# AnimateDiff · Video to Video API

> একটি প্রম্পট থেকে ইনপুট ভিডিওর প্রথম 2 থেকে 4 সেকেন্ড AnimateDiff দিয়ে নতুন স্টাইলে রূপান্তর করে

`prompt` অনুযায়ী `video_url` পুনরায় অ্যানিমেট করে, শুধু প্রথম `first_n_seconds` ব্যবহার করে (2 থেকে 4, ডিফল্ট 3)। 0 থেকে 1-এর `strength` সোর্স ভিডিও কতটা দৃশ্যমান থাকবে তা নির্ধারণ করে। এটি `motions`, `negative_prompt`, `guidance_scale`, সর্বোচ্চ 16 `fps` এবং সর্বোচ্চ 50টি ইনফারেন্স ধাপও গ্রহণ করে।

- Model id: `fast-animatediff/video-to-video`
- Made by: Open model
- Category: Video to Video
- Output: video
- Charged by usage (up to $4.50 per run, typical $0.001; the rest of the hold is refunded): $0.00125 / second of processing time (cheapest run $0.001 (1 API credit))
- Run: `POST https://api.doitong.ru/v1/run/fast-animatediff/video-to-video`
- Quote: `POST https://api.doitong.ru/v1/quote/fast-animatediff/video-to-video`
- Docs page: https://doitong.com/bn/developers/models/fast-animatediff/video-to-video

## Pricing

Price: **$0.00125 / second of processing time**. Charged by actual usage at $0.00125 / second of processing time: up to $4.50 per run (the quote gives the maximum for your input), the rest is refunded automatically after the run. A typical run costs $0.001.

The full example input below holds up to $4.50 = 4500 API credits (up to 3600 s of processing time × $0.00125) when it starts; a typical run costs $0.001 (1 API credit).

Prices are the upstream price in USD, paid from the API balance in API credits (1000 API credits = 1 USD). This model is charged by usage: `POST https://api.doitong.ru/v1/quote/fast-animatediff/video-to-video` with the same JSON body returns the most the run can cost for that input (`credits`, debited when the run starts); after the run you pay the usage the model reports and the rest is refunded automatically. An input whose maximum would exceed the per-run limit is refused with 422. 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 |
|---|---|---|---|---|---|---|
| `video_url` | `video` | string (video URL) | yes |  |  | ভিডিওর URL। |
| `first_n_seconds` |  | integer | no | `3` | 2 – 4 | অ্যানিমেট করার সময়কাল সেকেন্ডে, ভিডিওর শুরু থেকে গণনা করা। |
| `prompt` |  | string | yes |  |  | আপনি যে ছবি জেনারেট করতে চান তা যতটা সম্ভব বিস্তারিতভাবে বর্ণনা করুন, যাতে সেরা ফলাফল পাওয়া যায়। |
| `negative_prompt` |  | string | no | `(bad quality, worst quality:1.2), ugly faces, bad anime` |  | বাদ দিতে হবে এমন ছবির বিবরণ নির্দিষ্ট করা নেগেটিভ প্রম্পট, যার মধ্যে রং, বস্তু, দৃশ্য বা সূক্ষ্ম বৈশিষ্ট্য অন্তর্ভুক্ত থাকতে পারে। উদাহরণ হিসেবে গোঁফ, ব্লার বা কম রেজোলিউশন উল্লেখ করা যায়। |
| `num_inference_steps` |  | integer | no | `25` | 1 – 50 | চালানোর জন্য inference ধাপের সংখ্যা। |
| `strength` |  | number | no | `0.7` | 0 – 1 | চূড়ান্ত ফলাফলের ওপর ইনপুট ভিডিওর প্রভাবের মাত্রা। |
| `guidance_scale` |  | number | no | `7.5` | 0 – 20 | ছবি নির্বাচনের জন্য প্রম্পট-অনুসরণের শক্তি, CFG (Classifier Free Guidance) হিসেবে প্রকাশ করা। |
| `seed` |  | integer \| null | no |  |  | Stable Diffusion-এ ছবি পুনরুৎপাদনের seed। মডেলের সংস্করণ, প্রম্পট এবং seed অপরিবর্তিত রাখলে প্রতিবার ছবি হুবহু পুনরুৎপাদন করা যায়। |
| `fps` |  | integer | no | `8` | 1 – 16 | ভিডিও থেকে ফ্রেম এক্সট্র্যাকশনের হার, প্রতি সেকেন্ডে ফ্রেমে। |
| `motions` |  | array of enum (string) | no |  |  | ভিডিওতে প্রয়োগ করা মোশন। |
| `enable_safety_checker` |  | boolean | no | `true` |  | কলকারী অনুমোদিত হলে false সেট করে স্ক্রিনিং শিথিল করা যায়। |

