default, unset other defaults of same type
|
||||
if obj.is_default:
|
||||
AIModelConfig.objects.filter(
|
||||
model_type=obj.model_type,
|
||||
is_default=True
|
||||
).exclude(pk=obj.pk).update(is_default=False)
|
||||
super().save_model(request, obj, form, change)
|
||||
class CreditUsageLogResource(resources.ModelResource):
|
||||
"""Resource class for exporting Credit Usage Logs"""
|
||||
class Meta:
|
||||
model = CreditUsageLog
|
||||
fields = ('id', 'account__name', 'operation_type', 'credits_used', 'cost_usd',
|
||||
'model_used', 'created_at')
|
||||
export_order = fields
|
||||
|
||||
|
||||
@admin.register(CreditUsageLog)
|
||||
class CreditUsageLogAdmin(AccountAdminMixin, Igny8ModelAdmin):
|
||||
list_display = ['id', 'account', 'operation_type', 'credits_used', 'cost_usd', 'model_config', 'created_at']
|
||||
list_filter = ['operation_type', 'created_at', 'account', 'model_config']
|
||||
search_fields = ['account__name', 'model_name']
|
||||
class CreditUsageLogAdmin(ExportMixin, AccountAdminMixin, Igny8ModelAdmin):
|
||||
resource_class = CreditUsageLogResource
|
||||
list_display = ['id', 'account', 'operation_type', 'credits_used', 'cost_usd', 'model_used', 'created_at']
|
||||
list_filter = ['operation_type', 'created_at', 'account', 'model_used']
|
||||
search_fields = ['account__name', 'model_used']
|
||||
readonly_fields = ['created_at']
|
||||
date_hierarchy = 'created_at'
|
||||
|
||||
@@ -100,8 +79,18 @@ class CreditUsageLogAdmin(AccountAdminMixin, Igny8ModelAdmin):
|
||||
get_account_display.short_description = 'Account'
|
||||
|
||||
|
||||
class InvoiceResource(resources.ModelResource):
|
||||
"""Resource class for exporting Invoices"""
|
||||
class Meta:
|
||||
model = Invoice
|
||||
fields = ('id', 'invoice_number', 'account__name', 'status', 'total', 'currency',
|
||||
'invoice_date', 'due_date', 'created_at', 'updated_at')
|
||||
export_order = fields
|
||||
|
||||
|
||||
@admin.register(Invoice)
|
||||
class InvoiceAdmin(AccountAdminMixin, Igny8ModelAdmin):
|
||||
class InvoiceAdmin(ExportMixin, AccountAdminMixin, Igny8ModelAdmin):
|
||||
resource_class = InvoiceResource
|
||||
list_display = [
|
||||
'invoice_number',
|
||||
'account',
|
||||
@@ -114,6 +103,56 @@ class InvoiceAdmin(AccountAdminMixin, Igny8ModelAdmin):
|
||||
list_filter = ['status', 'currency', 'invoice_date', 'account']
|
||||
search_fields = ['invoice_number', 'account__name']
|
||||
readonly_fields = ['created_at', 'updated_at']
|
||||
actions = [
|
||||
'bulk_set_status_draft',
|
||||
'bulk_set_status_sent',
|
||||
'bulk_set_status_paid',
|
||||
'bulk_set_status_overdue',
|
||||
'bulk_set_status_cancelled',
|
||||
'bulk_send_reminders',
|
||||
]
|
||||
|
||||
def bulk_set_status_draft(self, request, queryset):
|
||||
"""Set selected invoices to draft status"""
|
||||
updated = queryset.update(status='draft')
|
||||
self.message_user(request, f'{updated} invoice(s) set to draft.', messages.SUCCESS)
|
||||
bulk_set_status_draft.short_description = 'Set status to Draft'
|
||||
|
||||
def bulk_set_status_sent(self, request, queryset):
|
||||
"""Set selected invoices to sent status"""
|
||||
updated = queryset.update(status='sent')
|
||||
self.message_user(request, f'{updated} invoice(s) set to sent.', messages.SUCCESS)
|
||||
bulk_set_status_sent.short_description = 'Set status to Sent'
|
||||
|
||||
def bulk_set_status_paid(self, request, queryset):
|
||||
"""Set selected invoices to paid status"""
|
||||
updated = queryset.update(status='paid')
|
||||
self.message_user(request, f'{updated} invoice(s) set to paid.', messages.SUCCESS)
|
||||
bulk_set_status_paid.short_description = 'Set status to Paid'
|
||||
|
||||
def bulk_set_status_overdue(self, request, queryset):
|
||||
"""Set selected invoices to overdue status"""
|
||||
updated = queryset.update(status='overdue')
|
||||
self.message_user(request, f'{updated} invoice(s) set to overdue.', messages.SUCCESS)
|
||||
bulk_set_status_overdue.short_description = 'Set status to Overdue'
|
||||
|
||||
def bulk_set_status_cancelled(self, request, queryset):
|
||||
"""Set selected invoices to cancelled status"""
|
||||
updated = queryset.update(status='cancelled')
|
||||
self.message_user(request, f'{updated} invoice(s) set to cancelled.', messages.SUCCESS)
|
||||
bulk_set_status_cancelled.short_description = 'Set status to Cancelled'
|
||||
|
||||
def bulk_send_reminders(self, request, queryset):
|
||||
"""Send reminder emails for selected invoices"""
|
||||
# TODO: Implement email sending logic when email service is configured
|
||||
unpaid = queryset.filter(status__in=['sent', 'overdue'])
|
||||
count = unpaid.count()
|
||||
self.message_user(
|
||||
request,
|
||||
f'{count} invoice reminder(s) queued for sending. (Email integration required)',
|
||||
messages.INFO
|
||||
)
|
||||
bulk_send_reminders.short_description = 'Send payment reminders'
|
||||
|
||||
|
||||
class PaymentResource(resources.ModelResource):
|
||||
@@ -160,7 +199,7 @@ class PaymentAdmin(ExportMixin, AccountAdminMixin, SimpleHistoryAdmin, Igny8Mode
|
||||
'manual_notes'
|
||||
]
|
||||
readonly_fields = ['created_at', 'updated_at', 'approved_at', 'processed_at', 'failed_at', 'refunded_at']
|
||||
actions = ['approve_payments', 'reject_payments']
|
||||
actions = ['approve_payments', 'reject_payments', 'bulk_refund']
|
||||
|
||||
fieldsets = (
|
||||
('Payment Info', {
|
||||
