# Fibo Gen 1.5 Text to Image API

> ᡥᡡᠯᠠᡥᠠ ᡤᡳᠰᡠᠨ ᡩᡝᠵᡳ ᠵᠠᠯᠠᠨ ᠣᠪᡠᠮᠪᡳ᠂ ᠵᠠᠯᠠᠨ ᠪᡝ ᠨᡠᠮᡝ ᠪᡠᡨᡠᠨ JSON ᡳ ᠵᠠᡵᡤᠠ ᠪᡝ ᠠᠪᡠᠮᠪᡳ᠂ 1MP ᠣᠴᡳ 4MP ᠵᠠᠯᠠᠨ ᠪᡝ ᠪᠠᡵᡠᠮᠪᡳ᠂ ᠵᠠᡳ ᠰᡳᠨᡩᠠᡥᠠ ᠳᠠᠮᡠ ᠠᡴᡡ

`prompt` ᠵᠠᠯᡳ ᡝᠮᡠᠯᡝ ᠵᠠᠯᡳ ᠪᡝ `structured_prompt` ᠵᠠᠯᡳ ᡤᠠᠳᠠᠨ ᠪᡠᠶᡝᠮᡝ, `resolution` ᠪᡝ 1MP ᠠᡳ 4MP ᠰᡝᠮᡝ ᠵᠠᠯᡳ ᠪᡝ ᡳᠯᡳᠨ ᠵᠠᠯᡳ ᠪᡠᠶᡝᠮᡝ. ᡳᠨᡝ ᠵᠠᠯᡳ ᠪᡝ ᠵᠠᠯᡳᠨ ᡥᡡᠯᠠᠨ ᠵᠠᠯᡳ ᠵᡠᠯᡝ ᠵᠠᠯᡳ ᠰᡝᠮᡝ ᠪᡠᠶᡝᠮᡝ. `seed` ᠪᡝ ᠨᡝᠮᡝᠨ ᠪᡠᠶᡝᠮᡝ ᠰᡳᠨᡝᡥᡝᠨ ᠠᠮᠠᠯᡤᠠ ᠰᠠᠮᠠ ᠪᡳᠰᡳᡵᡝᠩᡤᡝ᠂ ᡝᠮᡠᠯᡝ ᠵᠠᠯᡳ ᠰᠣᠯᡥᠣᠨ ᡥᡡᠯᠠᠨ ᠪᡠᠶᡝᠮᡝ ᡩᠠᠮᡝ. ᡝᠨᡳ ᡩᡠᠯᡝᠮᡝ ᠮᠣᠳᡝᠯ ᡩᡝ ᡠᠯᡥᡳ ᠮᠣᠳᡝᠯ ᠵᡠᠯᡝ ᠵᠠᠯᡳ ᡝᠮᡠᠯᡝ ᠪᡠᠮᡝ ᠪᡳᠰᡳᡵᡝᠩᡤᡝ᠂ ᠣᠯᡥᠣ ᡥᡡᠯᠠᠨ᠂ ᡝᠵᡝᠨ ᠵᠠᠯᡳ ᡥᡳᠰᡝ ᠠᠨᠠ ᡩᡝᡵᡝ ᡤᠠᠳᠠᠨ ᠠᡴᡡ.

