# Bernini-R Text to Video API

> صرف متنی پرامپٹ سے ویڈیو تخلیق، 16:9، 9:16 یا 1:1 آؤٹ پٹ کے ساتھ

Bernini-R فیملی کا صرف متنی رکن: `prompt` لکھیں اور 16:9، 9:16 یا 1:1 کا `aspect_ratio` منتخب کریں۔ `num_frames` 5 سے 121، `frames_per_second` 4 سے 30 اور `num_inference_steps` 1 سے 50 تک ہے۔ `max_image_size` لمبی سمت 256 سے 1280 تک مقرر کرتا ہے۔ اختیاری `negative_prompt` اور پرامپٹ توسیع۔

- Model id: `bernini-r/text-to-video`
- Made by: Open model
- Category: Text to Video
- Output: video
- Price per second of your output video: from $0.04 / second of output video (cheapest run $0.04 (40 API credits))
- Run: `POST https://api.doitong.com/v1/run/bernini-r/text-to-video`
- Quote: `POST https://api.doitong.com/v1/quote/bernini-r/text-to-video`
- Docs page: https://doitong.com/ur/developers/models/bernini-r/text-to-video

## Pricing

Price: **from $0.04 / second of output video** (the lowest tier; the quote prices your exact input). Price per second of your output video: the input files are measured before the run (length, resolution, frame rate). The quote measures the same files and is exactly what the run charges.

The full example input below costs $0.405 = 405 API credits (5.0625 s output video × $0.08).

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/bernini-r/text-to-video` 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 | yes |  |  | پرامپٹ یا مطلوبہ ترمیم کی وضاحت کرنے والا متن۔ |
| `negative_prompt` |  | string \| null | no |  |  | منفی پرامپٹ؛ متعین نہ ہونے پر Wan2.2 کا معیاری منفی پرامپٹ استعمال ہوتا ہے۔ |
| `num_inference_steps` |  | integer | no | `30` | 1 – 50 | کرنے والے ڈینوائزنگ مراحل کی تعداد۔ |
| `max_image_size` |  | integer | no | `848` | 256 – 1,280 | طویل کنارے کی پکسل سیٹنگ: ایڈیٹنگ میں اسے ماخذ/حوالہ میڈیا کے سائز کی بالائی حد کے طور پر، جبکہ تخلیق میں آؤٹ پٹ سائز مقرر کرنے کے لیے استعمال کیا جاتا ہے۔ |
| `seed` |  | integer \| null | no |  |  | قابلِ تکرار نتائج کے لیے سیڈ؛ نہ دی جائے تو بے ترتیب طور پر منتخب ہوتی ہے۔ |
| `enable_prompt_expansion` |  | boolean | no | `false` |  | تخلیق سے پہلے LLM کے ذریعے اختیاری پرامپٹ کی ازسرِنو تحریر؛ ڈیفالٹ طور پر غیر فعال ہے، اگرچہ ماڈل کو بہتر پرامپٹس پر ٹیون کیا گیا ہے۔ |
| `num_frames` |  | integer | no | `81` | 5 – 121 | فریموں کی تعداد، اندرونی طور پر 4k+1 کی شکل میں ایڈجسٹ کی جاتی ہے۔ |
| `frames_per_second` |  | integer | no | `16` | 4 – 30 | آؤٹ پٹ کی فریم ریٹ، فریم فی سیکنڈ میں۔ |
| `acceleration` |  | enum (string) | no | `none` | `none`, `regular` | لاگو کی جانے والی ایکسیلیریشن کی مقدار۔ |
| `aspect_ratio` |  | enum (string) | no | `16:9` | `16:9`, `9:16`, `1:1` | آؤٹ پٹ کا پہلو تناسب۔ |
| `enable_safety_checker` |  | boolean | no | `true` |  | false سیٹ کر کے اسکریننگ نرم کی جا سکتی ہے، بشرطیکہ کال کرنے والا مجاز ہو۔ |

## 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/bernini-r/text-to-video?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/bernini-r/text-to-video?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/bernini-r/text-to-video", 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": "bernini-r/text-to-video",
      "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": "bernini-r/text-to-video",
  "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": 405,
    "usd": "0.405",
    "charged": 405,
    "refunded": 0
  },
  "input": {
    "prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
  },
  "output": {
    "video": {
      "url": "https://content.doitong.com/dev-api/2026/10/20/req_8k2m4q7x1z9c3v5b6n0p2r4t/0-output.mp4",
      "content_type": "video/mp4",
      "file_name": "0-output.mp4",
      "file_size": 1843200
    },
    "seed": 42,
    "actual_prompt": "string"
  },
  "outputs": [
    {
      "type": "video",
      "url": "https://content.doitong.com/dev-api/2026/10/20/req_8k2m4q7x1z9c3v5b6n0p2r4t/0-output.mp4",
      "content_type": "video/mp4",
      "file_size": 1843200,
      "width": 1280,
      "height": 720,
      "duration": 5,
      "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 |
|---|---|---|
| `video` | object {url, content_type, file_name, file_size} | تخلیق یا ایڈیٹنگ سے حاصل ہونے والی ویڈیو۔ |
| `seed` | integer | تخلیق کے دوران لاگو ہونے والی سیڈ۔ |
| `actual_prompt` | string \| null | آخری توسیع شدہ پرامپٹ، صرف اسی وقت بھرا جاتا ہے جب پرامپٹ کی توسیع کی گئی ہو۔ |

## Related models

- [Bernini-R Edit Image](https://doitong.com/developers/models/bernini-r/edit-image.md) (`bernini-r/edit-image`): $0.03 / megapixel of output image
- [Bernini-R Reference to Video](https://doitong.com/developers/models/bernini-r/reference-to-video.md) (`bernini-r/reference-to-video`): from $0.04 / second of output video
- [Bernini-R Edit Video](https://doitong.com/developers/models/bernini-r/edit-video.md) (`bernini-r/edit-video`): from $0.04 / second of output video
- [Bernini-R Reference Edit Video](https://doitong.com/developers/models/bernini-r/reference-edit-video.md) (`bernini-r/reference-edit-video`): from $0.04 / second of output video
- [FLUX 3 Max Text to Video](https://doitong.com/developers/models/blackforestlabs/flux-3-max/text-to-video.md) (`blackforestlabs/flux-3-max/text-to-video`): from $0.0425 / second of output video
- [Grok Imagine Video 1.5 Text to Video](https://doitong.com/developers/models/xai/grok-imagine-video/v1.5/text-to-video.md) (`xai/grok-imagine-video/v1.5/text-to-video`): from $0.08 / second
- [Kling 3.0 Pro Text to Video](https://doitong.com/developers/models/kling-video/v3/pro/text-to-video.md) (`kling-video/v3/pro/text-to-video`): from $0.112 / second
- [LTX 2.5 Pro Text to Video](https://doitong.com/developers/models/lightricks/ltx-2.5/text-to-video/pro.md) (`lightricks/ltx-2.5/text-to-video/pro`): from $0.12 / second

## Links

- HTML page: https://doitong.com/developers/models/bernini-r/text-to-video
- 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=bernini-r/text-to-video
- Errors: https://doitong.com/developers/docs/errors
- Model details as JSON: https://api.doitong.com/v1/models/bernini-r/text-to-video