# Fibo · Structured Prompt API

> Convierte un prompt o una imagen de referencia en la descripción JSON estructurada de Fibo en lugar de renderizar una imagen

Endpoint con estilo de modelo lingüístico que devuelve el prompt estructurado de una imagen en lugar de la imagen misma. Las entradas son `prompt`, un `structured_prompt` existente o una `image_url` de referencia, además de `seed`. La salida JSON incluye campos como estética, iluminación, objetos, características fotográficas, descripción breve, medio artístico y texto que se renderizará.

- Model id: `bria/fibo/generate/structured_prompt`
- Made by: Bria AI
- Category: LLM
- Output: json
- Price: $0.01 / request (cheapest run $0.01 (10 API credits))
- Run: `POST https://api.doitong.com/v1/run/bria/fibo/generate/structured_prompt`
- Quote: `POST https://api.doitong.com/v1/quote/bria/fibo/generate/structured_prompt`
- Docs page: https://doitong.com/es/developers/models/bria/fibo/generate/structured_prompt

## Pricing

Price: **$0.01 / request**. Billed once per request.

The full example input below costs $0.01 = 10 API credits (1 request × 10 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/fibo/generate/structured_prompt` 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 \| null | no |  |  | Prompt utilizado para generar imágenes. |
| `structured_prompt` |  | object {short_description, objects, background_setting, lighting, aesthetics, photographic_characteristics, style_medium, text_render, context, artistic_style, trigger_word, sub_trigger_word, art_direction, action_description, actor_prefix} \| null | no |  |  | Prompt estructurado utilizado para la generación de imágenes. |
| `structured_prompt.short_description` |  | string \| null | no |  |  | Descripción breve de la imagen de salida prevista. |
| `structured_prompt.objects` |  | array of object {description, location, relationship, relative_size, shape_and_color, texture, appearance_details, number_of_objects, pose, expression, clothing, action, gender, skin_tone_and_texture, orientation} \| null | no | `[]` |  | Especifique el contenido de la imagen generada como una lista, registrando los atributos de cada objeto y sus relaciones con los demás objetos representados. |
| `structured_prompt.objects[].description` |  | string \| null | no |  |  | Descripción del objeto de salida previsto. |
| `structured_prompt.objects[].location` |  | string \| null | no |  |  | Posición del objeto dentro de la imagen. |
| `structured_prompt.objects[].relationship` |  | string | yes |  |  | Relación del objeto con los demás objetos de la imagen. |
| `structured_prompt.objects[].relative_size` |  | string \| null | no |  |  | Tamaño del objeto en relación con la imagen. |
| `structured_prompt.objects[].shape_and_color` |  | string \| null | no |  |  | Forma y color del objeto. |
| `structured_prompt.objects[].texture` |  | string \| null | no |  |  | Textura del objeto. |
| `structured_prompt.objects[].appearance_details` |  | string \| null | no |  |  | Detalles que describen el aspecto del objeto. |
| `structured_prompt.objects[].number_of_objects` |  | integer \| null | no |  |  | Cantidad de objetos dentro de la imagen. |
| `structured_prompt.objects[].pose` |  | string \| null | no |  |  | Pose del objeto representado. |
| `structured_prompt.objects[].expression` |  | string \| null | no |  |  | Expresión mostrada por el objeto representado. |
| `structured_prompt.objects[].clothing` |  | string \| null | no |  |  | Ropa que lleva el objeto representado. |
| `structured_prompt.objects[].action` |  | string \| null | no |  |  | Acción realizada por el objeto representado. |
| `structured_prompt.objects[].gender` |  | string \| null | no |  |  | Género del objeto representado. |
