> For the complete documentation index, see [llms.txt](https://docs.aimlapi.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.aimlapi.com/api-references/image-models/luma-ai/uni-1.md).

# Luma Uni-1

{% columns %}
{% column width="66.66666666666666%" %}
{% hint style="info" %}
This documentation is valid for the following list of our models:

* `luma/uni-1`
  {% endhint %}
  {% endcolumn %}

{% column width="33.33333333333334%" %} <a href="https://aimlapi.com/app/luma/uni-1" class="button primary">Try in Playground</a>
{% endcolumn %}
{% endcolumns %}

## 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.

{% hint style="success" %}
[Create AI/ML API Key](https://aimlapi.com/app/keys)
{% endhint %}

<details>

<summary>How to make the first API call</summary>

**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.

{% hint style="success" %}
For a detailed walkthrough, use our [Quickstart guide](https://docs.aimlapi.com/quickstart/setting-up).
{% endhint %}

</details>

## API Schema

## POST /v1/images/generations

>

```json
{"openapi":"3.0.0","info":{"title":"AIML API","version":"1.0.0"},"servers":[{"url":"https://api.aimlapi.com"}],"paths":{"/v1/images/generations":{"post":{"operationId":"_v1_images_generations","requestBody":{"required":true,"content":{"application/json":{"schema":{"type":"object","properties":{"model":{"type":"string","enum":["luma/uni-1"]},"prompt":{"type":"string","minLength":1,"maxLength":6000,"description":"Text description of the image to generate."},"type":{"type":"string","enum":["image","image_edit"],"default":"image","description":"Generation kind: \"image\" (text-to-image / reference) or \"image_edit\"."},"aspect_ratio":{"type":"string","enum":["3:1","2:1","16:9","3:2","1:1","2:3","9:16","1:2","1:3"],"description":"Output aspect ratio. Omit to let the model choose automatically."},"style":{"type":"string","enum":["auto","manga"],"default":"auto","description":"Rendering style. Defaults to \"auto\"."},"output_format":{"type":"string","enum":["png","jpeg"],"description":"Output image format (png or jpeg)."},"web_search":{"type":"boolean","default":false,"description":"Ground the generation with web search."},"image_url":{"type":"string","format":"uri","description":"A reference image URL for image generation, or source image URL for image editing."},"image_urls":{"type":"array","items":{"type":"string","format":"uri"},"maxItems":9,"description":"Up to 9 reference image URLs (or uploaded files)."}},"required":["model","prompt"],"title":"luma/uni-1"}}}},"responses":{"200":{"content":{"application/json":{"schema":{"type":"object","properties":{"data":{"type":"array","nullable":true,"items":{"type":"object","properties":{"url":{"type":"string","nullable":true,"description":"The URL where the file can be downloaded from."},"b64_json":{"type":"string","nullable":true,"description":"The base64-encoded JSON of the generated image."}}},"description":"The list of generated images."},"meta":{"type":"object","nullable":true,"properties":{"usage":{"type":"object","nullable":true,"properties":{"credits_used":{"type":"number","description":"The number of tokens consumed during generation."},"usd_spent":{"type":"number","description":"The total amount of money spent by the user in USD."}},"required":["credits_used","usd_spent"]}},"description":"Additional details about the generation."}}}}},"description":"Successful response."}}}}}}
```

## Code Example

{% tabs %}
{% tab title="Python" %}
{% code overflow="wrap" %}

```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())
```

{% endcode %}
{% endtab %}

{% tab title="JavaScript" %}
{% code overflow="wrap" %}

```javascript
const response = await fetch('https://api.aimlapi.com/v1/images/generations', {
  method: 'POST',
  headers: {
    'Authorization': 'Bearer <YOUR_AIMLAPI_KEY>',
    'Content-Type': 'application/json',
  },
  body: JSON.stringify({
  "model": "luma/uni-1",
  "prompt": "Describe what you want the model to generate.",
  "image_url": "https://example.com/input.jpg"
}),
});

console.log(await response.json());
```

{% endcode %}
{% endtab %}
{% endtabs %}

<details>

<summary>Response</summary>

{% code overflow="wrap" %}

```json
{
  "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"
}
```

{% endcode %}

</details>


---

# Agent Instructions
This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com.

## Querying This Documentation
If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter, and the optional `goal` query parameter:

```
GET https://docs.aimlapi.com/api-references/image-models/luma-ai/uni-1.md?ask=<question>&goal=<endgoal>
```

`ask` is the immediate question: it should be specific, self-contained, and written in natural language.
`goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal.

The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.