# Bria Text-to-Image Base API

> Modelo base de texto a imagen con nueve relaciones de aspecto, hasta 4 imágenes de guía y medio fotográfico o artístico

Genera imágenes a partir de un `prompt` con opciones de `aspect_ratio` de 1:1 a 16:9 y de 1 a 4 imágenes por solicitud (predeterminado: 4). Los controles incluyen `negative_prompt`, `guidance_scale` de 0 a 20, `num_inference_steps` de 20 a 50 y `prompt_enhancement` opcional. `medium` puede ser photography o art, y `guidance` admite hasta 4 imágenes de guía combinadas.

- Model id: `bria/text-to-image/base`
- Made by: Bria AI
- Category: Text to Image
- Output: image
- Price: $0.04 / image (cheapest run $0.16 (160 API credits))
- Run: `POST https://api.doitong.com/v1/run/bria/text-to-image/base`
- Quote: `POST https://api.doitong.com/v1/quote/bria/text-to-image/base`
- Docs page: https://doitong.com/es-ES/developers/models/bria/text-to-image/base

## Pricing

Price: **$0.04 / image**. Billed per generated image (`num_images`, default 1).

The full example input below costs $0.16 = 160 API credits (4 images × 40 API credits).

Prices are the upstream price in USD, paid from the API balance in API credits (1000 API credits = 1 USD). `POST https://api.doitong.com/v1/quote/bria/text-to-image/base` with the same JSON body returns the exact price for that input; the quote is exactly what a run charges. Invalid input is never charged and failed or canceled requests are refunded automatically.

## Input parameters

Send either the canonical name or the native field name (not both). Canonical names are the same across models.

| Parameter | Canonical name | Type | Required | Default | Allowed values / range | Description |
|---|---|---|---|---|---|---|
| `prompt` |  | string | yes |  | ≥ 1 characters | Prompt de texto que dirige la generación de imágenes. |
| `negative_prompt` |  | string | no | `` |  | Prompt de texto negativo para la generación de imágenes. |
| `num_images` | `num_outputs` | integer | no | `4` | 1 – 4 | Número de imágenes solicitado, que se establece en 1 siempre que se utilice cualquier método de guía. |
| `aspect_ratio` |  | enum (string) | no | `1:1` | `1:1`, `2:3`, `3:2`, `3:4`, `4:3`, `4:5`, `5:4`, `9:16`, `16:9` | Relación de aspecto de salida para la generación sin guía; un método de guía toma la relación de su imagen de guía e ignora este ajuste. |
| `seed` |  | integer \| null | no |  | 0 – 2,147,483,647 | Semilla para obtener imágenes reproducibles: un prompt y una semilla idénticos producen una imagen idéntica cuando la versión del modelo no cambia. |
| `num_inference_steps` |  | integer | no | `30` | 20 – 50 | Número opcional de iteraciones del modelo utilizadas para refinar la imagen de salida. |
| `guidance_scale` |  | number | no | `5` | 0 – 20 | Intensidad de seguimiento del prompt para la selección de imágenes, expresada como CFG (Classifier Free Guidance). |
| `prompt_enhancement` |  | boolean | no | `false` |  | Interruptor de mejora del prompt: true favorece imágenes más diversas y creativas al ampliar el prompt proporcionado con variaciones adicionales y descripciones más ricas. |
| `medium` |  | enum (string) \| null | no |  | `photography`, `art` | Medio que se utilizará en las imágenes generadas. Déjalo sin establecer o asigna null para seleccionar automáticamente el medio. |
| `guidance` |  | array of object {image_url, method, scale} | no | `[]` |  | Imágenes de guía de generación, proporcionadas con métodos que pueden combinarse en una inferencia, hasta un máximo de 4 métodos. |
| `guidance[].image_url` |  | string (image URL) | yes |  |  | Imagen de guía codificada en base64 para el método especificado por guidance_method_1; se requiere una imagen cuando se selecciona guidance_method_1. Formatos admitidos: jpeg, jpg, png, webp; el tamaño máximo es de 12 MB. Al combinar métodos de guía, todas las imágenes de guía deben compartir una relación de aspecto, que también determina la relación de aspecto de salida. |
| `guidance[].method` |  | enum (string) | no |  | `controlnet_canny`, `controlnet_depth`, `controlnet_recoloring`, `controlnet_color_grid` | Tipo de guía opcional para la generación. Una sola inferencia puede combinar hasta 4 métodos de guía. |
| `guidance[].scale` |  | number | no | `1` | 0 – 1 | Intensidad del efecto de guía. |

## Example input

Required parameters only:

```json
{
  "prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
}
```

A fuller example:

```json
{
  "prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
}
```

## Run it

Set `DOITONG_API_KEY` to a key from https://doitong.com/developers/dashboard#keys. `?wait=20` returns the finished request in the same call when it is ready within 20 seconds; otherwise poll `GET /requests/{id}` (it also accepts `?wait=`), or pass `webhook_url`.