| `structured_prompt.objects[].skin_tone_and_texture` |  | string \| null | no |  |  | Textura y tono de piel del objeto representado. |
| `structured_prompt.objects[].orientation` |  | string \| null | no |  |  | Orientación del objeto representado. |
| `structured_prompt.background_setting` |  | string \| null | no |  |  | Entorno del fondo de la imagen generada. |
| `structured_prompt.lighting` |  | object {conditions, direction, shadows} \| null | no |  |  | Iluminación de la imagen generada. |
| `structured_prompt.lighting.conditions` |  | string \| null | no |  |  | Condiciones de iluminación de la imagen generada. |
| `structured_prompt.lighting.direction` |  | string \| null | no |  |  | Dirección de la iluminación de la imagen generada. |
| `structured_prompt.lighting.shadows` |  | string \| null | no |  |  | Sombras que se representarán en la imagen generada. |
| `structured_prompt.aesthetics` |  | object {composition, color_scheme, mood_atmosphere, aesthetic_score, preference_score} \| null | no |  |  | Cualidades estéticas de la imagen generada. |
| `structured_prompt.aesthetics.composition` |  | string \| null | no |  |  | Composición de la imagen generada. |
| `structured_prompt.aesthetics.color_scheme` |  | string \| null | no |  |  | Paleta de colores de la imagen generada. |
| `structured_prompt.aesthetics.mood_atmosphere` |  | string \| null | no |  |  | Estado de ánimo y atmósfera de la imagen generada. |
| `structured_prompt.aesthetics.aesthetic_score` |  | string \| null | no |  |  | Puntuación estética de la imagen que se está generando. |
| `structured_prompt.aesthetics.preference_score` |  | string \| null | no |  |  | Puntuación de preferencia de la imagen que se está generando. |
| `structured_prompt.photographic_characteristics` |  | object {depth_of_field, focus, camera_angle, lens_focal_length} \| null | no |  |  | Propiedades fotográficas de la imagen generada. |
| `structured_prompt.photographic_characteristics.depth_of_field` |  | string \| null | no |  |  | Profundidad de campo de la imagen generada. |
| `structured_prompt.photographic_characteristics.focus` |  | string \| null | no |  |  | Enfoque de la imagen generada. |
| `structured_prompt.photographic_characteristics.camera_angle` |  | string \| null | no |  |  | Ángulo de cámara de la imagen generada. |
| `structured_prompt.photographic_characteristics.lens_focal_length` |  | string \| null | no |  |  | Configuración del objetivo de la imagen generada, expresada como distancia focal. |
| `structured_prompt.style_medium` |  | string \| null | no |  |  | Medio estilístico de la imagen generada. |
| `structured_prompt.text_render` |  | array of any \| null | no | `[]` |  | Lista de entradas de texto que se incluirán en la imagen. |
| `structured_prompt.context` |  | string \| null | no |  |  | Contexto de la imagen generada. |
| `structured_prompt.artistic_style` |  | string \| null | no |  |  | Estilo artístico de la imagen generada. |
| `structured_prompt.trigger_word` |  | string \| null | no |  |  |  |
| `structured_prompt.sub_trigger_word` |  | string \| null | no |  |  |  |
| `structured_prompt.art_direction` |  | string \| null | no |  |  |  |
| `structured_prompt.action_description` |  | string \| null | no |  |  |  |
| `structured_prompt.actor_prefix` |  | string \| null | no |  |  |  |
| `image_url` | `image` | string (image URL) \| null | no |  |  | Imagen de referencia proporcionada como archivo o URL. |
| `seed` |  | integer | no | `5555` |  | Semilla que controla la aleatoriedad para obtener resultados reproducibles. |

File parameters (`image`) take a public `https://` URL, a `data:` URI up to 10 MB, or the `file_url` of an upload from `POST /files`.