@@ -406,14 +445,71 @@ class PaymentAdmin(ExportMixin, AccountAdminMixin, SimpleHistoryAdmin, Igny8Mode
|
||||
self.message_user(request, f'Rejected {count} payment(s)')
|
||||
|
||||
reject_payments.short_description = 'Reject selected manual payments'
|
||||
|
||||
def bulk_refund(self, request, queryset):
|
||||
"""Refund selected payments"""
|
||||
from django.utils import timezone
|
||||
|
||||
# Only refund succeeded payments
|
||||
succeeded_payments = queryset.filter(status='succeeded')
|
||||
count = 0
|
||||
|
||||
for payment in succeeded_payments:
|
||||
# Mark as refunded
|
||||
payment.status = 'refunded'
|
||||
payment.refunded_at = timezone.now()
|
||||
payment.admin_notes = f'{payment.admin_notes or ""}\nBulk refunded by {request.user.email} on {timezone.now()}'
|
||||
payment.save()
|
||||
|
||||
# TODO: Process actual refund through payment gateway (Stripe/PayPal)
|
||||
# For now, just marking as refunded in database
|
||||
|
||||
count += 1
|
||||
|
||||
self.message_user(
|
||||
request,
|
||||
f'{count} payment(s) marked as refunded. Note: Actual gateway refunds need to be processed separately.',
|
||||
messages.WARNING
|
||||
)
|
||||
bulk_refund.short_description = 'Refund selected payments'
|
||||
|
||||
|
||||
class CreditPackageResource(resources.ModelResource):
|
||||
"""Resource class for importing/exporting Credit Packages"""
|
||||
class Meta:
|
||||
model = CreditPackage
|
||||
fields = ('id', 'name', 'slug', 'credits', 'price', 'discount_percentage',
|
||||
'is_active', 'is_featured', 'sort_order', 'created_at')
|
||||
export_order = fields
|
||||
import_id_fields = ('id',)
|
||||
skip_unchanged = True
|
||||
|
||||
|
||||
@admin.register(CreditPackage)
|
||||
class CreditPackageAdmin(Igny8ModelAdmin):
|
||||
class CreditPackageAdmin(ImportExportMixin, Igny8ModelAdmin):
|
||||
resource_class = CreditPackageResource
|
||||
list_display = ['name', 'slug', 'credits', 'price', 'discount_percentage', 'is_active', 'is_featured', 'sort_order']
|
||||
list_filter = ['is_active', 'is_featured']
|
||||
search_fields = ['name', 'slug']
|
||||
readonly_fields = ['created_at', 'updated_at']
|
||||
actions = [
|
||||
'bulk_activate',
|
||||
'bulk_deactivate',
|
||||
]
|
||||
actions = [
|
||||
'bulk_activate',
|
||||
'bulk_deactivate',
|
||||
]
|
||||
|
||||
def bulk_activate(self, request, queryset):
|
||||
updated = queryset.update(is_active=True)
|
||||
self.message_user(request, f'{updated} credit package(s) activated.', messages.SUCCESS)
|
||||
bulk_activate.short_description = 'Activate selected packages'
|
||||
|
||||
def bulk_deactivate(self, request, queryset):
|
||||
updated = queryset.update(is_active=False)
|
||||
self.message_user(request, f'{updated} credit package(s) deactivated.', messages.SUCCESS)
|
||||
bulk_deactivate.short_description = 'Deactivate selected packages'
|
||||
|
||||
|
||||
@admin.register(PaymentMethodConfig)
|
||||
@@ -459,55 +555,57 @@ class CreditCostConfigAdmin(SimpleHistoryAdmin, Igny8ModelAdmin):
|
||||
list_display = [
|
||||
'operation_type',
|
||||
'display_name',
|
||||
'credits_cost_display',
|
||||
'unit',
|
||||
'tokens_per_credit_display',
|
||||
'price_per_credit_usd',
|
||||
'min_credits',
|
||||
'is_active',
|
||||
'cost_change_indicator',
|
||||
'updated_at',
|
||||
'updated_by'
|
||||
]
|
||||
|
||||
list_filter = ['is_active', 'unit', 'updated_at']
|
||||
list_filter = ['is_active', 'updated_at']
|
||||
search_fields = ['operation_type', 'display_name', 'description']
|
||||
|
||||
fieldsets = (
|
||||
('Operation', {
|
||||
'fields': ('operation_type', 'display_name', 'description')
|
||||
}),
|
||||
('Cost Configuration', {
|
||||
'fields': ('credits_cost', 'unit', 'is_active')
|
||||
('Token-to-Credit Configuration', {
|
||||
'fields': ('tokens_per_credit', 'min_credits', 'price_per_credit_usd', 'is_active'),
|
||||
'description': 'Configure how tokens are converted to credits for this operation'
|
||||
}),
|
||||
('Audit Trail', {
|
||||
'fields': ('previous_cost', 'updated_by', 'created_at', 'updated_at'),
|
||||
'fields': ('previous_tokens_per_credit', 'updated_by', 'created_at', 'updated_at'),
|
||||
'classes': ('collapse',)
|
||||
}),
|
||||
)
|
||||
|
||||
readonly_fields = ['created_at', 'updated_at', 'previous_cost']
|
||||
readonly_fields = ['created_at', 'updated_at', 'previous_tokens_per_credit']
|
||||
|
||||
def credits_cost_display(self, obj):
|
||||
"""Show cost with color coding"""
|
||||
if obj.credits_cost >= 20:
|
||||
color = 'red'
|
||||
elif obj.credits_cost >= 10:
|
||||
def tokens_per_credit_display(self, obj):
|
||||
"""Show token ratio with color coding"""
|
||||
if obj.tokens_per_credit <= 50:
|
||||
color = 'red' # Expensive (low tokens per credit)
|
||||
elif obj.tokens_per_credit <= 100:
|
||||
color = 'orange'
|
||||
else:
|
||||
color = 'green'
|
||||
color = 'green' # Cheap (high tokens per credit)
|
||||
return format_html(
|
||||
'<span style="color: {}; font-weight: bold;">{} credits</span>',
|
||||
'<span style="color: {}; font-weight: bold;">{} tokens/credit</span>',
|
||||
color,
|
||||
obj.credits_cost
|
||||
obj.tokens_per_credit
|
||||
)
|
||||
credits_cost_display.short_description = 'Cost'
|
||||
tokens_per_credit_display.short_description = 'Token Ratio'
|
||||
|
||||
def cost_change_indicator(self, obj):
|
||||
"""Show if cost changed recently"""
|
||||
if obj.previous_cost is not None:
|
||||
if obj.credits_cost > obj.previous_cost:
|
||||
icon = '📈' # Increased
