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image_to_image

Generate new images by modifying existing ones with text prompts. Upload an image and describe desired changes to transform its style, content, or appearance.

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
Behavior5/5

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

Despite no annotations, the description fully discloses behavioral traits: prompt language requirement ('MUST BE IN ENGLISH'), safety checker option, guidance scale range and default, output handling (return object with status, urls, etc.), and request_id for tracing. No contradictions.

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 well-structured with sections (Args, Returns, Examples, Note) and front-loaded with the main purpose. It is somewhat lengthy but every part adds value. Minor redundancy in examples could be trimmed, but overall effective.

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, no output schema, and no annotations, the description is fully complete. It explains all parameters, return values in detail, provides multiple examples, and includes a critical note on English prompts. No gaps.

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%, but the description adds rich meaning for all 8 parameters: image (URL/base64/path), images (list), prompt (English required), model (optional), guidance_scale (range 1-10, default 3.5), enable_safety_checker (boolean, default True), output_directory (temp if not given), request_id (UUID recommended). This greatly exceeds the bare 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's purpose: 'Generate an image from an existing image using WaveSpeed AI.' It uses a specific verb ('Generate') and resource ('image from an existing image'), effectively distinguishing it from siblings like 'text_to_image' (which generates from text) and 'generate_video' (which generates video).

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

Usage Guidelines4/5

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

The description provides clear context on when to use the tool, including required parameters and examples. It does not explicitly state when not to use it versus alternatives, but the purpose and examples make it intuitive. The note about English prompts adds essential guidance.

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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