### curl

```bash
# Run the model; wait up to 20 s for the finished result in the same call
curl -X POST "https://api.doitong.com/v1/run/bria/text-to-image/base?wait=20" \
  -H "Authorization: Bearer $DOITONG_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
  }'

# Still "queued" or "running"? Poll with the id from the response:
curl "https://api.doitong.com/v1/requests/REQUEST_ID?wait=20" \
  -H "Authorization: Bearer $DOITONG_API_KEY"
```

### JavaScript

```javascript
const API = "https://api.doitong.com/v1";
const headers = {
  "Authorization": "Bearer " + process.env.DOITONG_API_KEY,
  "Content-Type": "application/json",
};

// Run the model; wait up to 20 s for the finished result in the same call
let res = await fetch(API + "/run/bria/text-to-image/base?wait=20", {
  method: "POST",
  headers,
  body: JSON.stringify({
    "prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
  }),
});
let request = await res.json();
if (!res.ok) throw new Error(request.error.code + ": " + request.error.message);

// Not finished yet: long-poll until it is
while (request.status === "queued" || request.status === "running") {
  res = await fetch(API + "/requests/" + request.id + "?wait=20", { headers });
  request = await res.json();
}
if (request.status !== "succeeded") throw new Error(JSON.stringify(request.error));
console.log(request.outputs.map((o) => o.url), request.cost.credits + " API credits ($" + request.cost.usd + ")");
```

### Python

```python
import os
import requests

API = "https://api.doitong.com/v1"
headers = {"Authorization": "Bearer " + os.environ["DOITONG_API_KEY"]}

payload = {
    "prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
}

# Run the model; wait up to 20 s for the finished result in the same call
r = requests.post(API + "/run/bria/text-to-image/base", params={"wait": 20}, json=payload, headers=headers)
request = r.json()
if not r.ok:
    raise RuntimeError(request["error"]["code"] + ": " + request["error"]["message"])

# Not finished yet: long-poll until it is
while request["status"] in ("queued", "running"):
    request = requests.get(API + "/requests/" + request["id"], params={"wait": 20}, headers=headers).json()
if request["status"] != "succeeded":
    raise RuntimeError(request["error"])
print([o["url"] for o in request["outputs"]], request["cost"]["credits"], "API credits", "$" + request["cost"]["usd"])
```

### MCP

The MCP server at `https://api.doitong.com/v1/mcp` exposes the tools `search_models`, `get_model`, `quote`, `run`, `get_request`, `cancel_request`, `list_requests`, `create_upload` and `get_account`. A `run` call for this model:

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "run",
    "arguments": {
      "model_id": "bria/text-to-image/base",
      "input": {
        "prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
      },
      "wait_seconds": 20
    }
  }
}
```

## Response

Every call returns a request object. `status` is one of `queued`, `running`, `succeeded`, `failed`, `canceled`. `outputs` lists the generated files with URLs on our storage (kept forever, or 7 days with `?storage=temporary`; `storage` says which); `output` is the model's own result object with the same URLs.

```json
{
  "id": "req_8k2m4q7x1z9c3v5b6n0p2r4t",
  "object": "request",
  "model": "bria/text-to-image/base",
  "status": "succeeded",
  "created_at": "2026-10-20T12:00:00Z",
  "started_at": "2026-10-20T12:00:02Z",
  "completed_at": "2026-10-20T12:00:09Z",
  "queue_position": null,
  "cost": {
    "credits": 160,
    "usd": "0.16",
    "charged": 160,
    "refunded": 0
  },
  "input": {
    "prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
  },
  "output": {
    "images": [
      {
        "url": "https://content.doitong.com/dev-api/2026/10/20/req_8k2m4q7x1z9c3v5b6n0p2r4t/0-output.jpeg",
        "content_type": "image/jpeg",
        "file_name": "0-output.jpeg",
        "file_size": 1843200,
        "width": 1024,
        "height": 768
      }
    ],
    "seed": 42
  },
  "outputs": [
    {
      "type": "image",
      "url": "https://content.doitong.com/dev-api/2026/10/20/req_8k2m4q7x1z9c3v5b6n0p2r4t/0-output.jpeg",
      "content_type": "image/jpeg",
      "file_size": 1843200,
      "width": 1024,
      "height": 768,
      "stored": true
    }
  ],
  "error": null,
  "metrics": {
    "inference_seconds": 6.8
  },
  "urls": {
    "self": "https://api.doitong.com/v1/requests/req_8k2m4q7x1z9c3v5b6n0p2r4t",
    "cancel": "https://api.doitong.com/v1/requests/req_8k2m4q7x1z9c3v5b6n0p2r4t/cancel"
  }
}
```

### Output fields (`output`)

| Field | Type | Description |
|---|---|---|
| `images` | array of object {url, content_type, file_name, file_size, width, height} | Imágenes producidas por el modelo. |
| `seed` | integer | Semilla aplicada durante la generación. |

## Related models

- [Bria Text-to-Image Fast](https://doitong.com/developers/models/bria/text-to-image/fast.md) (`bria/text-to-image/fast`): $0.028 / image
- [Bria Text-to-Image HD](https://doitong.com/developers/models/bria/text-to-image/hd.md) (`bria/text-to-image/hd`): $0.04 / image
- [Bria](https://doitong.com/developers/models/bria/reimagine.md) (`bria/reimagine`): $0.04 / image
- [Bria Background Replace](https://doitong.com/developers/models/bria/background/replace.md) (`bria/background/replace`): $0.04 / image
- [Bria Eraser](https://doitong.com/developers/models/bria/eraser.md) (`bria/eraser`): $0.04 / request
- [Bria Expand Image](https://doitong.com/developers/models/bria/expand.md) (`bria/expand`): $0.04 / request
- [Bria GenFill](https://doitong.com/developers/models/bria/genfill.md) (`bria/genfill`): $0.04 / image
- [Bria Product Dimensions](https://doitong.com/developers/models/bria/product-dimensions.md) (`bria/product-dimensions`): $0.04 / image

## Links

- HTML page: https://doitong.com/developers/models/bria/text-to-image/base
- All models and guides for AI agents: https://doitong.com/developers/llms.txt
- OpenAPI 3.1 with this model's typed request body: https://doitong.com/developers/openapi.json?model=bria/text-to-image/base
- Errors: https://doitong.com/developers/docs/errors
- Model details as JSON: https://api.doitong.com/v1/models/bria/text-to-image/base