|
||||
"""Show if token ratio changed recently"""
|
||||
if obj.previous_tokens_per_credit is not None:
|
||||
if obj.tokens_per_credit < obj.previous_tokens_per_credit:
|
||||
icon = '📈' # More expensive (fewer tokens per credit)
|
||||
color = 'red'
|
||||
elif obj.credits_cost < obj.previous_cost:
|
||||
icon = '📉' # Decreased
|
||||
elif obj.tokens_per_credit > obj.previous_tokens_per_credit:
|
||||
icon = '📉' # Cheaper (more tokens per credit)
|
||||
color = 'green'
|
||||
else:
|
||||
icon = '➡️' # Same
|
||||
@@ -517,8 +615,8 @@ class CreditCostConfigAdmin(SimpleHistoryAdmin, Igny8ModelAdmin):
|
||||
'{} <span style="color: {};">({} → {})</span>',
|
||||
icon,
|
||||
color,
|
||||
obj.previous_cost,
|
||||
obj.credits_cost
|
||||
obj.previous_tokens_per_credit,
|
||||
obj.tokens_per_credit
|
||||
)
|
||||
return '—'
|
||||
cost_change_indicator.short_description = 'Recent Change'
|
||||
@@ -529,8 +627,18 @@ class CreditCostConfigAdmin(SimpleHistoryAdmin, Igny8ModelAdmin):
|
||||
super().save_model(request, obj, form, change)
|
||||
|
||||
|
||||
class PlanLimitUsageResource(resources.ModelResource):
|
||||
"""Resource class for exporting Plan Limit Usage"""
|
||||
class Meta:
|
||||
model = PlanLimitUsage
|
||||
fields = ('id', 'account__name', 'limit_type', 'amount_used',
|
||||
'period_start', 'period_end', 'created_at')
|
||||
export_order = fields
|
||||
|
||||
|
||||
@admin.register(PlanLimitUsage)
|
||||
class PlanLimitUsageAdmin(AccountAdminMixin, Igny8ModelAdmin):
|
||||
class PlanLimitUsageAdmin(ExportMixin, AccountAdminMixin, Igny8ModelAdmin):
|
||||
resource_class = PlanLimitUsageResource
|
||||
"""Admin for tracking plan limit usage across billing periods"""
|
||||
list_display = [
|
||||
'account',
|
||||
@@ -548,6 +656,10 @@ class PlanLimitUsageAdmin(AccountAdminMixin, Igny8ModelAdmin):
|
||||
search_fields = ['account__name']
|
||||
readonly_fields = ['created_at', 'updated_at']
|
||||
date_hierarchy = 'period_start'
|
||||
actions = [
|
||||
'bulk_reset_usage',
|
||||
'bulk_delete_old_records',
|
||||
]
|
||||
|
||||
fieldsets = (
|
||||
('Usage Info', {
|
||||
@@ -570,4 +682,272 @@ class PlanLimitUsageAdmin(AccountAdminMixin, Igny8ModelAdmin):
|
||||
"""Display billing period range"""
|
||||
return f"{obj.period_start} to {obj.period_end}"
|
||||
period_display.short_description = 'Billing Period'
|
||||
|
||||
def bulk_reset_usage(self, request, queryset):
|
||||
"""Reset usage counters to zero"""
|
||||
updated = queryset.update(amount_used=0)
|
||||
self.message_user(request, f'{updated} usage counter(s) reset to zero.', messages.SUCCESS)
|
||||
bulk_reset_usage.short_description = 'Reset usage counters'
|
||||
|
||||
def bulk_delete_old_records(self, request, queryset):
|
||||
"""Delete usage records older than 1 year"""
|
||||
from django.utils import timezone
|
||||
from datetime import timedelta
|
||||
|
||||
cutoff_date = timezone.now() - timedelta(days=365)
|
||||
old_records = queryset.filter(period_end__lt=cutoff_date)
|
||||
count = old_records.count()
|
||||
old_records.delete()
|
||||
self.message_user(request, f'{count} old usage record(s) deleted (older than 1 year).', messages.SUCCESS)
|
||||
bulk_delete_old_records.short_description = 'Delete old records (>1 year)'
|
||||
|
||||
|
||||
@admin.register(BillingConfiguration)
|
||||
class BillingConfigurationAdmin(Igny8ModelAdmin):
|
||||
"""Admin for global billing configuration (Singleton)"""
|
||||
list_display = [
|
||||
'id',
|
||||
'default_tokens_per_credit',
|
||||
'default_credit_price_usd',
|
||||
'credit_rounding_mode',
|
||||
'enable_token_based_reporting',
|
||||
'updated_at',
|
||||
'updated_by'
|
||||
]
|
||||
|
||||
fieldsets = (
|
||||
('Global Token-to-Credit Settings', {
|
||||
'fields': ('default_tokens_per_credit', 'default_credit_price_usd', 'credit_rounding_mode'),
|
||||
'description': 'These settings apply when no operation-specific config exists'
|
||||
}),
|
||||
('Reporting Settings', {
|
||||
'fields': ('enable_token_based_reporting',),
|
||||
'description': 'Control token-based reporting features'
|
||||
}),
|
||||
('Audit Trail', {
|
||||
'fields': ('updated_by', 'updated_at'),
|
||||
'classes': ('collapse',)
|
||||
}),
|
||||
)
|
||||
|
||||
readonly_fields = ['updated_at']
|
||||
|
||||
def has_add_permission(self, request):
|
||||
"""Only allow one instance (singleton)"""
|
||||
from igny8_core.business.billing.models import BillingConfiguration
|
||||
return not BillingConfiguration.objects.exists()
|
||||
|
||||
def has_delete_permission(self, request, obj=None):
|
||||
"""Prevent deletion of the singleton"""
|
||||
return False
|
||||
|
||||
def save_model(self, request, obj, form, change):
|
||||
"""Track who made the change"""
|
||||
obj.updated_by = request.user
|
||||
super().save_model(request, obj, form, change)
|
||||
|
||||
|
||||
@admin.register(AIModelConfig)
|
||||
class AIModelConfigAdmin(SimpleHistoryAdmin, Igny8ModelAdmin):
|
||||
"""
|
||||
Admin for AI Model Configuration - Database-driven model pricing
|
||||
Replaces hardcoded MODEL_RATES and IMAGE_MODEL_RATES
|
||||
"""
|
||||
list_display = [
|
||||
'model_name',
|
||||
'display_name_short',
|
||||
'model_type_badge',
|
||||
'provider_badge',
|
||||
'pricing_display',
|
||||
'is_active_icon',
|
||||
'is_default_icon',
|
||||
'sort_order',
|
||||
'updated_at',
|
||||
]
|
||||
|
||||
list_filter = [
|
||||
'model_type',
|
||||
'provider',
