transform_image_from_url
Transform existing images from URLs using AI editing functions like stylization, resolution enhancement, watermark removal, and content modification based on text prompts.
Instructions
Transform an existing image from a URL using the configured image provider.
Args:
image_url: Remote or Public URL of the image to be transformed
prompt: Text prompt describing the desired transformation or modifications
function: WanX editing function (default: 'description_edit'). Supported functions:
'description_edit', 'description_edit_with_mask', 'stylization_all',
'stylization_local', 'remove_watermark', 'expand', 'super_resolution',
'colorization', 'doodle', 'control_cartoon_feature'
mask_image_url: URL of mask image (required for 'description_edit_with_mask')
Returns:
Details about the transformed image including local path and remote URL
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| image_url | Yes | ||
| prompt | Yes | ||
| function | No | description_edit | |
| mask_image_url | No |
Output Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |
Implementation Reference
- The core handler function for the 'transform_image_from_url' MCP tool. It is decorated with @mcp.tool() for automatic registration and schema inference from signature/docstring. Handles provider-specific logic for downloading images from URL, prompt translation/optimization, and transformation via the image provider.
@mcp.tool() async def transform_image_from_url(image_url: str, prompt: str, function: str = "description_edit", mask_image_url: Optional[str] = None) -> str: """Transform an existing image from a URL using the configured image provider. Args: image_url: Remote or Public URL of the image to be transformed prompt: Text prompt describing the desired transformation or modifications function: WanX editing function (default: 'description_edit'). Supported functions: 'description_edit', 'description_edit_with_mask', 'stylization_all', 'stylization_local', 'remove_watermark', 'expand', 'super_resolution', 'colorization', 'doodle', 'control_cartoon_feature' mask_image_url: URL of mask image (required for 'description_edit_with_mask') Returns: Details about the transformed image including local path and remote URL """ try: provider = get_image_provider() logger.info(f"Processing transform_image_from_url request with {provider.get_name()}") logger.info(f"Image URL: {image_url}") logger.info(f"Transformation prompt: {prompt}") logger.info(f"Function: {function}") # For providers that don't support URL-based transformation, we need to download and convert if provider.get_name() == "google": # Download image and convert to PIL Image for Google import requests response = requests.get(image_url) if response.status_code != 200: raise ValueError(f"Failed to download image from URL: {image_url}") source_image = PIL.Image.open(BytesIO(response.content)) logger.info(f"Downloaded and loaded image from URL for Google") # Translate the prompt for the provider translated_prompt = await translate_prompt_for_provider(prompt, provider) # Create detailed transformation prompt transformation_prompt = get_image_transformation_prompt(translated_prompt) # Process the transformation using the provider _, saved_path, remote_url = await provider.transform_image(source_image, transformation_prompt) elif provider.get_name() == "bailian": # For Bailian, we can use the URL directly # Translate the prompt for the provider translated_prompt = await translate_prompt_for_provider(prompt, provider) # Create detailed transformation prompt transformation_prompt = get_image_transformation_prompt(translated_prompt) # Prepare kwargs for Bailian provider kwargs = { 'function': function, 'base_image_url': image_url } # Add mask image URL if provided and function requires it if mask_image_url: kwargs['mask_image_url'] = mask_image_url elif function == "description_edit_with_mask": raise ValueError("mask_image_url is required for description_edit_with_mask function") # Use a dummy PIL image since we're passing URL via kwargs dummy_image = PIL.Image.new('RGB', (1, 1)) # Process the transformation using the provider _, saved_path, remote_url = await provider.transform_image(dummy_image, transformation_prompt, **kwargs) else: # For other providers, download image first import requests response = requests.get(image_url) if response.status_code != 200: raise ValueError(f"Failed to download image from URL: {image_url}") source_image = PIL.Image.open(BytesIO(response.content)) logger.info(f"Downloaded and loaded image from URL") # Translate the prompt for the provider translated_prompt = await translate_prompt_for_provider(prompt, provider) # Create detailed transformation prompt transformation_prompt = get_image_transformation_prompt(translated_prompt) # Process the transformation using the provider _, saved_path, remote_url = await provider.transform_image(source_image, transformation_prompt) logger.info(f"Image transformed and saved to: {saved_path}") # Prepare response with remote URL if available response = f"Image transformed and saved to: {saved_path}" if remote_url: response += f"\nRemote URL: {remote_url}" return response except Exception as e: error_msg = f"Error transforming image from URL: {str(e)}" logger.error(error_msg) return error_msg