# Luma Uni-1 Text to Image

> Luma Uni-1 turns a text prompt into a single high-fidelity image, with control over aspect ratio and visual style, plus optional web-sourced and reference-image guidance for sharper grounding.


## Overview

- **Endpoint**: `https://fal.run/luma/agent/uni-1/v1/text-to-image`
- **Model ID**: `luma/agent/uni-1/v1/text-to-image`
- **Category**: text-to-image
- **Kind**: inference
**Tags**: realism, typography, stylized



## Pricing

Each image costs **$0.042**. For **$1** you can run this model approximately **23** times.

For more details, see [fal.ai pricing](https://fal.ai/pricing).

## API Information

This model can be used via our HTTP API or more conveniently via our client libraries.
See the input and output schema below, as well as the usage examples.


### Input Schema

The API accepts the following input parameters:


- **`prompt`** (`string`, _required_):
  Text prompt describing the image to generate.
  - Examples: "A manga panel of a stoic samurai overlooking a neon cyberpunk city at dusk."

- **`aspect_ratio`** (`Enum`, _optional_):
  Aspect ratio of the generated image.
  - Options: `"3:1"`, `"2:1"`, `"16:9"`, `"3:2"`, `"1:1"`, `"2:3"`, `"9:16"`, `"1:2"`, `"1:3"`
  - Examples: "16:9"

- **`style`** (`StyleEnum`, _optional_):
  Visual style of the generated image. Default value: `"auto"`
  - Default: `"auto"`
  - Options: `"auto"`, `"manga"`

- **`output_format`** (`Enum`, _optional_):
  Encoding format of the generated image.
  - Options: `"png"`, `"jpeg"`

- **`enable_web_search`** (`boolean`, _optional_):
  When true, the model may consult the web for references.
  - Default: `false`

- **`reference_image_urls`** (`list<string>`, _optional_):
  Optional list of reference image URLs used to guide the generation.
  - Array of string



**Required Parameters Example**:

```json
{
  "prompt": "A manga panel of a stoic samurai overlooking a neon cyberpunk city at dusk."
}
```

**Full Example**:

```json
{
  "prompt": "A manga panel of a stoic samurai overlooking a neon cyberpunk city at dusk.",
  "aspect_ratio": "16:9",
  "style": "auto"
}
```


### Output Schema

The API returns the following output format:

- **`images`** (`list<File>`, _required_):
  The generated image(s).
  - Array of File



**Example Response**:

```json
{
  "images": [
    {
      "url": "",
      "content_type": "image/png",
      "file_name": "z9RV14K95DvU.png",
      "file_size": 4404019
    }
  ]
}
```


## Usage Examples

### cURL

```bash
curl --request POST \
  --url https://fal.run/luma/agent/uni-1/v1/text-to-image \
  --header "Authorization: Key $FAL_KEY" \
  --header "Content-Type: application/json" \
  --data '{
     "prompt": "A manga panel of a stoic samurai overlooking a neon cyberpunk city at dusk."
   }'
```

### Python

Ensure you have the Python client installed:

```bash
pip install fal-client
```

Then use the API client to make requests:

```python
import fal_client

def on_queue_update(update):
    if isinstance(update, fal_client.InProgress):
        for log in update.logs:
           print(log["message"])

result = fal_client.subscribe(
    "luma/agent/uni-1/v1/text-to-image",
    arguments={
        "prompt": "A manga panel of a stoic samurai overlooking a neon cyberpunk city at dusk."
    },
    with_logs=True,
    on_queue_update=on_queue_update,
)
print(result)
```

### JavaScript

Ensure you have the JavaScript client installed:

```bash
npm install --save @fal-ai/client
```

Then use the API client to make requests:

```javascript
import { fal } from "@fal-ai/client";

const result = await fal.subscribe("luma/agent/uni-1/v1/text-to-image", {
  input: {
    prompt: "A manga panel of a stoic samurai overlooking a neon cyberpunk city at dusk."
  },
  logs: true,
  onQueueUpdate: (update) => {
    if (update.status === "IN_PROGRESS") {
      update.logs.map((log) => log.message).forEach(console.log);
    }
  },
});
console.log(result.data);
console.log(result.requestId);
```


## Additional Resources

### Documentation

- [Model Playground](https://fal.ai/models/luma/agent/uni-1/v1/text-to-image)
- [API Documentation](https://fal.ai/models/luma/agent/uni-1/v1/text-to-image/api)
- [OpenAPI Schema](https://fal.ai/api/openapi/queue/openapi.json?endpoint_id=luma/agent/uni-1/v1/text-to-image)

### fal.ai Platform

- [Platform Documentation](https://docs.fal.ai)
- [Python Client](https://docs.fal.ai/clients/python)
- [JavaScript Client](https://docs.fal.ai/clients/javascript)