|
||||
'is_active',
|
||||
'is_default',
|
||||
'supports_json_mode',
|
||||
'supports_vision',
|
||||
'supports_function_calling',
|
||||
]
|
||||
|
||||
search_fields = ['model_name', 'display_name', 'description']
|
||||
|
||||
ordering = ['model_type', 'sort_order', 'model_name']
|
||||
|
||||
readonly_fields = ['created_at', 'updated_at', 'updated_by']
|
||||
|
||||
fieldsets = (
|
||||
('Basic Information', {
|
||||
'fields': ('model_name', 'display_name', 'model_type', 'provider', 'description'),
|
||||
'description': 'Core model identification and classification'
|
||||
}),
|
||||
('Text Model Pricing', {
|
||||
'fields': ('input_cost_per_1m', 'output_cost_per_1m', 'context_window', 'max_output_tokens'),
|
||||
'description': 'Pricing and limits for TEXT models only (leave blank for image models)',
|
||||
'classes': ('collapse',)
|
||||
}),
|
||||
('Image Model Pricing', {
|
||||
'fields': ('cost_per_image', 'valid_sizes'),
|
||||
'description': 'Pricing and configuration for IMAGE models only (leave blank for text models)',
|
||||
'classes': ('collapse',)
|
||||
}),
|
||||
('Capabilities', {
|
||||
'fields': ('supports_json_mode', 'supports_vision', 'supports_function_calling'),
|
||||
'description': 'Model features and capabilities'
|
||||
}),
|
||||
('Status & Display', {
|
||||
'fields': ('is_active', 'is_default', 'sort_order'),
|
||||
'description': 'Control model availability and ordering in dropdowns'
|
||||
}),
|
||||
('Lifecycle', {
|
||||
'fields': ('release_date', 'deprecation_date'),
|
||||
'description': 'Model release and deprecation dates',
|
||||
'classes': ('collapse',)
|
||||
}),
|
||||
('Audit Trail', {
|
||||
'fields': ('created_at', 'updated_at', 'updated_by'),
|
||||
'classes': ('collapse',)
|
||||
}),
|
||||
)
|
||||
|
||||
# Custom display methods
|
||||
def display_name_short(self, obj):
|
||||
"""Truncated display name for list view"""
|
||||
if len(obj.display_name) > 50:
|
||||
return obj.display_name[:47] + '...'
|
||||
return obj.display_name
|
||||
display_name_short.short_description = 'Display Name'
|
||||
|
||||
def model_type_badge(self, obj):
|
||||
"""Colored badge for model type"""
|
||||
colors = {
|
||||
'text': '#3498db', # Blue
|
||||
'image': '#e74c3c', # Red
|
||||
'embedding': '#2ecc71', # Green
|
||||
}
|
||||
color = colors.get(obj.model_type, '#95a5a6')
|
||||
return format_html(
|
||||
'<span style="background-color: {}; color: white; padding: 3px 10px; '
|
||||
'border-radius: 3px; font-weight: bold;">{}</span>',
|
||||
color,
|
||||
obj.get_model_type_display()
|
||||
)
|
||||
model_type_badge.short_description = 'Type'
|
||||
|
||||
def provider_badge(self, obj):
|
||||
"""Colored badge for provider"""
|
||||
colors = {
|
||||
'openai': '#10a37f', # OpenAI green
|
||||
'anthropic': '#d97757', # Anthropic orange
|
||||
'runware': '#6366f1', # Purple
|
||||
'google': '#4285f4', # Google blue
|
||||
}
|
||||
color = colors.get(obj.provider, '#95a5a6')
|
||||
return format_html(
|
||||
'<span style="background-color: {}; color: white; padding: 3px 10px; '
|
||||
'border-radius: 3px; font-weight: bold;">{}</span>',
|
||||
color,
|
||||
obj.get_provider_display()
|
||||
)
|
||||
provider_badge.short_description = 'Provider'
|
||||
|
||||
def pricing_display(self, obj):
|
||||
"""Format pricing based on model type"""
|
||||
if obj.model_type == 'text':
|
||||
return format_html(
|
||||
'<span style="color: #2c3e50; font-family: monospace;">'
|
||||
'${} / ${} per 1M</span>',
|
||||
obj.input_cost_per_1m,
|
||||
obj.output_cost_per_1m
|
||||
)
|
||||
elif obj.model_type == 'image':
|
||||
return format_html(
|
||||
'<span style="color: #2c3e50; font-family: monospace;">'
|
||||
'${} per image</span>',
|
||||
obj.cost_per_image
|
||||
)
|
||||
return '-'
|
||||
pricing_display.short_description = 'Pricing'
|
||||
|
||||
def is_active_icon(self, obj):
|
||||
"""Active status icon"""
|
||||
if obj.is_active:
|
||||
return format_html(
|
||||
'<span style="color: green; font-size: 18px;" title="Active">●</span>'
|
||||
)
|
||||
return format_html(
|
||||
'<span style="color: red; font-size: 18px;" title="Inactive">●</span>'
|
||||
)
|
||||
is_active_icon.short_description = 'Active'
|
||||
|
||||
def is_default_icon(self, obj):
|
||||
"""Default status icon"""
|
||||
if obj.is_default:
|
||||
return format_html(
|
||||
'<span style="color: gold; font-size: 18px;" title="Default">★</span>'
|
||||
)
|
||||
return format_html(
|
||||
'<span style="color: #ddd; font-size: 18px;" title="Not Default">☆</span>'
|
||||
)
|
||||
is_default_icon.short_description = 'Default'
|
||||
|
||||
# Admin actions
|
||||
actions = ['bulk_activate', 'bulk_deactivate', 'set_as_default']
|
||||
|
||||
def bulk_activate(self, request, queryset):
|
||||
"""Enable selected models"""
|
||||
count = queryset.update(is_active=True)
|
||||
self.message_user(
|
||||
request,
|
||||
f'{count} model(s) activated successfully.',
|
||||
messages.SUCCESS
|
||||
)
|
||||
bulk_activate.short_description = 'Activate selected models'
|
||||
|
||||
def bulk_deactivate(self, request, queryset):
|
||||
"""Disable selected models"""
|
||||
count = queryset.update(is_active=False)
|
||||
self.message_user(
|
||||
request,
|
||||
f'{count} model(s) deactivated successfully.',
|
||||
messages.WARNING
|
||||
)
|
||||
bulk_deactivate.short_description = 'Deactivate selected models'
|
||||
|
||||
def set_as_default(self, request, queryset):
