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image_to_image

Modifies an input image according to a text prompt, enabling style transfer, seasonal changes, or other transformations using AI.

Instructions

Generate an image from an existing image using WaveSpeed AI.

Args:
    image (str): Required. URL, base64 string, or local file path of the input image to modify.
    images (List[str]): Required. List of URLs to images to modify.
    prompt (str): Required. Text description of the desired modifications. MUST BE IN ENGLISH. Non-English prompts will be rejected or result in poor quality outputs.
    model (str, optional): Model to use for image generation.
    guidance_scale (float, optional): Guidance scale for text adherence. Controls how closely the output follows the prompt. Range: [1.0-10.0]. Default: 3.5.
    enable_safety_checker (bool, optional): Whether to enable safety filtering. Default: True.
    output_directory (str, optional): Directory to save the generated images. Uses a temporary directory if not provided.
    request_id (str, optional): Request correlation ID for tracing the entire request chain. Strongly recommended to provide a unique ID (e.g., UUID) to correlate logs across the request lifecycle.

Returns:
    WaveSpeedResult object with the result of the image generation, containing:
    - status: "success" or "error"
    - urls: List of image URLs if successful
    - base64: List of base64 encoded images if resource_mode is set to base64
    - local_files: List of local file paths if resource_mode is set to local
    - error: Error message if status is "error"
    - processing_time: Time taken to generate the image(s)
    
Examples:
    Single image: image_to_image(image="https://example.com/image.jpg", images=[], prompt="Make it look like winter")
    Multiple images: image_to_image(image="", images=["https://example.com/img1.jpg", "https://example.com/img2.jpg"], prompt="Convert to oil painting style")
    Both parameters: image_to_image(image="https://example.com/main.jpg", images=["https://example.com/ref1.jpg"], prompt="Apply style transfer")
    
Note: 
    For optimal results, always provide prompts in English, regardless of your interface language.
    Non-English prompts may result in lower quality or unexpected images.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
imageYes
imagesYes
promptYes
modelNo
guidance_scaleNo
enable_safety_checkerNo
output_directoryNo
request_idNo
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description bears full responsibility. It discloses behavioral traits: uses WaveSpeed AI, requires English prompts, provides safety checker, and explains request_id for tracing. It also describes the return structure. However, it omits potential rate limits, authentication requirements, or error handling details.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is front-loaded with a clear one-sentence summary followed by structured Args/Returns/Examples/Note sections. However, it is somewhat verbose with multiple examples and a note that could be shorter. Still, the structure aids readability and comprehension.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given 8 parameters (3 required), no output schema, and no nested objects, the description is complete. It explains the return structure (status, urls, base64, local_files, error, processing_time) and provides examples showing different usage patterns. No additional context seems necessary for correct tool invocation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, meaning the input schema only provides names and types. The description adds substantial meaning: explains that 'image' and 'images' accept URL, base64, or local paths; describes prompt language requirement; specifies range and default for guidance_scale; explains safety checker, output directory, and request_id purpose. This is far beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool generates an image from an existing image using WaveSpeed AI. It effectively distinguishes from sibling tools: generate_video (video output) and text_to_image (no input image). The verb 'generate' and resource 'image from an existing image' are specific.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides examples and notes about English prompts, but lacks explicit guidance on when to use this tool versus alternatives like text_to_image or generate_video. The usage context is implied through examples but no exclusions or when-not scenarios are mentioned.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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