## Example input

Required parameters only:

```json
{}
```

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/fibo/generate/structured_prompt?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/fibo/generate/structured_prompt?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/fibo/generate/structured_prompt", 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/fibo/generate/structured_prompt",
      "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/fibo/generate/structured_prompt",
  "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": 10,
    "usd": "0.01",
    "charged": 10,
    "refunded": 0
  },
  "input": {
    "prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
  },
  "output": {
    "short_description": "string",
    "objects": [
      {
        "description": "string",
        "location": "string",
        "relationship": "string",
        "relative_size": "string",
        "shape_and_color": "string",
        "texture": "string",
        "appearance_details": "string",
        "number_of_objects": 1,
        "pose": "string",
        "expression": "string",
        "clothing": "string",
        "action": "string",
        "gender": "string",
        "skin_tone_and_texture": "string",
        "orientation": "string"
      }
    ],
    "background_setting": "string",
    "lighting": {
      "conditions": "string",
      "direction": "string",
      "shadows": "string"
    },
    "aesthetics": {
      "composition": "string",
      "color_scheme": "string",
      "mood_atmosphere": "string",
      "aesthetic_score": "string",
      "preference_score": "string"
    },
    "photographic_characteristics": {
      "depth_of_field": "string",
      "focus": "string",
      "camera_angle": "string",
      "lens_focal_length": "string"
    },
    "style_medium": "string",
    "text_render": [],
    "context": "string",
    "artistic_style": "string"
  },
  "outputs": [
    {
      "type": "file",
      "url": "https://content.doitong.com/dev-api/2026/10/20/req_8k2m4q7x1z9c3v5b6n0p2r4t/0-output.jpeg",
      "content_type": "image/jpeg",
      "file_size": 1843200,
      "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 |
|---|---|---|
| `short_description` | string \| null | Descripción breve de la imagen de salida prevista. |
| `objects` | array of object {description, location, relationship, relative_size, shape_and_color, texture, appearance_details, number_of_objects, pose, expression, clothing, action, gender, skin_tone_and_texture, orientation} \| null | Especifique el contenido de la imagen generada como una lista, registrando los atributos de cada objeto y sus relaciones con los demás objetos representados. |
| `background_setting` | string \| null | Entorno del fondo de la imagen generada. |
| `lighting` | object {conditions, direction, shadows} \| null | Iluminación de la imagen generada. |
| `aesthetics` | object {composition, color_scheme, mood_atmosphere, aesthetic_score, preference_score} \| null | Cualidades estéticas de la imagen generada. |
| `photographic_characteristics` | object {depth_of_field, focus, camera_angle, lens_focal_length} \| null | Propiedades fotográficas de la imagen generada. |
| `style_medium` | string \| null | Medio estilístico de la imagen generada. |
| `text_render` | array of any \| null | Lista de entradas de texto que se incluirán en la imagen. |
| `context` | string \| null | Contexto de la imagen generada. |
| `artistic_style` | string \| null | Estilo artístico de la imagen generada. |

## Related models

- [Fibo](https://doitong.com/developers/models/bria/fibo/generate.md) (`bria/fibo/generate`): $0.04 / image
- [Fibo Edit \[Structured Instruction\]](https://doitong.com/developers/models/bria/fibo-edit/edit/structured_instruction.md) (`bria/fibo-edit/edit/structured_instruction`): $0.01 / request
- [Fibo Lite · Structured Prompt](https://doitong.com/developers/models/bria/fibo-lite/generate/structured_prompt.md) (`bria/fibo-lite/generate/structured_prompt`): $0.008 / request
- [Bytedance Seed V2 Mini](https://doitong.com/developers/models/bytedance/seed/v2/mini.md) (`bytedance/seed/v2/mini`): $0.0001 / 1000 tokens
- [Mureka 9.5 Lyrics Generation](https://doitong.com/developers/models/mureka/api/generate/lyrics.md) (`mureka/api/generate/lyrics`): $0.0135 / request
- [Nemotron 3 Nano Omni](https://doitong.com/developers/models/nvidia/nemotron-3-nano-omni.md) (`nvidia/nemotron-3-nano-omni`): $0.01 / run
- [NVIDIA Nemotron 3.5 Super Text](https://doitong.com/developers/models/nvidia/nemotron-3-5-super/text.md) (`nvidia/nemotron-3-5-super/text`): $0.01 / run
- [OpenRouter](https://doitong.com/developers/models/openrouter/router.md) (`openrouter/router`): $0.01 / usage unit

## Links

- HTML page: https://doitong.com/developers/models/bria/fibo/generate/structured_prompt
- 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/fibo/generate/structured_prompt
- Errors: https://doitong.com/developers/docs/errors
- Model details as JSON: https://api.doitong.com/v1/models/bria/fibo/generate/structured_prompt