|
||||
"""Set one model as default for its type"""
|
||||
if queryset.count() != 1:
|
||||
self.message_user(
|
||||
request,
|
||||
'Please select exactly one model to set as default.',
|
||||
messages.ERROR
|
||||
)
|
||||
return
|
||||
|
||||
model = queryset.first()
|
||||
# Unset other defaults for same type
|
||||
AIModelConfig.objects.filter(
|
||||
model_type=model.model_type,
|
||||
is_default=True
|
||||
).exclude(pk=model.pk).update(is_default=False)
|
||||
|
||||
# Set this as default
|
||||
model.is_default = True
|
||||
model.save()
|
||||
|
||||
self.message_user(
|
||||
request,
|
||||
f'{model.model_name} is now the default {model.get_model_type_display()} model.',
|
||||
messages.SUCCESS
|
||||
)
|
||||
set_as_default.short_description = 'Set as default model (for its type)'
|
||||
|
||||
def save_model(self, request, obj, form, change):
|
||||
"""Track who made the change"""
|
||||
obj.updated_by = request.user
|
||||
super().save_model(request, obj, form, change)
|
||||
|
||||
@@ -0,0 +1,264 @@
|
||||
# Generated by Django 5.2.9 on 2025-12-24 01:20
|
||||
|
||||
import django.core.validators
|
||||
import django.db.models.deletion
|
||||
import simple_history.models
|
||||
from decimal import Decimal
|
||||
from django.conf import settings
|
||||
from django.db import migrations, models
|
||||
|
||||
|
||||
def seed_ai_models(apps, schema_editor):
|
||||
"""Seed AIModelConfig with data from constants.py"""
|
||||
AIModelConfig = apps.get_model('billing', 'AIModelConfig')
|
||||
|
||||
# Text Models (from MODEL_RATES in constants.py)
|
||||
text_models = [
|
||||
{
|
||||
'model_name': 'gpt-4o-mini',
|
||||
'display_name': 'GPT-4o mini - Fast & Affordable',
|
||||
'model_type': 'text',
|
||||
'provider': 'openai',
|
||||
'input_cost_per_1m': Decimal('0.1500'),
|
||||
'output_cost_per_1m': Decimal('0.6000'),
|
||||
'context_window': 128000,
|
||||
'max_output_tokens': 16000,
|
||||
'supports_json_mode': True,
|
||||
'supports_vision': False,
|
||||
'supports_function_calling': True,
|
||||
'is_active': True,
|
||||
'is_default': True, # Default text model
|
||||
'sort_order': 1,
|
||||
'description': 'Fast and cost-effective model for most tasks. Best balance of speed and quality.',
|
||||
},
|
||||
{
|
||||
'model_name': 'gpt-4.1',
|
||||
'display_name': 'GPT-4.1 - Legacy Model',
|
||||
'model_type': 'text',
|
||||
'provider': 'openai',
|
||||
'input_cost_per_1m': Decimal('2.0000'),
|
||||
'output_cost_per_1m': Decimal('8.0000'),
|
||||
'context_window': 8192,
|
||||
'max_output_tokens': 4096,
|
||||
'supports_json_mode': False,
|
||||
'supports_vision': False,
|
||||
'supports_function_calling': False,
|
||||
'is_active': True,
|
||||
'is_default': False,
|
||||
'sort_order': 10,
|
||||
'description': 'Legacy GPT-4 model. Higher cost but reliable.',
|
||||
},
|
||||
{
|
||||
'model_name': 'gpt-4o',
|
||||
'display_name': 'GPT-4o - High Quality with Vision',
|
||||
'model_type': 'text',
|
||||
'provider': 'openai',
|
||||
'input_cost_per_1m': Decimal('2.5000'),
|
||||
'output_cost_per_1m': Decimal('10.0000'),
|
||||
'context_window': 128000,
|
||||
'max_output_tokens': 4096,
|
||||
'supports_json_mode': True,
|
||||
'supports_vision': True,
|
||||
'supports_function_calling': True,
|
||||
'is_active': True,
|
||||
'is_default': False,
|
||||
'sort_order': 5,
|
||||
'description': 'Most capable GPT-4 variant with vision capabilities. Best for complex tasks.',
|
||||
},
|
||||
{
|
||||
'model_name': 'gpt-5.1',
|
||||
'display_name': 'GPT-5.1 - Advanced (16K context)',
|
||||
'model_type': 'text',
|
||||
'provider': 'openai',
|
||||
'input_cost_per_1m': Decimal('1.2500'),
|
||||
'output_cost_per_1m': Decimal('10.0000'),
|
||||
'context_window': 16000,
|
||||
'max_output_tokens': 16000,
|
||||
'supports_json_mode': True,
|
||||
'supports_vision': False,
|
||||
'supports_function_calling': True,
|
||||
'is_active': True,
|
||||
'is_default': False,
|
||||
'sort_order': 20,
|
||||
'description': 'Advanced GPT-5 model with 16K context window.',
|
||||
},
|
||||
{
|
||||
'model_name': 'gpt-5.2',
|
||||
'display_name': 'GPT-5.2 - Most Advanced (16K context)',
|
||||
'model_type': 'text',
|
||||
'provider': 'openai',
|
||||
'input_cost_per_1m': Decimal('1.7500'),
|
||||
'output_cost_per_1m': Decimal('14.0000'),
|
||||
'context_window': 16000,
|
||||
'max_output_tokens': 16000,
|
||||
'supports_json_mode': True,
|
||||
'supports_vision': False,
|
||||
'supports_function_calling': True,
|
||||
'is_active': True,
|
||||
'is_default': False,
|
||||
'sort_order': 30,
|
||||
'description': 'Most advanced GPT-5 variant. Highest quality output.',
|
||||
},
|
||||
]
|
||||
|
||||
# Image Models (from IMAGE_MODEL_RATES in constants.py)
|
||||
image_models = [
|
||||
{
|
||||
'model_name': 'dall-e-3',
|
||||
'display_name': 'DALL-E 3 - High Quality Images',
|
||||
'model_type': 'image',
|
||||
'provider': 'openai',
|
||||
'cost_per_image': Decimal('0.0400'),
|
||||
'valid_sizes': ['1024x1024', '1024x1792', '1792x1024'],
|
||||
'supports_json_mode': False,
|
||||
'supports_vision': False,
|
||||
'supports_function_calling': False,
|
||||
'is_active': True,
|
||||
'is_default': True, # Default image model
|
||||
'sort_order': 1,
|
||||
'description': 'Latest DALL-E model with best quality and prompt adherence.',
|
||||
},
|
||||
{
|
||||
'model_name': 'dall-e-2',
|
||||
'display_name': 'DALL-E 2 - Standard Quality',
|
||||
'model_type': 'image',
