# Fibo Gen 1.5 Text to Image API

> Modèle texte vers image avec prompts simples ou structurés en JSON et sortie 1MP ou 4MP, sans image de référence

Génère des images à partir d’un `prompt` ou d’un `structured_prompt`, avec `resolution` réglée sur 1MP ou 4MP et neuf formats. `seed` rend les résultats reproductibles, et le prompt structuré utilisé est renvoyé. L’ensemble des entrées est plus réduit que dans le Fibo précédent, sans prompt négatif, nombre d’étapes ni image de référence.

- Model id: `bria/fibo-gen-1.5/text-to-image`
- Made by: Bria AI
- Category: Text to Image
- Output: image
- Price: $0.04 / image (cheapest run $0.04 (40 API credits))
- Run: `POST https://api.doitong.ru/v1/run/bria/fibo-gen-1.5/text-to-image`
- Quote: `POST https://api.doitong.ru/v1/quote/bria/fibo-gen-1.5/text-to-image`
- Docs page: https://doitong.com/fr/developers/models/bria/fibo-gen-1.5/text-to-image

## Pricing

Price: **$0.04 / image**. Billed per generated image.

The full example input below costs $0.04 = 40 API credits (1 image × 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.ru/v1/quote/bria/fibo-gen-1.5/text-to-image` 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

| Parameter | Canonical name | Type | Required | Default | Allowed values / range | Description |
|---|---|---|---|---|---|---|
| `prompt` |  | string \| null | no |  |  | Prompt utilisé pour générer des images. |
| `structured_prompt` |  | object {short_description, objects, background_setting, lighting, aesthetics, photographic_characteristics, style_medium, text_render, context, artistic_style} \| null | no |  |  | Prompt structuré utilisé pour la génération d’image. |
| `structured_prompt.short_description` |  | string \| null | no |  |  | Brève description de l’image de sortie souhaitée. |
| `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 | `[]` |  | Spécifiez le contenu de l’image générée sous forme de liste, en indiquant les attributs de chaque objet et ses relations avec les autres objets représentés. |
| `structured_prompt.objects[].description` |  | string \| null | no |  |  | Description de l’objet de sortie souhaité. |
| `structured_prompt.objects[].location` |  | string \| null | no |  |  | Position de l’objet dans l’image. |
| `structured_prompt.objects[].relationship` |  | string | yes |  |  | Relation de l’objet avec les autres objets de l’image. |
| `structured_prompt.objects[].relative_size` |  | string \| null | no |  |  | Taille de l’objet par rapport à l’image. |
| `structured_prompt.objects[].shape_and_color` |  | string \| null | no |  |  | Forme et couleur de l’objet. |
| `structured_prompt.objects[].texture` |  | string \| null | no |  |  | Texture de l’objet. |
| `structured_prompt.objects[].appearance_details` |  | string \| null | no |  |  | Détails décrivant l’apparence de l’objet. |
| `structured_prompt.objects[].number_of_objects` |  | integer \| null | no |  |  | Nombre d’objets dans l’image. |
| `structured_prompt.objects[].pose` |  | string \| null | no |  |  | Pose de l’objet représenté. |
| `structured_prompt.objects[].expression` |  | string \| null | no |  |  | Expression affichée par l’objet représenté. |
| `structured_prompt.objects[].clothing` |  | string \| null | no |  |  | Vêtements portés par l’objet représenté. |
| `structured_prompt.objects[].action` |  | string \| null | no |  |  | Action effectuée par l’objet représenté. |
| `structured_prompt.objects[].gender` |  | string \| null | no |  |  | Genre de l’objet représenté. |
| `structured_prompt.objects[].skin_tone_and_texture` |  | string \| null | no |  |  | Texture et teinte de peau de l’objet représenté. |
| `structured_prompt.objects[].orientation` |  | string \| null | no |  |  | Orientation de l’objet représenté. |
| `structured_prompt.background_setting` |  | string \| null | no |  |  | Arrière-plan de l’image générée. |
| `structured_prompt.lighting` |  | object {conditions, direction, shadows} \| null | no |  |  | Éclairage de l’image générée. |
| `structured_prompt.lighting.conditions` |  | string \| null | no |  |  | Conditions d’éclairage de l’image générée. |
| `structured_prompt.lighting.direction` |  | string \| null | no |  |  | Direction de l’éclairage de l’image générée. |
| `structured_prompt.lighting.shadows` |  | string \| null | no |  |  | Ombres à représenter dans l’image générée. |
| `structured_prompt.aesthetics` |  | object {composition, color_scheme, mood_atmosphere, aesthetic_score, preference_score} \| null | no |  |  | Qualités esthétiques de l’image générée. |
| `structured_prompt.aesthetics.composition` |  | string \| null | no |  |  | Composition de l’image générée. |
| `structured_prompt.aesthetics.color_scheme` |  | string \| null | no |  |  | Palette de couleurs de l’image générée. |
| `structured_prompt.aesthetics.mood_atmosphere` |  | string \| null | no |  |  | Ambiance et atmosphère de l’image générée. |
| `structured_prompt.aesthetics.aesthetic_score` |  | string \| null | no |  |  | Score esthétique de l’image en cours de génération. |
| `structured_prompt.aesthetics.preference_score` |  | string \| null | no |  |  | Score de préférence de l’image en cours de génération. |
| `structured_prompt.photographic_characteristics` |  | object {depth_of_field, focus, camera_angle, lens_focal_length} \| null | no |  |  | Propriétés photographiques de l’image générée. |
| `structured_prompt.photographic_characteristics.depth_of_field` |  | string \| null | no |  |  | Profondeur de champ de l’image générée. |
| `structured_prompt.photographic_characteristics.focus` |  | string \| null | no |  |  | Mise au point de l’image générée. |
| `structured_prompt.photographic_characteristics.camera_angle` |  | string \| null | no |  |  | Angle de caméra de l’image générée. |
| `structured_prompt.photographic_characteristics.lens_focal_length` |  | string \| null | no |  |  | Réglage de l’objectif de l’image générée, exprimé comme une longueur focale. |
| `structured_prompt.style_medium` |  | string \| null | no |  |  | Médium stylistique de l’image générée. |
| `structured_prompt.text_render` |  | array of any \| null | no | `[]` |  | Liste des éléments textuels à inclure dans l’image. |
| `structured_prompt.context` |  | string \| null | no |  |  | Contexte de l’image générée. |
| `structured_prompt.artistic_style` |  | string \| null | no |  |  | Style artistique de l’image générée. |
| `seed` |  | integer | no | `5555` |  | Seed contrôlant l’aléatoire pour obtenir des résultats reproductibles. |
| `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` | Proportions de l’image ; valeurs disponibles : 1:1, 2:3, 3:2, 3:4, 4:3, 4:5, 5:4, 9:16, 16:9. |
| `resolution` |  | enum (string) | no | `1MP` | `1MP`, `4MP` | Résolution de l'image générée. |