- 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/mnc/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 |  |  | ᡤᠠᠳᠠᠨ ᠪᡠᠶᡝᠮᡝᠮᡝ ᠠᠰᡥᠠᠨ ᡥᡡᠯᠠᠨ. |
| `structured_prompt` |  | object {short_description, objects, background_setting, lighting, aesthetics, photographic_characteristics, style_medium, text_render, context, artistic_style} \| null | no |  |  | ᡤᠠᠳᠠᠨᡳ ᠪᡠᠶᡝᠮᡝᠮᡝ ᠠᠰᡥᠠᠨ ᠵᠠᠰᠠᠨᡳ ᡥᡡᠯᠠᠨ. |
| `structured_prompt.short_description` |  | string \| null | no |  |  | ᠪᡠᠶᡝᠮᡝᠨᡳ ᡤᠠᠳᠠᠨᡳ ᠵᡠᠯᡝ ᡩᠠᠯᡵᡳ ᠪᡳᠴᡳᠪᡝᠨ᠈ |
| `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 | `[]` |  | ᠪᡠᠶᡝᠮᡝᠨᡳ ᡤᠠᠳᠠᠨᡳ ᠪᡳᠴᡳᠪᡝᠨᡳ ᠵᡠᠯᡝᠨᡳ ᡴᡝᠮᡠᠨᡳ ᡩᠠᠯᡵᡳ ᠠᠴᡳ᠈ |
| `structured_prompt.objects[].description` |  | string \| null | no |  |  | ᠪᡠᠶᡝᠮᡝᠨᡳ ᠪᡠᠮᡝᠨᡳ ᡩᠠᠯᡵᡳ ᠪᡳᠴᡳᠪᡝᠨ᠈ |
| `structured_prompt.objects[].location` |  | string \| null | no |  |  | ᠪᡠᠮᡝᠨᡳ ᡤᠠᠳᠠᠨᡩᡝ ᠠᠰᡠᠯᠠᠮᠪᡳ᠈ |
| `structured_prompt.objects[].relationship` |  | string | yes |  |  | ᠪᡠᠮᡝᠨᡳ ᡤᠠᠳᠠᠨᡳ ᡩᠠᠯᡮᡳ ᠵᡠᠯᡝ᠈ |
| `structured_prompt.objects[].relative_size` |  | string \| null | no |  |  | ᠪᡠᠮᡝᠨᡳ ᠠᠮᠪᠠᠨᡳ ᠵᡠᠯᡝ᠈ |
| `structured_prompt.objects[].shape_and_color` |  | string \| null | no |  |  | ᠪᡠᠮᡝᠨᡳ ᠮᠠᠶᠠᠨ ᠮᠠᠩᡤᡳᠨᡳ ᡤᠠᠯᠠᠨ᠈ |
| `structured_prompt.objects[].texture` |  | string \| null | no |  |  | ᠪᡠᠮᡝᠨᡳ ᠮᠠᠶᠠᠨᡳ ᡤᠠᠯᠠᠨ᠈ |
| `structured_prompt.objects[].appearance_details` |  | string \| null | no |  |  | ᠪᡠᠮᡝᠨᡳ ᡤᠠᠯᠠᠨᡳ ᡩᠠᠯᡵᡳ ᠪᡳᠴᡳᠪᡝᠨ᠈ |
| `structured_prompt.objects[].number_of_objects` |  | integer \| null | no |  |  | ᡤᠠᠳᠠᠨᡳ ᠪᡠᠮᡝᠨᡳ ᠵᡠᠯᡝᠨᡳ ᡤᡝᠪᡠᠨ᠈ |
| `structured_prompt.objects[].pose` |  | string \| null | no |  |  | ᠪᡠᠮᡝᠨᡳ ᡶᡳᠶᡝᠯᡝᠮᡝᠨᡳ ᠮᠠᠶᠠᠨ᠈ |
| `structured_prompt.objects[].expression` |  | string \| null | no |  |  | ᠪᡠᠮᡝᠨᡳ ᡩᠠᠯᡵᡳ ᡝᠵᡝᠨᡳ ᠵᠠᠯᡤᠠᠶᡳ᠈ |
| `structured_prompt.objects[].clothing` |  | string \| null | no |  |  | ᠪᡠᠮᡝᠨᡳ ᠵᠠᠯᡠᠪᡠᡵᡝ ᠪᡠᠰᡝᠨᡳ᠈ |