|
||||
'provider': 'openai',
|
||||
'cost_per_image': Decimal('0.0200'),
|
||||
'valid_sizes': ['256x256', '512x512', '1024x1024'],
|
||||
'supports_json_mode': False,
|
||||
'supports_vision': False,
|
||||
'supports_function_calling': False,
|
||||
'is_active': True,
|
||||
'is_default': False,
|
||||
'sort_order': 10,
|
||||
'description': 'Cost-effective image generation with good quality.',
|
||||
},
|
||||
{
|
||||
'model_name': 'gpt-image-1',
|
||||
'display_name': 'GPT Image 1 (Not compatible with OpenAI)',
|
||||
'model_type': 'image',
|
||||
'provider': 'openai',
|
||||
'cost_per_image': Decimal('0.0420'),
|
||||
'valid_sizes': ['1024x1024'],
|
||||
'supports_json_mode': False,
|
||||
'supports_vision': False,
|
||||
'supports_function_calling': False,
|
||||
'is_active': False, # Not valid for OpenAI endpoint
|
||||
'is_default': False,
|
||||
'sort_order': 20,
|
||||
'description': 'Not compatible with OpenAI /v1/images/generations endpoint.',
|
||||
},
|
||||
{
|
||||
'model_name': 'gpt-image-1-mini',
|
||||
'display_name': 'GPT Image 1 Mini (Not compatible with OpenAI)',
|
||||
'model_type': 'image',
|
||||
'provider': 'openai',
|
||||
'cost_per_image': Decimal('0.0110'),
|
||||
'valid_sizes': ['1024x1024'],
|
||||
'supports_json_mode': False,
|
||||
'supports_vision': False,
|
||||
'supports_function_calling': False,
|
||||
'is_active': False, # Not valid for OpenAI endpoint
|
||||
'is_default': False,
|
||||
'sort_order': 30,
|
||||
'description': 'Not compatible with OpenAI /v1/images/generations endpoint.',
|
||||
},
|
||||
]
|
||||
|
||||
# Create all models
|
||||
for model_data in text_models + image_models:
|
||||
AIModelConfig.objects.create(**model_data)
|
||||
|
||||
|
||||
def reverse_seed(apps, schema_editor):
|
||||
"""Remove seeded data"""
|
||||
AIModelConfig = apps.get_model('billing', 'AIModelConfig')
|
||||
AIModelConfig.objects.all().delete()
|
||||
|
||||
|
||||
class Migration(migrations.Migration):
|
||||
|
||||
dependencies = [
|
||||
('billing', '0019_populate_token_based_config'),
|
||||
migrations.swappable_dependency(settings.AUTH_USER_MODEL),
|
||||
]
|
||||
|
||||
operations = [
|
||||
migrations.CreateModel(
|
||||
name='HistoricalAIModelConfig',
|
||||
fields=[
|
||||
('id', models.BigIntegerField(auto_created=True, blank=True, db_index=True, verbose_name='ID')),
|
||||
('model_name', models.CharField(db_index=True, help_text="Model identifier used in API calls (e.g., 'gpt-4o-mini', 'dall-e-3')", max_length=100)),
|
||||
('display_name', models.CharField(help_text="Human-readable name shown in UI (e.g., 'GPT-4o mini - Fast & Affordable')", max_length=200)),
|
||||
('model_type', models.CharField(choices=[('text', 'Text Generation'), ('image', 'Image Generation'), ('embedding', 'Embedding')], db_index=True, help_text='Type of model - determines which pricing fields are used', max_length=20)),
|
||||
('provider', models.CharField(choices=[('openai', 'OpenAI'), ('anthropic', 'Anthropic'), ('runware', 'Runware'), ('google', 'Google')], db_index=True, help_text='AI provider (OpenAI, Anthropic, etc.)', max_length=50)),
|
||||
('input_cost_per_1m', models.DecimalField(blank=True, decimal_places=4, help_text='Cost per 1 million input tokens (USD). For text models only.', max_digits=10, null=True, validators=[django.core.validators.MinValueValidator(Decimal('0.0001'))])),
|
||||
('output_cost_per_1m', models.DecimalField(blank=True, decimal_places=4, help_text='Cost per 1 million output tokens (USD). For text models only.', max_digits=10, null=True, validators=[django.core.validators.MinValueValidator(Decimal('0.0001'))])),
|
||||
('context_window', models.IntegerField(blank=True, help_text='Maximum input tokens (context length). For text models only.', null=True, validators=[django.core.validators.MinValueValidator(1)])),
|
||||
('max_output_tokens', models.IntegerField(blank=True, help_text='Maximum output tokens per request. For text models only.', null=True, validators=[django.core.validators.MinValueValidator(1)])),
|
||||
('cost_per_image', models.DecimalField(blank=True, decimal_places=4, help_text='Fixed cost per image generation (USD). For image models only.', max_digits=10, null=True, validators=[django.core.validators.MinValueValidator(Decimal('0.0001'))])),
|
||||
('valid_sizes', models.JSONField(blank=True, help_text='Array of valid image sizes (e.g., ["1024x1024", "1024x1792"]). For image models only.', null=True)),
|
||||
('supports_json_mode', models.BooleanField(default=False, help_text='True for models with JSON response format support')),
|
||||
('supports_vision', models.BooleanField(default=False, help_text='True for models that can analyze images')),
|
||||
('supports_function_calling', models.BooleanField(default=False, help_text='True for models with function calling capability')),
|
||||
('is_active', models.BooleanField(db_index=True, default=True, help_text='Enable/disable model without deleting')),
|
||||
('is_default', models.BooleanField(db_index=True, default=False, help_text='Mark as default model for its type (only one per type)')),
|
||||
('sort_order', models.IntegerField(default=0, help_text='Control order in dropdown lists (lower numbers first)')),
|
||||
('description', models.TextField(blank=True, help_text='Admin notes about model usage, strengths, limitations')),
|
||||
('release_date', models.DateField(blank=True, help_text='When model was released/added', null=True)),