## 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.ru/v1/run/bria/fibo-gen-1.5/text-to-image?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.ru/v1/requests/REQUEST_ID?wait=20" \
  -H "Authorization: Bearer $DOITONG_API_KEY"
```

### JavaScript

```javascript
const API = "https://api.doitong.ru/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-gen-1.5/text-to-image?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.ru/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-gen-1.5/text-to-image", 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.ru/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-gen-1.5/text-to-image",
      "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-gen-1.5/text-to-image",
  "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": 40,
    "usd": "0.04",
    "charged": 40,
    "refunded": 0
  },
  "input": {
    "prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
  },
  "output": {
    "image": {
      "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
    },
    "images": [
      {}
    ],
    "structured_prompt": {}
  },
  "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.ru/v1/requests/req_8k2m4q7x1z9c3v5b6n0p2r4t",
    "cancel": "https://api.doitong.ru/v1/requests/req_8k2m4q7x1z9c3v5b6n0p2r4t/cancel"
  }
}
```

### Output fields (`output`)

| Field | Type | Description |
|---|---|---|
| `image` | object {url, content_type, file_name, file_size, width, height} | Image produite par le modèle. |
| `images` | array of object | Images produites par la génération. |
| `structured_prompt` | object | Prompt actuellement utilisé. |

## Related models

- [FLUX.1 \[dev\]](https://doitong.com/developers/models/flux/dev.md) (`flux/dev`): $0.025 / megapixel
- [FLUX.1 \[schnell\]](https://doitong.com/developers/models/flux/schnell.md) (`flux/schnell`): $0.003 / megapixel
- [FLUX.2 \[dev\]](https://doitong.com/developers/models/flux-2.md) (`flux-2`): $0.012 / megapixel
- [FLUX.2 \[pro\]](https://doitong.com/developers/models/flux-2-pro.md) (`flux-2-pro`): $0.015 / megapixel of output image
- [GPT Image 2.5 Text to Image](https://doitong.com/developers/models/openai/gpt-image-2.5/flare/text-to-image.md) (`openai/gpt-image-2.5/flare/text-to-image`): from $0.008 / image
- [Ideogram V4.5](https://doitong.com/developers/models/ideogram/v4.5.md) (`ideogram/v4.5`): from $0.03 / image
- [Nano Banana 2](https://doitong.com/developers/models/nano-banana-2.md) (`nano-banana-2`): from $0.06 / image
- [Nano Banana Pro](https://doitong.com/developers/models/nano-banana-pro.md) (`nano-banana-pro`): from $0.15 / image

## Links

- HTML page: https://doitong.com/developers/models/bria/fibo-gen-1.5/text-to-image
- 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-gen-1.5/text-to-image
- Errors: https://doitong.com/developers/docs/errors
- Model details as JSON: https://api.doitong.ru/v1/models/bria/fibo-gen-1.5/text-to-image