# AI Avatar Multi Text API

> ينشئ فيديو يتحدث فيه شخصان انطلاقًا من صورة واحدة، مع نص وصوت محدد لكل متحدث

يحوّل صورة واحدة إلى محادثة بين شخصين. قدم `first_text_input` و`second_text_input` كسطرين للحوار، إلى جانب `prompt`، واختر `voice1` و`voice2` من الأصوات الجاهزة. يكون الإخراج بدقة 480p أو 720p، مع `num_frames` من 41 إلى 241. يتوفر إعداد `acceleration` بالقيم none أو regular أو high.

- Model id: `ai-avatar/multi-text`
- Made by: Open model
- Category: Lipsync & Avatars
- Output: video
- Estimated price per run: from $0.648 / run (cheapest run $0.648 (648 API credits))
- Run: `POST https://api.doitong.ru/v1/run/ai-avatar/multi-text`
- Quote: `POST https://api.doitong.ru/v1/quote/ai-avatar/multi-text`
- Docs page: https://doitong.com/ar/developers/models/ai-avatar/multi-text

## Pricing

Price: **from $0.648 / run** (the lowest tier; the quote prices your exact input). Estimated from the typical cost of one run. The quote is exactly what the run charges.

Price rules (the first rule that matches the input wins; a parameter you leave out counts as its default):

- When `num_frames` > 191 and `resolution` = 720p: base price × 4.5
- When `num_frames` ≤ 191 and `resolution` = 720p: base price × 2.25
- When `num_frames` > 191 and `resolution` = 480p: base price × 2

The full example input below costs $0.648 = 648 API credits (1 request × 648 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/ai-avatar/multi-text` 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 |
|---|---|---|---|---|---|---|
| `image_url` | `image` | string (image URL) | yes |  |  | عنوان URL للصورة المصدر، مع تحديد نسبة العرض إلى الارتفاع المختارة لما إذا كانت المعالجة المسبقة مطلوبة: يؤدي عدم التطابق إلى تغيير الحجم ثم الاقتصاص من المنتصف. |
| `first_text_input` |  | string | yes |  |  | نص يوجّه عملية توليد الفيديو. |
| `second_text_input` |  | string | yes |  |  | نص يوجّه عملية توليد الفيديو. |
| `voice1` |  | enum (string) | no | `Sarah` | `Aria`, `Roger`, `Sarah`, `Laura`, `Charlie`, `George`, `Callum`, `River`, `Liam`, `Charlotte`, `Alice`, `Matilda`, `Will`, `Jessica`, `Eric`, `Chris`, `Brian`, `Daniel`, `Lily`, `Bill` | الصوت المعيّن للشخص الأول عند توليد الكلام. |
| `voice2` |  | enum (string) | no | `Roger` | `Aria`, `Roger`, `Sarah`, `Laura`, `Charlie`, `George`, `Callum`, `River`, `Liam`, `Charlotte`, `Alice`, `Matilda`, `Will`, `Jessica`, `Eric`, `Chris`, `Brian`, `Daniel`, `Lily`, `Bill` | الصوت المعيّن للشخص الثاني عند توليد الكلام. |
| `prompt` |  | string | yes |  |  | تعليمات نصية لتوجيه توليد الفيديو. |
| `num_frames` |  | integer | no | `191` | 41 – 241 | عدد الإطارات للتوليد، من 81 إلى 129، شاملًا. |
| `resolution` |  | enum (string) | no | `480p` | `480p`, `720p` | دقة الفيديو الناتج؛ لا يُدعم سوى 480p و720p. |
| `seed` |  | integer | no | `81` | 0 – 4,294,967,295 | بذرة تجعل التوليد قابلًا لإعادة الإنتاج. يؤدي ضبطها على None إلى اختيار بذرة عشوائيًا. |
| `acceleration` |  | enum (string) | no | `regular` | `none`, `regular`, `high` | مستوى التسريع المطبّق أثناء التوليد. |
| `enable_safety_checker` |  | boolean | no | `true` |  | يمكن تخفيف الفحص بضبط القيمة على false، شريطة أن يكون المستدعي مخولًا بذلك. |

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

A fuller example:

```json
{
  "image_url": "https://content.doitong.com/images/showcase/v3/avatar/talking_avatar.jpg",
  "first_text_input": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
  "second_text_input": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
  "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/ai-avatar/multi-text?wait=20" \
  -H "Authorization: Bearer $DOITONG_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "image_url": "https://content.doitong.com/images/showcase/v3/avatar/talking_avatar.jpg",
    "first_text_input": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
    "second_text_input": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
    "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/ai-avatar/multi-text?wait=20", {
  method: "POST",
  headers,
  body: JSON.stringify({
    "image_url": "https://content.doitong.com/images/showcase/v3/avatar/talking_avatar.jpg",
    "first_text_input": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
    "second_text_input": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
    "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 = {
    "image_url": "https://content.doitong.com/images/showcase/v3/avatar/talking_avatar.jpg",
    "first_text_input": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
    "second_text_input": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
    "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/ai-avatar/multi-text", 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": "ai-avatar/multi-text",
      "input": {
        "image_url": "https://content.doitong.com/images/showcase/v3/avatar/talking_avatar.jpg",
        "first_text_input": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
        "second_text_input": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
        "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": "ai-avatar/multi-text",
  "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": 648,
    "usd": "0.648",
    "charged": 648,
    "refunded": 0
  },
  "input": {
    "image_url": "https://content.doitong.com/images/showcase/v3/avatar/talking_avatar.jpg",
    "first_text_input": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
    "second_text_input": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
    "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
  },
  "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} | ملف الفيديو الناتج عن التوليد. |
| `seed` | integer | قيمة البذرة المطبّقة أثناء التوليد. |

## Related models

- [AI Avatar Multi](https://doitong.com/developers/models/ai-avatar/multi.md) (`ai-avatar/multi`): from $0.20 / second of output video
- [AI Avatar Single Text](https://doitong.com/developers/models/ai-avatar/single-text.md) (`ai-avatar/single-text`): from $4.688 / run
- [Kling AI Avatar 2.0 Pro](https://doitong.com/developers/models/kling-video/ai-avatar/v2/pro.md) (`kling-video/ai-avatar/v2/pro`): $0.115 / second of input audio
- [Sync Lipsync 3](https://doitong.com/developers/models/sync-lipsync/v3.md) (`sync-lipsync/v3`): $8.00 / minute of output video
- [VEED Fabric 1.0](https://doitong.com/developers/models/veed/fabric-1.0.md) (`veed/fabric-1.0`): from $0.08 / second of input audio
- [Flashhead](https://doitong.com/developers/models/flashhead.md) (`flashhead`): $0.068 / run
- [Flashtalk](https://doitong.com/developers/models/flashtalk.md) (`flashtalk`): $0.02 / second of input audio
- [Sad Talker](https://doitong.com/developers/models/sadtalker.md) (`sadtalker`): $0.00125 / second of processing time

## Links

- HTML page: https://doitong.com/developers/models/ai-avatar/multi-text
- 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=ai-avatar/multi-text
- Errors: https://doitong.com/developers/docs/errors
- Model details as JSON: https://api.doitong.ru/v1/models/ai-avatar/multi-text