|
||||
('deprecation_date', models.DateField(blank=True, help_text='When model will be removed', null=True)),
|
||||
('created_at', models.DateTimeField(blank=True, editable=False)),
|
||||
('updated_at', models.DateTimeField(blank=True, editable=False)),
|
||||
('history_id', models.AutoField(primary_key=True, serialize=False)),
|
||||
('history_date', models.DateTimeField(db_index=True)),
|
||||
('history_change_reason', models.CharField(max_length=100, null=True)),
|
||||
('history_type', models.CharField(choices=[('+', 'Created'), ('~', 'Changed'), ('-', 'Deleted')], max_length=1)),
|
||||
('history_user', models.ForeignKey(null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='+', to=settings.AUTH_USER_MODEL)),
|
||||
('updated_by', models.ForeignKey(blank=True, db_constraint=False, help_text='Admin who last updated', null=True, on_delete=django.db.models.deletion.DO_NOTHING, related_name='+', to=settings.AUTH_USER_MODEL)),
|
||||
],
|
||||
options={
|
||||
'verbose_name': 'historical AI Model Configuration',
|
||||
'verbose_name_plural': 'historical AI Model Configurations',
|
||||
'ordering': ('-history_date', '-history_id'),
|
||||
'get_latest_by': ('history_date', 'history_id'),
|
||||
},
|
||||
bases=(simple_history.models.HistoricalChanges, models.Model),
|
||||
),
|
||||
migrations.CreateModel(
|
||||
name='AIModelConfig',
|
||||
fields=[
|
||||
('id', models.BigAutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
|
||||
('model_name', models.CharField(db_index=True, help_text="Model identifier used in API calls (e.g., 'gpt-4o-mini', 'dall-e-3')", max_length=100, unique=True)),
|
||||
('display_name', models.CharField(help_text="Human-readable name shown in UI (e.g., 'GPT-4o mini - Fast & Affordable')", max_length=200)),
|
||||
('model_type', models.CharField(choices=[('text', 'Text Generation'), ('image', 'Image Generation'), ('embedding', 'Embedding')], db_index=True, help_text='Type of model - determines which pricing fields are used', max_length=20)),
|
||||
('provider', models.CharField(choices=[('openai', 'OpenAI'), ('anthropic', 'Anthropic'), ('runware', 'Runware'), ('google', 'Google')], db_index=True, help_text='AI provider (OpenAI, Anthropic, etc.)', max_length=50)),
|
||||
('input_cost_per_1m', models.DecimalField(blank=True, decimal_places=4, help_text='Cost per 1 million input tokens (USD). For text models only.', max_digits=10, null=True, validators=[django.core.validators.MinValueValidator(Decimal('0.0001'))])),
|
||||
('output_cost_per_1m', models.DecimalField(blank=True, decimal_places=4, help_text='Cost per 1 million output tokens (USD). For text models only.', max_digits=10, null=True, validators=[django.core.validators.MinValueValidator(Decimal('0.0001'))])),
|
||||
('context_window', models.IntegerField(blank=True, help_text='Maximum input tokens (context length). For text models only.', null=True, validators=[django.core.validators.MinValueValidator(1)])),
|
||||
('max_output_tokens', models.IntegerField(blank=True, help_text='Maximum output tokens per request. For text models only.', null=True, validators=[django.core.validators.MinValueValidator(1)])),
|
||||
('cost_per_image', models.DecimalField(blank=True, decimal_places=4, help_text='Fixed cost per image generation (USD). For image models only.', max_digits=10, null=True, validators=[django.core.validators.MinValueValidator(Decimal('0.0001'))])),
|
||||
('valid_sizes', models.JSONField(blank=True, help_text='Array of valid image sizes (e.g., ["1024x1024", "1024x1792"]). For image models only.', null=True)),
|
||||
('supports_json_mode', models.BooleanField(default=False, help_text='True for models with JSON response format support')),
|
||||
('supports_vision', models.BooleanField(default=False, help_text='True for models that can analyze images')),
|
||||
('supports_function_calling', models.BooleanField(default=False, help_text='True for models with function calling capability')),
|
||||
('is_active', models.BooleanField(db_index=True, default=True, help_text='Enable/disable model without deleting')),
|
||||
('is_default', models.BooleanField(db_index=True, default=False, help_text='Mark as default model for its type (only one per type)')),
|
||||
('sort_order', models.IntegerField(default=0, help_text='Control order in dropdown lists (lower numbers first)')),
|
||||
('description', models.TextField(blank=True, help_text='Admin notes about model usage, strengths, limitations')),
|
||||
('release_date', models.DateField(blank=True, help_text='When model was released/added', null=True)),
|
||||
('deprecation_date', models.DateField(blank=True, help_text='When model will be removed', null=True)),
|
||||
('created_at', models.DateTimeField(auto_now_add=True)),
|
||||
('updated_at', models.DateTimeField(auto_now=True)),
|
||||
('updated_by', models.ForeignKey(blank=True, help_text='Admin who last updated', null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='ai_model_updates', to=settings.AUTH_USER_MODEL)),
|
||||
],
|
||||
options={
|
||||
'verbose_name': 'AI Model Configuration',
|
||||
'verbose_name_plural': 'AI Model Configurations',
|
||||
'db_table': 'igny8_ai_model_config',
|
||||
'ordering': ['model_type', 'sort_order', 'model_name'],
|
||||
'indexes': [models.Index(fields=['model_type', 'is_active'], name='igny8_ai_mo_model_t_1eef71_idx'), models.Index(fields=['provider', 'is_active'], name='igny8_ai_mo_provide_fbda6c_idx'), models.Index(fields=['is_default', 'model_type'], name='igny8_ai_mo_is_defa_95bfb9_idx')],