| `structured_prompt.objects[].action` |  | string \| null | no |  |  | ᠪᡠᠮᡝᠨᡳ ᠠᠰᡠᠯᠠᡥᠠ ᡝᡵᡝᠮᠪᡳ᠈ |
| `structured_prompt.objects[].gender` |  | string \| null | no |  |  | ᠪᡠᠮᡝᠨᡳ ᡴᡝᠮᡠᠨᡳ ᠵᡠᠯᡝ᠈ |
| `structured_prompt.objects[].skin_tone_and_texture` |  | string \| null | no |  |  | ᠪᡠᠮᡝᠨᡳ ᠰᡳᠨᡩᠠᠨ ᡨᡝᠨᡝᠮᡝ ᠵᡠᠯᡝ᠈ |
| `structured_prompt.objects[].orientation` |  | string \| null | no |  |  | ᠪᡠᠮᡝᠨᡳ ᠵᡠᠯᡝᠨᡳ ᠮᠠᠶᠠᠨ᠈ |
| `structured_prompt.background_setting` |  | string \| null | no |  |  | ᠪᡠᠶᡝᠮᡝᠨᡳ ᠵᡠᠯᡝ ᠵᡝᠯᡥᡝᠨᡳ ᠵᡠᠯᡝ᠈ |
| `structured_prompt.lighting` |  | object {conditions, direction, shadows} \| null | no |  |  | ᠪᡠᠶᡝᠮᡝᠨᡳ ᠵᡝᠯᡥᡝᠨᡳ ᠵᡠᠯᡝ᠈ |
| `structured_prompt.lighting.conditions` |  | string \| null | no |  |  | ᠪᡠᠶᡝᠮᡝᠨᡳ ᠵᡝᠯᡥᡝᠨᡳ ᠶᠠᠯᡳ᠈ |
| `structured_prompt.lighting.direction` |  | string \| null | no |  |  | ᠪᡠᠶᡝᠮᡝᠨᡳ ᠵᡝᠯᡥᡝᠨᡳ ᡩᠠᠯᡮᡳ᠈ |
| `structured_prompt.lighting.shadows` |  | string \| null | no |  |  | ᠪᡠᠶᡝᠮᡝᠨᡳ ᠰᠠᠯᡤᠠᠨᡳ ᠵᡠᠯᡝ᠈ |
| `structured_prompt.aesthetics` |  | object {composition, color_scheme, mood_atmosphere, aesthetic_score, preference_score} \| null | no |  |  | ᠪᡠᠶᡝᠮᡝᠨᡳ ᠰᠠᠶᠠᠨᡳ ᠵᡠᠯᡝ᠈ |
| `structured_prompt.aesthetics.composition` |  | string \| null | no |  |  | ᠪᡠᠶᡝᠮᡝᠨᡳ ᡝᠮᡴᡝᠨᡳ ᠵᡠᠯᡝ᠈ |
| `structured_prompt.aesthetics.color_scheme` |  | string \| null | no |  |  | ᠪᡠᠶᡝᠮᡝᠨᡳ ᠮᠠᠩᡤᡳᠨᡳ ᠵᡠᠯᡝ᠈ |
| `structured_prompt.aesthetics.mood_atmosphere` |  | string \| null | no |  |  | ᠪᠠᠶᠠᠨ ᠰᡡᠨᡝᠨᡳ ᠠᠮᡤᠠᠨᡳ ᠵᡠᠯᡝ᠈ |
| `structured_prompt.aesthetics.aesthetic_score` |  | string \| null | no |  |  | ᠪᡠᠶᡝᠮᡝᠮᡝ ᠠᠰᡥᠠᠨ ᠤᠯᡤᡳᠨᡳ ᠪᡳᠯᡝᠪᡠᡵᡝᠩᡤᡝ. |
| `structured_prompt.aesthetics.preference_score` |  | string \| null | no |  |  | ᠪᡠᠶᡝᠮᡝᠮᡝ ᠠᠰᡥᠠᠨ ᠠᡵᡤᠠᠨᡳ ᠪᡳᠯᡝᠪᡠᡵᡝᠩᡤᡝ. |
