# Bria Text-to-Image Base API

> Dokuz en-boy oranı, en fazla 4 yönlendirme görüntüsü ve fotoğraf veya sanat ortamı sunan temel metinden görüntü modeli

`aspect_ratio` için 1:1 ile 16:9 arasında seçenekler ve istek başına 1 ila 4 görüntü (varsayılan 4) ile `prompt` üzerinden görüntüler üretir. Denetimler arasında `negative_prompt`, 0 ile 20 arasında `guidance_scale`, 20 ile 50 arasında `num_inference_steps` ve isteğe bağlı `prompt_enhancement` bulunur. `medium`, photography veya art olabilir; `guidance` en fazla 4 birleştirilmiş yönlendirme görüntüsünü kabul eder.

- 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/tr/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 | Görsel üretimini yönlendiren metin istemi. |
| `negative_prompt` |  | string | no | `` |  | Görsel üretimi için negatif metin istemi. |
| `num_images` | `num_outputs` | integer | no | `4` | 1 – 4 | İstenen görsel sayısı; herhangi bir yönlendirme yöntemi kullanıldığında 1 olarak geçersiz kılınır. |
| `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` | Yönlendirme olmadan üretim için çıktı en-boy oranı; yönlendirme yöntemi bunun yerine oranı yönlendirme görselinden alır ve bu ayarı yok sayar. |
| `seed` |  | integer \| null | no |  | 0 – 2,147,483,647 | Tekrarlanabilir görseller için seed: model sürümü değişmediğinde aynı istem ve seed, aynı görseli üretir. |
| `num_inference_steps` |  | integer | no | `30` | 20 – 50 | Çıktı görselini iyileştirmek için kullanılan model yinelemelerinin isteğe bağlı sayısı. |
| `guidance_scale` |  | number | no | `5` | 0 – 20 | Görsel seçimi için isteme uyum gücü; CFG (Classifier Free Guidance) olarak ifade edilir. |
| `prompt_enhancement` |  | boolean | no | `false` |  | İstem geliştirme anahtarı: true, sağlanan istemi daha zengin açıklamalarla ek varyasyonlara genişleterek daha çeşitli ve yaratıcı görselleri teşvik eder. |
| `medium` |  | enum (string) \| null | no |  | `photography`, `art` | Üretilen görsellerde kullanılacak ortam. Otomatik ortam seçimi için ayarlamadan bırakın veya null atayın. |
| `guidance` |  | array of object {image_url, method, scale} | no | `[]` |  | Tek bir çıkarımda birleştirilebilen yöntemlerle sağlanan üretim yönlendirme görselleri; en fazla 4 yöntem kullanılabilir. |
| `guidance[].image_url` |  | string (image URL) | yes |  |  | guidance_method_1 tarafından belirtilen yöntem için base64 kodlu yönlendirme görseli; guidance_method_1 seçildiğinde görsel zorunludur. Desteklenen biçimler: jpeg, jpg, png, webp; maksimum boyut 12 MB'tır. Yönlendirme yöntemleri birleştirilirken her yönlendirme görseli aynı en-boy oranına sahip olmalı; bu oran çıktı en-boy oranını da belirler. |
| `guidance[].method` |  | enum (string) | no |  | `controlnet_canny`, `controlnet_depth`, `controlnet_recoloring`, `controlnet_color_grid` | Üretim için isteğe bağlı yönlendirme türü. Tek bir çıkarımda en fazla 4 yönlendirme yöntemi birleştirilebilir. |
| `guidance[].scale` |  | number | no | `1` | 0 – 1 | Yönlendirme etkisinin gücü. |

## 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} | Model tarafından oluşturulan görseller. |
| `seed` | integer | Üretim sırasında uygulanan seed. |

## 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