# AI Avatar Multi Text API

> Joħloq vidjo ta’ żewġ persuni jitkellmu minn immaġni waħda, bi skript u vuċi magħżula għal kull kelliem

Janima immaġni waħda f’konversazzjoni bejn żewġ persuni. Ipprovdi `first_text_input` u `second_text_input` bħala l-linji, flimkien ma’ `prompt`, u agħżel `voice1` u `voice2` mill-vuċijiet issettjati minn qabel. L-output huwa 480p jew 720p, b’`num_frames` minn 41 sa 241. Is-setting `acceleration` jista’ jkun none, regular jew 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.com/v1/run/ai-avatar/multi-text`
- Quote: `POST https://api.doitong.com/v1/quote/ai-avatar/multi-text`
- Docs page: https://doitong.com/mt/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.com/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 |  |  | URL tal-immaġni tas-sors, bir-ratio tal-aspett magħżul jiddetermina jekk hemmx bżonn ta’ preprocessing: nuqqas ta’ qbil iqanqal ridimensjonar segwit minn crop ċentrali. |
| `first_text_input` |  | string | yes |  |  | Test li jidderieġi l-proċess tal-ġenerazzjoni tal-vidjo. |
| `second_text_input` |  | string | yes |  |  | Test li jidderieġi l-proċess tal-ġenerazzjoni tal-vidjo. |
| `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` | Vuċi assenjata lill-ewwel persuna meta jiġi ġġenerat id-diskors. |
| `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` | Vuċi assenjata lit-tieni persuna meta jiġi ġġenerat id-diskors. |
| `prompt` |  | string | yes |  |  | Istruzzjonijiet testwali li jiggwidaw il-ġenerazzjoni tal-vidjo. |
| `num_frames` |  | integer | no | `191` | 41 – 241 | Għadd ta’ frejms għall-ġenerazzjoni, minn 81 sa 129, inklużi. |
| `resolution` |  | enum (string) | no | `480p` | `480p`, `720p` | Riżoluzzjoni tal-vidjo output; huma appoġġjati biss 480p u 720p. |
| `seed` |  | integer | no | `81` | 0 – 4,294,967,295 | Seed li jagħmel il-ġenerazzjoni riproduċibbli. L-issettjar tiegħu għal None jagħżel seed b’mod każwali. |
| `acceleration` |  | enum (string) | no | `regular` | `none`, `regular`, `high` | Livell ta’ aċċelerazzjoni applikat waqt il-ġenerazzjoni. |
| `enable_safety_checker` |  | boolean | no | `true` |  | L-iskrinjar jista’ jiġi rilassat billi jiġi ssettjat għal false, sakemm min jagħmel it-talba jkun awtorizzat. |

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.com/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.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/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.com/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.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": "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.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} | Fajl vidjo prodott mill-ġenerazzjoni. |
| `seed` | integer | Valur ta’ seed applikat waqt il-ġenerazzjoni. |

## 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.com/v1/models/ai-avatar/multi-text