File parameters (`video`) 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",
  "video": "https://content.doitong.com/video/showcase/v3/gen_fox_cartoon.mp4"
}
```

A fuller example:

```json
{
  "prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
  "video_url": "https://content.doitong.com/video/showcase/v3/gen_fox_cartoon.mp4"
}
```

## 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/fast-animatediff/video-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",
    "video_url": "https://content.doitong.com/video/showcase/v3/gen_fox_cartoon.mp4"
  }'

# 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/fast-animatediff/video-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",
    "video_url": "https://content.doitong.com/video/showcase/v3/gen_fox_cartoon.mp4"
  }),
});
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",
    "video_url": "https://content.doitong.com/video/showcase/v3/gen_fox_cartoon.mp4",
}

# Run the model; wait up to 20 s for the finished result in the same call
r = requests.post(API + "/run/fast-animatediff/video-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.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": "fast-animatediff/video-to-video",
      "input": {
        "prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
        "video_url": "https://content.doitong.com/video/showcase/v3/gen_fox_cartoon.mp4"
      },
      "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": "fast-animatediff/video-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": 4500,
    "usd": "4.50",
    "charged": 4500,
    "refunded": 0
  },
  "input": {
    "prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
    "video_url": "https://content.doitong.com/video/showcase/v3/gen_fox_cartoon.mp4"
  },
  "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
  },
  "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.ru/v1/requests/req_8k2m4q7x1z9c3v5b6n0p2r4t",
    "cancel": "https://api.doitong.ru/v1/requests/req_8k2m4q7x1z9c3v5b6n0p2r4t/cancel"
  }
}
```

### Output fields (`output`)

| Field | Type | Description |
|---|---|---|
| `video` | object {url, content_type, file_name, file_size} | ফলাফল হিসেবে পাওয়া ভিডিও ফাইল। |
| `seed` | integer | ভিডিও জেনারেশনের সময় ব্যবহৃত seed। |

## Related models

- [AnimateDiff · Text to Video](https://doitong.com/developers/models/fast-animatediff/text-to-video.md) (`fast-animatediff/text-to-video`): from $0.023 / run
- [AMT Interpolation](https://doitong.com/developers/models/amt-interpolation.md) (`amt-interpolation`): $0.000575 / second of processing time
- [AnimateDiff Turbo · Video to Video](https://doitong.com/developers/models/fast-animatediff/turbo/video-to-video.md) (`fast-animatediff/turbo/video-to-video`): $0.00125 / second of processing time
- [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
- [DWPose Pose Prediction · Video](https://doitong.com/developers/models/dwpose/video.md) (`dwpose/video`): $0.0006 / second of processing time
- [Editto](https://doitong.com/developers/models/editto.md) (`editto`): from $0.04 / second of output video
- [ID-V2V](https://doitong.com/developers/models/id-v2v.md) (`id-v2v`): $0.20 / second of output video

## Links

- HTML page: https://doitong.com/developers/models/fast-animatediff/video-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=fast-animatediff/video-to-video
- Errors: https://doitong.com/developers/docs/errors
- Model details as JSON: https://api.doitong.ru/v1/models/fast-animatediff/video-to-video