Luma Uni v1 Edit API | WaveSpeedAI

Luma UNI V1 Edit

Luma UNI V1 Edit edits an input image using a natural-language prompt, with optional reference-image guidance and flexible output format support. It is suitable for scene changes, style edits, mood adjustments, lighting transformations, and other prompt-driven image editing workflows.

Why Choose This?

Prompt-based image editing
Edit an existing image by describing the change you want in natural language.
Reference-guided visual control
Add one or more reference images when you want stronger style or subject guidance.
Simple editing workflow
Upload an image, write a prompt, optionally add references, and generate the edited result.
Flexible output format
Export the edited image in a supported format such as jpeg.
Production-ready API
Suitable for visual retouching, scene transformation, content iteration, and creative image editing workflows.

Parameters

Parameter	Required	Description
prompt	Yes	Text instruction describing the desired edit.
image	Yes	Input image to edit.
output_format	No	Output image format, such as `jpeg`.
reference	No	Optional reference images for visual guidance.

How to Use

Upload your image — provide the source image you want to edit.
Write your prompt — describe what should change in the image.
Choose output format (optional) — select the file format that best fits your workflow.
Add references (optional) — upload one or more reference images if you want stronger style or visual guidance.
Submit — run the model and download the edited image.

Example Prompt

Change the time to the midnight.

Pricing

Pricing includes a fixed base image charge plus a reference-related surcharge.

Mode	Cost
Edit with no extra references	$0.045
Edit with 1 reference image	$0.048
Edit with 2 reference images	$0.051
Edit with 3 reference images	$0.054

Billing Rules

Editing adds a built-in $0.003 surcharge for the required source image workflow
Each additional reference image adds $0.003
output_format does not affect pricing

Best Use Cases

Scene transformation — Change time of day, environment mood, or background feel.
Lighting adjustment — Shift an image into nighttime, sunset, studio, or other lighting conditions.
Style adaptation — Move an image toward a different visual tone with optional references.
Creative retouching — Refine a shot for storytelling, ads, or social content.
Prompt-driven variations — Explore multiple edited versions from the same base image.

Pro Tips

Be clear and direct about what should change in the source image.
Add references only when you need stronger style guidance, since they increase the price slightly.
Keep prompts focused on the main transformation rather than restating unchanged details.
Use jpeg for lightweight delivery unless your workflow requires another format.
Try the edit once without references first, then add them if the result needs more control.

Notes

prompt and image are required.
Pricing depends on the number of additional reference images.
The required input image is already accounted for in the edit pricing.
Better prompts usually improve edit accuracy and scene consistency.

Related Models

Luma UNI V1 Text-to-Image — Generate images directly from text prompts.
Luma image generation workflows — Useful when you need different image generation or editing styles.

Uni v1 Edit API — Quick start

Grab a WaveSpeedAI API key, then call POST https://api.wavespeed.ai/api/v3/luma/uni-v1/edit with your input as JSON. The endpoint returns a prediction id; poll the prediction endpoint until status flips to completed, then read the output URL from data.outputs[0]. Examples for Uni v1 Edit below.

HTTP example

# Submit the prediction
curl -X POST "https://api.wavespeed.ai/api/v3/luma/uni-v1/edit" \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $WAVESPEED_API_KEY" \
  -d '{
    "prompt": "A cinematic shot of a city at sunset, soft golden light",
    "image": "https://example.com/your-input.jpg",
    "output_format": "jpeg"
}'

# Response includes a prediction id. Poll for the result:
curl -X GET "https://api.wavespeed.ai/api/v3/predictions/{request_id}/result" \
  -H "Authorization: Bearer $WAVESPEED_API_KEY"

# When status is "completed", read the output from data.outputs[0].

Node.js example

// npm install wavespeed
const WaveSpeed = require('wavespeed');

const client = new WaveSpeed(); // reads WAVESPEED_API_KEY from env

const result = await client.run("luma/uni-v1/edit", {
        "prompt": "A cinematic shot of a city at sunset, soft golden light",
        "image": "https://example.com/your-input.jpg",
        "output_format": "jpeg"
});

console.log(result.outputs[0]); // → URL of the generated output

Python example

# pip install wavespeed
import wavespeed

output = wavespeed.run(
    "luma/uni-v1/edit",
    {
    "prompt": "A cinematic shot of a city at sunset, soft golden light",
    "image": "https://example.com/your-input.jpg",
    "output_format": "jpeg"
}
)

print(output["outputs"][0])  # → URL of the generated output

Uni v1 Edit API — Frequently asked questions

What is the Uni v1 Edit API?

Uni v1 Edit is a Luma model for image editing, exposed as a REST API on WaveSpeedAI. Luma Uni v1 Edit is a fast AI image editing model that reworks source images from text instructions while preserving composition and supporting optional reference images. Ready-to-use REST inference API for photo editing, product image updates, creative retouching, marketing assets, brand visuals, style changes, and professional image editing workflows with simple integration, no coldstarts, and affordable pricing. You can call it programmatically or try it from the playground above.

How do I call the Uni v1 Edit API?

POST your input parameters to the model's REST endpoint (shown in the API tab of this playground) with your WaveSpeedAI API key in the Authorization header. Submission returns a prediction ID; poll the prediction endpoint until status flips to "completed", then read the output URL from the result. The playground generates a ready-to-paste code sample in Python, JavaScript, or cURL for whatever inputs you've set. Full request/response shape is documented at https://wavespeed.ai/docs/docs-api/luma/luma-uni-v1-edit.

How much does Uni v1 Edit cost per run?

Uni v1 Edit starts at $0.042 per run. That figure is the base price — the final charge scales with the parameters you set in the form (output size, length, count, references, or whatever knobs this model exposes), so a higher-quality or larger output costs more than a minimal one. The exact cost for your current input is shown live next to the Generate button before you submit, and the actual per-call charge is recorded on the prediction afterwards.

What inputs does Uni v1 Edit accept?

Key inputs: `prompt`, `image`, `output_format`, `reference`. The full JSON schema (types, defaults, allowed values) is rendered above the Generate button and mirrored in the API reference at https://wavespeed.ai/docs/docs-api/luma/luma-uni-v1-edit.

How do I get started with the Uni v1 Edit API?

Sign up for a free WaveSpeedAI account to claim starter credits, copy your API key from /accesskey, then call the endpoint shown in the API tab of the playground. The playground also auto-generates a code sample in Python, JavaScript, or cURL for the parameters you've set.

Can I use Uni v1 Edit outputs commercially?

Commercial usage rights depend on the model's license, set by its provider (Luma). The license summary appears on the model card above; see WaveSpeedAI's Terms of Service for platform-level conditions.

EjemplosVer todo

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