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post-upscale-inferences

Upscale images using AI with customizable styles, presets, and parameters to enhance resolution and detail while maintaining control over fidelity and creativity.

Instructions

Trigger the upscaling of an image. You can use styles and presets to quickly get results or craft your very own settings.

Note:This endpoint is deprecated and will be removed in the future. Please leverage POST /generate/custom/{modelId} endpoint instead with model_scenario-upscale-v3 modelId for example. See https://docs.scenario.com/docs/upscale-generation for more details.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
originalAssetsNoIf set to true, returns the original asset without transformation
dryRunNo
imageYesImage to upscale. Must reference an existing AssetId or be a data URL.
creativityDecayNoAmount of decay in creativity over the upscale process. The lowest the value, the less the creativity will be preserved over the upscale process.
tileStyleNoIf set to true, during the upscaling process, the model will match tiles of the source image with tiles of the style image(s). This will result in a more coherent restyle. Works best with style images that have a similar composition.
seedNoUsed to reproduce previous results. Default: randomly generated number.
styleImagesNo
scalingFactorNoScaling factor (when `targetWidth` not specified)
presetNoOptimize the upscale for a specific use case. Precise: Upscale for high fidelity. Balanced: Upscale for a balance between fidelity and creativity. Creative: Upscale for creativity.
styleImagesFidelityNoCondition the influence of the style image(s). The higher the value, the more the style images will influence the upscaled image.
detailsLevelNoAmount of details to remove or add
fractalityNoDetermine the scale at which the upscale process works. - With a small value, the upscale works at the largest scale, resulting in fewer added details and more coherent images. Ideal for portraits, for example. - With a large value, the upscale works at the smallest scale, resulting in more added details and more hallucinations. Ideal for landscapes, for example. (info): A small value is slower and more expensive to run.
negativePromptNoA negative full text prompt that discourages the upscale from generating certain characteristics. It is recommended to test without using a negative prompt. Default: empty string. Example: "Low resolution, blurry, pixelated, noisy."
overrideEmbeddingsNoOverride the embeddings of the model. Only your prompt and negativePrompt will be used. Use with caution.
promptFidelityNoIncrease the fidelity to the prompt during upscale. Default: optimized for your preset and style.
styleNoOptimize the upscale for a specific style. standard works in most cases. Use one of the other styles to refine the outputs.
refinementStepsNoAdditional refinement steps before scaling. If scalingFactor == 1, the refinement process will be applied (1 + refinementSteps) times. If scalingFactor > 1, the refinement process will be applied refinementSteps times.
creativityNoAllow the generation of "hallucinations" during the upscale process, which adds additional details and deviates from the original image. Default: optimized for your preset and style.
imageFidelityNoStrengthen the similarity to the original image during the upscale. Default: optimized for your preset and style.
imageTypeNoPreserve the seamless properties of skybox or texture images. Input has to be of same type (seamless).
promptNoA full text prompt to guide the upscale and forcing the generation of certain characteristics. Default: empty string. Example: "UHD 8K hyper detailed studio photo of man face with yellow skin, anatomical++, disturbing+++, black background. Bloody++."
targetWidthNoTarget width for the upscaled image, take priority over scaling factor
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. While it mentions the tool is deprecated (a critical behavioral trait), it lacks essential operational details such as required permissions, rate limits, cost implications, or what the output looks like (e.g., returns an asset ID, URL, or processed image). For a complex mutation tool with 22 parameters, this is a significant gap.

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 efficiently structured with two sentences: one stating the purpose and capabilities, and another providing critical deprecation and migration guidance. The note is front-loaded with important information, though the second sentence could be slightly more concise.

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

Completeness2/5

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

Given the tool's complexity (22 parameters, no output schema, no annotations), the description is incomplete. It lacks details on output format, error handling, authentication needs, and operational constraints. While the deprecation note is crucial, it doesn't compensate for the missing behavioral and contextual information required for effective tool invocation.

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

Parameters3/5

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

Schema description coverage is high at 91%, so the schema already documents most parameters thoroughly. The description adds minimal value beyond the schema by vaguely mentioning 'styles and presets' and 'craft your very own settings,' but doesn't provide additional syntax, format, or interaction details for the parameters. The baseline of 3 is appropriate given the schema does the heavy lifting.

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 specific action ('Trigger the upscaling of an image') and resource ('image'), distinguishing it from sibling tools like 'post-img2img-inferences' or 'post-restyle-inferences' that perform different image transformations. The mention of 'styles and presets' further clarifies the tool's functionality beyond basic upscaling.

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

Usage Guidelines5/5

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

The description explicitly provides when-not-to-use guidance by stating the tool is deprecated and recommending an alternative ('POST /generate/custom/{modelId}' with specific parameters). It includes a link to documentation for further details, offering clear direction for migration.

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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