| `structured_prompt.photographic_characteristics` |  | object {depth_of_field, focus, camera_angle, lens_focal_length} \| null | no |  |  | ᠪᡠᠶᡝᠮᡝᠨᡳ ᡤᠠᠳᠠᠨᡳ ᠰᠠᠶᠠᠨᡳ ᡩᠠᠯᡵᡳ᠈ |
| `structured_prompt.photographic_characteristics.depth_of_field` |  | string \| null | no |  |  | ᠪᡠᠶᡝᠮᡝᠨᡳ ᡤᠠᠳᠠᠨᡳ ᡥᡡᠯᡳᠨᡳ ᠵᡠᠯᡝ᠈ |
| `structured_prompt.photographic_characteristics.focus` |  | string \| null | no |  |  | ᠪᡠᠶᡝᠮᡝᠨᡳ ᡤᠠᠳᠠᠨᡳ ᡳᠯᠠᠨᡤᠠᠨᡳ ᠵᡠᠯᡝ᠈ |
| `structured_prompt.photographic_characteristics.camera_angle` |  | string \| null | no |  |  | ᠪᡠᠶᡝᠮᡝᠨᡳ ᡤᠠᠳᠠᠨᡳ ᡩᠠᠯᡮᡳ ᠠᠩᡤᠠᠨᡳ ᠵᡠᠯᡝ᠈ |
| `structured_prompt.photographic_characteristics.lens_focal_length` |  | string \| null | no |  |  | ᠪᡠᠶᡝᠮᡝᠨᡳ ᡤᠠᠳᠠᠨᡳ ᠰᡝᡵᡝ ᠵᡠᠯᡝ᠈ |
| `structured_prompt.style_medium` |  | string \| null | no |  |  | ᠪᡠᠶᡝᠮᡝᠨᡳ ᠰᠠᠶᠠᠨᡳ ᠮᠠᠶᠠᠨ᠈ |
| `structured_prompt.text_render` |  | array of any \| null | no | `[]` |  | ᡤᠠᠳᠠᠨᡩᡝ ᡝᠮᡤᡝᠯᡝᡵᡝ ᡥᡡᠯᠠᠨᡳ ᡩᠠᠰᠠᠨ᠈ |
| `structured_prompt.context` |  | string \| null | no |  |  | ᠪᡠᠶᡝᠮᡝᠨᡳ ᡤᠠᠳᠠᠨᡳ ᠵᡠᠯᡝ᠈ |
| `structured_prompt.artistic_style` |  | string \| null | no |  |  | ᠪᡠᠶᡝᠮᡝᠨᡳ ᠰᠠᠶᠠᠨᡳ ᠮᠠᠶᠠᠨ᠈ |
| `seed` |  | integer | no | `5555` |  | ᠨᠠᠮᡠ ᡨᡠᡶᡳ ᠵᠠᠯᡤᠠᠶᡳ ᡝᠮᡤᡝᠯᡝᠮᡝ ᠵᡠᠯᡝ᠈ |
| `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` | ᠤᠯᡥᡳᠶᡝᠮᡝᠨᡳ ᠯᠠᠯᡳᠶᠠᠨ; ᠣᠮᠪᡳ ᠵᡳᠯᡤᠠᠨ ᠪᡳ 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` | ᠪᡠᠶᡝᠮᡝᡵᡝ ᡤᠠᠳᠠᠨ ᡳ ᠵᠠᠯᠠᠨ. |

## 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} | ᠮᠣᠳᡝᠯ ᠪᡝ ᠪᡠᠶᡝᠮᡝᡥᡝ ᡤᠠᠳᠠᠨ. |
| `images` | array of object | ᠪᡠᠶᡝᠮᡝ ᠵᡠᠴᡝᠨ ᡳ ᠤᠯᡥᠠᠨ ᠤᠯᡥᠠᠨ᠉ |
| `structured_prompt` | object | ᡳᠨᡠ ᠠᠰᡥᠠᠨ ᡥᡡᠯᠠᠨ. |

## 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
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- [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
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## 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