Luma Uni-1

This documentation is valid for the following list of our models:

• luma/uni-1

Try in Playground

Model Overview

Luma Uni-1 generates and edits images from text prompts with support for up to 9 reference images, styles, and web-search grounding.

Create AI/ML API Key

How to make the first API call

1️⃣ Required setup (don’t skip this) ▪ Create an account: Sign up on the AI/ML API website (if you don’t have one yet). ▪ Generate an API key: In your account dashboard, create an API key and make sure it’s enabled in the UI.

2️ Copy the code example At the bottom of this page, pick the snippet for your preferred programming language (Python / Node.js) and copy it into your project.

3️ Update the snippet for your use case ▪ Insert your API key: replace <YOUR_AIMLAPI_KEY> with your real AI/ML API key. ▪ Select a model: set the model field to the model you want to call. ▪ Provide input: fill in the request input field(s) shown in the example.

4️ (Optional) Tune the request See the API schema below for optional generation settings.

5️ Run your code Run the updated code in your development environment.

For a detailed walkthrough, use our Quickstart guide.

API Schema

post

Body

application/json

modelstring · enumRequiredPossible values:

promptstring · min: 1 · max: 6000Required

Text description of the image to generate.

typestring · enumOptional

Generation kind: "image" (text-to-image / reference) or "image_edit".

Default: imagePossible values:

aspect_ratiostring · enumOptional

Output aspect ratio. Omit to let the model choose automatically.

Possible values:

stylestring · enumOptional

Rendering style. Defaults to "auto".

Default: autoPossible values:

output_formatstring · enumOptional

Output image format (png or jpeg).

Possible values:

web_searchbooleanOptional

Ground the generation with web search.

Default: false

image_urlstring · uriOptional

A reference image URL for image generation, or source image URL for image editing.

image_urlsstring · uri[] · max: 9Optional

Up to 9 reference image URLs (or uploaded files).

Responses

200

Successful response.

application/json

post/v1/images/generations

cURLJavaScriptPython

curl --request POST \
  --url 'https://api.aimlapi.com/v1/images/generations' \
  --header 'Authorization: Bearer <YOUR_AIMLAPI_KEY>' \
  --header 'Content-Type: application/json' \
  --data '{"model": "luma/uni-1", "prompt": "Describe what you want the model to generate.", "image_url": "https://example.com/input.jpg"}'

200

Successful response.

{
  "data": [
    {
      "url": "https://cdn.aimlapi.com/generations/hedgehog/1749730923700-29fe35d2-4aef-4bc5-a911-6c39884d16a8.png",
      "b64_json": null
    }
  ],
  "meta": {
    "usage": {
      "credits_used": 120000,
      "usd_spent": 0.06
    }
  }
}

Code Example

Python

import requests

response = requests.post(
    "https://api.aimlapi.com/v1/images/generations",
    headers={
        "Authorization": "Bearer <YOUR_AIMLAPI_KEY>",
        "Content-Type": "application/json",
    },
    json={'model': 'luma/uni-1', 'prompt': 'Describe what you want the model to generate.', 'image_url': 'https://example.com/input.jpg'},
)

print(response.json())

JavaScript

Response

{
  "data": [
    {
      "url": "https://cdn.aimlapi.com/generations/hedgehog/1749730923700-29fe35d2-4aef-4bc5-a911-6c39884d16a8.png",
      "b64_json": null
    }
  ],
  "meta": {
    "usage": {
      "credits_used": 120000,
      "usd_spent": 0.06
    }
  },
  "model": "luma/uni-1"
}