AI MODELS & final updates - feat: Implement AI Model Configuration with dynamic pricing and REST API
- Added AIModelConfig model to manage AI model configurations in the database. - Created serializers and views for AI model configurations, enabling read-only access via REST API. - Implemented filtering capabilities for model type, provider, and default status in the API. - Seeded initial data for text and image models, including pricing and capabilities. - Updated Django Admin interface for managing AI models with enhanced features and bulk actions. - Added validation methods for model and image size checks. - Comprehensive migration created to establish the AIModelConfig model and seed initial data. - Documented implementation and validation results in summary and report files.
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IGNY8 VPS (Salman)
@@ -687,3 +687,238 @@ class AccountPaymentMethod(AccountBaseModel):
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def __str__(self):
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return f"{self.account_id} - {self.display_name} ({self.type})"
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class AIModelConfig(models.Model):
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"""
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AI Model Configuration - Database-driven model pricing and capabilities.
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Replaces hardcoded MODEL_RATES and IMAGE_MODEL_RATES from constants.py
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Two pricing models:
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- Text models: Cost per 1M tokens (input/output), credits calculated AFTER AI call
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- Image models: Cost per image, credits calculated BEFORE AI call
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"""
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MODEL_TYPE_CHOICES = [
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('text', 'Text Generation'),
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('image', 'Image Generation'),
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('embedding', 'Embedding'),
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]
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PROVIDER_CHOICES = [
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('openai', 'OpenAI'),
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('anthropic', 'Anthropic'),
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('runware', 'Runware'),
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('google', 'Google'),
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]
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# Basic Information
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model_name = models.CharField(
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max_length=100,
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unique=True,
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db_index=True,
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help_text="Model identifier used in API calls (e.g., 'gpt-4o-mini', 'dall-e-3')"
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)
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display_name = models.CharField(
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max_length=200,
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help_text="Human-readable name shown in UI (e.g., 'GPT-4o mini - Fast & Affordable')"
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)
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model_type = models.CharField(
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max_length=20,
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choices=MODEL_TYPE_CHOICES,
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db_index=True,
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help_text="Type of model - determines which pricing fields are used"
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)
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provider = models.CharField(
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max_length=50,
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choices=PROVIDER_CHOICES,
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db_index=True,
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help_text="AI provider (OpenAI, Anthropic, etc.)"
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)
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# Text Model Pricing (Only for model_type='text')
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input_cost_per_1m = models.DecimalField(
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max_digits=10,
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decimal_places=4,
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null=True,
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blank=True,
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validators=[MinValueValidator(Decimal('0.0001'))],
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help_text="Cost per 1 million input tokens (USD). For text models only."
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)
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output_cost_per_1m = models.DecimalField(
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max_digits=10,
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decimal_places=4,
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null=True,
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blank=True,
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validators=[MinValueValidator(Decimal('0.0001'))],
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help_text="Cost per 1 million output tokens (USD). For text models only."
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)
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context_window = models.IntegerField(
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null=True,
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blank=True,
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validators=[MinValueValidator(1)],
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help_text="Maximum input tokens (context length). For text models only."
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)
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max_output_tokens = models.IntegerField(
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null=True,
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blank=True,
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validators=[MinValueValidator(1)],
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help_text="Maximum output tokens per request. For text models only."
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)
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# Image Model Pricing (Only for model_type='image')
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cost_per_image = models.DecimalField(
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max_digits=10,
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decimal_places=4,
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null=True,
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blank=True,
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validators=[MinValueValidator(Decimal('0.0001'))],
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help_text="Fixed cost per image generation (USD). For image models only."
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)
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valid_sizes = models.JSONField(
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null=True,
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blank=True,
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help_text='Array of valid image sizes (e.g., ["1024x1024", "1024x1792"]). For image models only.'
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)
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# Capabilities
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supports_json_mode = models.BooleanField(
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default=False,
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help_text="True for models with JSON response format support"
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)
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supports_vision = models.BooleanField(
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default=False,
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help_text="True for models that can analyze images"
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)
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supports_function_calling = models.BooleanField(
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default=False,
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help_text="True for models with function calling capability"
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)
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# Status & Configuration
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is_active = models.BooleanField(
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default=True,
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db_index=True,
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help_text="Enable/disable model without deleting"
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)
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is_default = models.BooleanField(
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default=False,
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db_index=True,
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help_text="Mark as default model for its type (only one per type)"
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)
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sort_order = models.IntegerField(
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default=0,
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help_text="Control order in dropdown lists (lower numbers first)"
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)
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# Metadata
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description = models.TextField(
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blank=True,
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help_text="Admin notes about model usage, strengths, limitations"
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)
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release_date = models.DateField(
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null=True,
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blank=True,
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help_text="When model was released/added"
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)
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deprecation_date = models.DateField(
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null=True,
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blank=True,
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help_text="When model will be removed"
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)
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# Audit Fields
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created_at = models.DateTimeField(auto_now_add=True)
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updated_at = models.DateTimeField(auto_now=True)
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updated_by = models.ForeignKey(
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settings.AUTH_USER_MODEL,
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null=True,
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blank=True,
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on_delete=models.SET_NULL,
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related_name='ai_model_updates',
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help_text="Admin who last updated"
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)
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# History tracking
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history = HistoricalRecords()
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class Meta:
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app_label = 'billing'
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db_table = 'igny8_ai_model_config'
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verbose_name = 'AI Model Configuration'
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verbose_name_plural = 'AI Model Configurations'
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ordering = ['model_type', 'sort_order', 'model_name']
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indexes = [
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models.Index(fields=['model_type', 'is_active']),
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models.Index(fields=['provider', 'is_active']),
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models.Index(fields=['is_default', 'model_type']),
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]
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def __str__(self):
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return self.display_name
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def save(self, *args, **kwargs):
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"""Ensure only one is_default per model_type"""
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if self.is_default:
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# Unset other defaults for same model_type
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AIModelConfig.objects.filter(
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model_type=self.model_type,
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is_default=True
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).exclude(pk=self.pk).update(is_default=False)
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super().save(*args, **kwargs)
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def get_cost_for_tokens(self, input_tokens, output_tokens):
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"""Calculate cost for text models based on token usage"""
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if self.model_type != 'text':
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raise ValueError("get_cost_for_tokens only applies to text models")
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if not self.input_cost_per_1m or not self.output_cost_per_1m:
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raise ValueError(f"Model {self.model_name} missing cost_per_1m values")
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cost = (
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(Decimal(input_tokens) * self.input_cost_per_1m) +
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(Decimal(output_tokens) * self.output_cost_per_1m)
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) / Decimal('1000000')
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return cost
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def get_cost_for_images(self, num_images):
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"""Calculate cost for image models"""
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if self.model_type != 'image':
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raise ValueError("get_cost_for_images only applies to image models")
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if not self.cost_per_image:
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raise ValueError(f"Model {self.model_name} missing cost_per_image")
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return self.cost_per_image * Decimal(num_images)
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def validate_size(self, size):
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"""Check if size is valid for this image model"""
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if self.model_type != 'image':
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raise ValueError("validate_size only applies to image models")
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if not self.valid_sizes:
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return True # No size restrictions
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return size in self.valid_sizes
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def get_display_with_pricing(self):
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"""For dropdowns: show model with pricing"""
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if self.model_type == 'text':
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return f"{self.display_name} - ${self.input_cost_per_1m}/${self.output_cost_per_1m} per 1M"
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elif self.model_type == 'image':
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return f"{self.display_name} - ${self.cost_per_image} per image"
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return self.display_name
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