# Bernini-R Reference to Video API

> Generuje jedno souvislé video z jednoho až pěti referenčních obrázků subjektů a promptu

Zadejte `prompt` a jeden až pět `reference_image_urls`; model vytvoří jedno video s těmito subjekty. `aspect_ratio` může být 16:9, 9:16 nebo 1:1. Nastavit lze `num_frames` (5 až 121), `frames_per_second` (4 až 30) a `num_inference_steps` (1 až 50). `negative_prompt` a rozšíření promptu jsou volitelné.

- Model id: `bernini-r/reference-to-video`
- Made by: Open model
- Category: Reference 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/reference-to-video`
- Quote: `POST https://api.doitong.com/v1/quote/bernini-r/reference-to-video`
- Docs page: https://doitong.com/cs/developers/models/bernini-r/reference-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/reference-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

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 |  |  | Text popisující prompt nebo požadovanou úpravu. |
| `negative_prompt` |  | string \| null | no |  |  | Negativní prompt; pokud není zadán, použije se standardní negativní prompt modelu Wan2.2. |
| `num_inference_steps` |  | integer | no | `30` | 1 – 50 | Počet provedených kroků odšumování. |
| `max_image_size` |  | integer | no | `848` | 256 – 1,280 | Nastavení pixelů delší hrany: při úpravách slouží jako limit velikosti zdrojových/referenčních médií, při generování určuje velikost výstupu. |
| `seed` |  | integer \| null | no |  |  | Seed umožňující opakovatelné výsledky; pokud není zadán, zvolí se náhodně. |
| `enable_prompt_expansion` |  | boolean | no | `false` |  | Volitelné přepsání promptu pomocí LLM před generováním; ve výchozím nastavení je vypnuté, přestože model byl trénován na rozšířených promptech. |
| `num_frames` |  | integer | no | `81` | 5 – 121 | Počet snímků interně upravený na tvar 4k+1. |
| `frames_per_second` |  | integer | no | `16` | 4 – 30 | Snímková frekvence výstupu ve snímcích za sekundu. |
| `acceleration` |  | enum (string) | no | `none` | `none`, `regular` | Míra použitého zrychlení. |
| `reference_image_urls` | `images` | array of image URL | yes |  | 1 – 5 items | Obrázky poskytující reference objektu, maximálně 5. |
| `aspect_ratio` |  | enum (string) | no | `16:9` | `16:9`, `9:16`, `1:1` | Poměr stran výstupu. |
| `enable_safety_checker` |  | boolean | no | `true` |  | Kontrolu lze uvolnit nastavením na false, pokud je volající autorizován. |

File parameters (`images`) 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
{
  "prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
  "images": [
    "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
  ]
}
```

A fuller example:

```json
{
  "prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
  "reference_image_urls": [
    "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
  ]
}
```

## 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/reference-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",
    "reference_image_urls": [
      "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
    ]
  }'

# 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/reference-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",
    "reference_image_urls": [
      "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
    ]
  }),
});
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",
    "reference_image_urls": [
        "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg",
    ],
}

# Run the model; wait up to 20 s for the finished result in the same call
r = requests.post(API + "/run/bernini-r/reference-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/reference-to-video",
      "input": {
        "prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
        "reference_image_urls": [
          "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
        ]
      },
      "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/reference-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",
    "reference_image_urls": [
      "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
    ]
  },
  "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} | Video vzniklé generováním nebo úpravou. |
| `seed` | integer | Seed použitý během generování. |
| `actual_prompt` | string \| null | Konečný rozšířený prompt, vyplněný pouze po provedení rozšíření promptu. |

## 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 Text to Video](https://doitong.com/developers/models/bernini-r/text-to-video.md) (`bernini-r/text-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
- [Seedance 2.0 Fast Reference to Video](https://doitong.com/developers/models/bytedance/seedance-2.0/fast/reference-to-video.md) (`bytedance/seedance-2.0/fast/reference-to-video`): from $0.113 / second
- [Seedance 2.0 Reference to Video](https://doitong.com/developers/models/bytedance/seedance-2.0/reference-to-video.md) (`bytedance/seedance-2.0/reference-to-video`): from $0.141 / second
- [Wan 3.0 Reference to Video](https://doitong.com/developers/models/alibaba/wan-3.0/reference-to-video.md) (`alibaba/wan-3.0/reference-to-video`): from $0.05 / second
- [Alibaba V2.6 · Reference to Video · Flash](https://doitong.com/developers/models/wan/v2.6/reference-to-video/flash.md) (`wan/v2.6/reference-to-video/flash`): from $0.05 / second of output video

## Links

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