|
||||
},
|
||||
),
|
||||
# Seed initial model data
|
||||
migrations.RunPython(seed_ai_models, reverse_seed),
|
||||
]
|
||||
@@ -142,3 +142,59 @@ class UsageLimitsSerializer(serializers.Serializer):
|
||||
"""Serializer for usage limits response"""
|
||||
limits: LimitCardSerializer = LimitCardSerializer(many=True)
|
||||
|
||||
|
||||
class AIModelConfigSerializer(serializers.Serializer):
|
||||
"""
|
||||
Serializer for AI Model Configuration (Read-Only API)
|
||||
Provides model information for frontend dropdowns and displays
|
||||
"""
|
||||
model_name = serializers.CharField(read_only=True)
|
||||
display_name = serializers.CharField(read_only=True)
|
||||
model_type = serializers.CharField(read_only=True)
|
||||
provider = serializers.CharField(read_only=True)
|
||||
|
||||
# Text model fields
|
||||
input_cost_per_1m = serializers.DecimalField(
|
||||
max_digits=10,
|
||||
decimal_places=4,
|
||||
read_only=True,
|
||||
allow_null=True
|
||||
)
|
||||
output_cost_per_1m = serializers.DecimalField(
|
||||
max_digits=10,
|
||||
decimal_places=4,
|
||||
read_only=True,
|
||||
allow_null=True
|
||||
)
|
||||
context_window = serializers.IntegerField(read_only=True, allow_null=True)
|
||||
max_output_tokens = serializers.IntegerField(read_only=True, allow_null=True)
|
||||
|
||||
# Image model fields
|
||||
cost_per_image = serializers.DecimalField(
|
||||
max_digits=10,
|
||||
decimal_places=4,
|
||||
read_only=True,
|
||||
allow_null=True
|
||||
)
|
||||
valid_sizes = serializers.ListField(read_only=True, allow_null=True)
|
||||
|
||||
# Capabilities
|
||||
supports_json_mode = serializers.BooleanField(read_only=True)
|
||||
supports_vision = serializers.BooleanField(read_only=True)
|
||||
supports_function_calling = serializers.BooleanField(read_only=True)
|
||||
|
||||
# Status
|
||||
is_default = serializers.BooleanField(read_only=True)
|
||||
sort_order = serializers.IntegerField(read_only=True)
|
||||
|
||||
# Computed field
|
||||
pricing_display = serializers.SerializerMethodField()
|
||||
|
||||
def get_pricing_display(self, obj):
|
||||
"""Generate pricing display string based on model type"""
|
||||
if obj.model_type == 'text':
|
||||
return f"${obj.input_cost_per_1m}/{obj.output_cost_per_1m} per 1M"
|
||||
elif obj.model_type == 'image':
|
||||
return f"${obj.cost_per_image} per image"
|
||||
return ""
|
||||
|
||||
|
||||
@@ -751,3 +751,75 @@ class AdminBillingViewSet(viewsets.ViewSet):
|
||||
return Response({'error': 'Method not found'}, status=404)
|
||||
|
||||
|
||||
@extend_schema_view(
|
||||
list=extend_schema(tags=['AI Models'], summary='List available AI models'),
|
||||
retrieve=extend_schema(tags=['AI Models'], summary='Get AI model details'),
|
||||
)
|
||||
class AIModelConfigViewSet(viewsets.ReadOnlyModelViewSet):
|
||||
"""
|
||||
ViewSet for AI Model Configuration (Read-Only)
|
||||
Provides model information for frontend dropdowns and displays
|
||||
"""
|
||||
permission_classes = [IsAuthenticatedAndActive]
|
||||
authentication_classes = [JWTAuthentication, CSRFExemptSessionAuthentication]
|
||||
throttle_scope = 'billing'
|
||||
throttle_classes = [DebugScopedRateThrottle]
|
||||
pagination_class = None # No pagination for model lists
|
||||
lookup_field = 'model_name'
|
||||
|
||||
def get_queryset(self):
|
||||
"""Get AIModelConfig queryset with filters"""
|
||||
from igny8_core.business.billing.models import AIModelConfig
|
||||
|
||||
queryset = AIModelConfig.objects.filter(is_active=True)
|
||||
|
||||
# Filter by model type
|
||||
model_type = self.request.query_params.get('type', None)
|
||||
if model_type:
|
||||
queryset = queryset.filter(model_type=model_type)
|
||||
|
||||
# Filter by provider
|
||||
provider = self.request.query_params.get('provider', None)
|
||||
if provider:
|
||||
queryset = queryset.filter(provider=provider)
|
||||
|
||||
# Filter by default
|
||||
is_default = self.request.query_params.get('default', None)
|
||||
if is_default is not None:
|
||||
is_default_bool = is_default.lower() in ['true', '1', 'yes']
|
||||
queryset = queryset.filter(is_default=is_default_bool)
|
||||
|
||||
return queryset.order_by('model_type', 'sort_order', 'model_name')
|
||||
|
||||
def get_serializer_class(self):
|
||||
"""Return serializer class"""
|
||||
from .serializers import AIModelConfigSerializer
|
||||
return AIModelConfigSerializer
|
||||
|
||||
def list(self, request, *args, **kwargs):
|
||||
"""List all available models with filters"""
|
||||
queryset = self.get_queryset()
|
||||
serializer = self.get_serializer(queryset, many=True)
|
||||
|
||||
return success_response(
|
||||
data=serializer.data,
|
||||
message='AI models retrieved successfully'
|
||||
)
|
||||
|
||||
def retrieve(self, request, *args, **kwargs):
|
||||
"""Get details for a specific model"""
|
||||
try:
|
||||
instance = self.get_queryset().get(model_name=kwargs.get('model_name'))
|
||||
serializer = self.get_serializer(instance)
|
||||
|
||||
return success_response(
|
||||
data=serializer.data,
|
||||
message='AI model details retrieved successfully'
|
||||
)
|
||||
except Exception as e:
|
||||
return error_response(
|
||||
message='Model not found',
|
||||
errors={'model_name': [str(e)]},
|
||||
status_code=status.HTTP_404_NOT_FOUND
|
||||
)
|
||||
|
||||
|
||||
Reference in New Issue
Block a user