# LTX 2.3 Trainer (V2) - Video-to-Audio API

> Melatih LoRA yang menjana audio sepadan atau foley untuk video senyap

Melatih LoRA yang menghasilkan runut bunyi sepadan dengan aksi pada skrin dalam video. Setiap klip latihan mesti mengekalkan runut audio, jadi pemisahan adegan dilumpuhkan secara lalai bagi mengelakkan segmen hujung yang senyap. Sampel pengesahan (sehingga 2) masing-masing memadankan prompt dengan video senyap. Data ialah zip melalui `training_data_url`.

- Model id: `ltx23-trainer-v2/v2a`
- Made by: Lightricks
- Category: Training
- Output: file
- Price: $0.0049 / step (cheapest run $9.80 (9800 API credits))
- Run: `POST https://api.doitong.com/v1/run/ltx23-trainer-v2/v2a`
- Quote: `POST https://api.doitong.com/v1/quote/ltx23-trainer-v2/v2a`
- Docs page: https://doitong.com/ms/developers/models/ltx23-trainer-v2/v2a

## Pricing

Price: **$0.0049 / step**. Billed per training step (`number_of_steps`).

The full example input below costs $9.80 = 9800 API credits (2000 steps × 4.9 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/ltx23-trainer-v2/v2a` 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 |
|---|---|---|---|---|---|---|
| `training_data_url` |  | string | yes |  |  | URL untuk `.zip` yang mengandungi data latihan, disusun mengikut mod latihan yang dipilih. Setiap fail media boleh disertai kapsyen `.txt` dengan nama asas yang sepadan. |
| `rank` |  | enum (integer) | no | `32` | `8`, `16`, `32`, `64`, `128` | Rank penyesuaian LoRA, menukar penggunaan memori yang meningkat dengan kapasiti yang lebih besar apabila tetapan dinaikkan. |
| `number_of_steps` |  | integer | no | `2000` | 100 – 10,000 | Jumlah langkah latihan. |
| `learning_rate` |  | number | no | `0.0002` | 0.000001 – 1 | Kadar pembelajaran pengoptimuman. |
| `number_of_frames` |  | integer | no | `89` | 9 – 121 | Kiraan bingkai bagi setiap sampel latihan. Membahagikan kiraan dengan 8 mesti meninggalkan baki 1; contohnya 1, 9, 17, 25, 33, 41, 49, 57, 65, 73, 81, 89, 97. |
| `frame_rate` |  | integer | no | `24` | 8 – 60 | Kadar bingkai sasaran video latihan dalam bingkai sesaat. Kadar asli untuk LTX-2.3 ialah 24. |
| `resolution` |  | enum (string) | no | `medium` | `low`, `medium`, `high` | Resolusi latihan. Meningkatkan resolusi meningkatkan keperluan memori. |
| `aspect_ratio` |  | enum (string) | no | `1:1` | `16:9`, `1:1`, `9:16` | Nisbah aspek latihan. |
| `trigger_phrase` |  | string | no | `` |  | Frasa pengaktifan gaya LoRA, disisipkan pada permulaan kapsyen semasa latihan. |
| `auto_scale_input` |  | boolean | no | `false` |  | Pelarasan video automatik agar sepadan dengan FPS dan kiraan bingkai yang diminta apabila didayakan; set data imej kekal tidak berubah. |
| `split_input_into_scenes` |  | boolean | no | `false` |  | Mengawal pemisahan berasaskan adegan bagi video panjang apabila true. Untuk v2a, ia lalai kepada mati, selaras dengan a2v: setiap klip memerlukan trek audio kerana model menjana audio. Pemisahan mungkin meninggalkan segmen senyap pada penghujung yang mencetuskan ralat mengelirukan semasa pengesahan audio setiap klip. |
| `split_input_duration_threshold` |  | number | no | `30` | 1 – 60 | Pencetus pemisahan adegan yang dinyatakan sebagai tempoh dalam saat: hanya video yang lebih panjang daripada ambang akan dipisahkan. |
| `debug_dataset` |  | boolean | no | `false` |  | Mod pemeriksaan prapemprosesan untuk menyemak video, imej dan kapsyen sebelum larian latihan penuh. Mendayakannya menyebabkan pelatih mengembalikan set data latihan yang diproses dalam arkib boleh dimuat turun untuk semakan manual. |
| `validation` |  | array of object {prompt, video_url} | no | `[]` | ≤ 2 items | Data pengesahan untuk menjana audio, dibekalkan sebagai senarai entri yang mengandungi prompt dan video senyap. |
| `validation[].prompt` |  | string | yes |  |  | Prompt yang digunakan semasa pengesahan. |
| `validation[].video_url` |  | string (video URL) | yes |  | ≥ 1 characters | URL video senyap yang audionya akan dicipta oleh model. |
| `validation_negative_prompt` |  | string | no | `blurry, out of focus, overexposed, underexposed, low contrast, washed out colors, excessive noise, grainy texture, poor lighting, flickering, motion blur, distorted proportions, unnatural skin tones, deformed facial features, asymmetrical face, missing facial features, extra limbs, disfigured hands, wrong hand count, artifacts around text, inconsistent perspective, camera shake, incorrect depth of field, background too sharp, background clutter, distracting reflections, harsh shadows, inconsistent lighting direction, color banding, cartoonish rendering, 3D CGI look, unrealistic materials, uncanny valley effect, incorrect ethnicity, wrong gender, exaggerated expressions, wrong gaze direction, mismatched lip sync, silent or muted audio, distorted voice, robotic voice, echo, background noise, off-sync audio, incorrect dialogue, added dialogue, repetitive speech, jittery movement, awkward pauses, incorrect timing, unnatural transitions, inconsistent framing, tilted camera, flat lighting, inconsistent tone, cinematic oversaturation, stylized filters, or AI artifacts.` |  | Prompt negatif yang digunakan semasa pengesahan, yang menggunakan proses pratonton satu peringkat. Oleh sebab proses itu menghampiri inferens pengeluaran terdistil dengan dua peringkat, panduan dan kualiti pratontonnya berbeza daripada hasil akhir. |
| `validation_number_of_frames` |  | integer | no | `89` | 9 – 121 | Kiraan bingkai bagi setiap video pengesahan. |
| `validation_frame_rate` |  | integer | no | `24` | 8 – 60 | Kadar bingkai sasaran untuk video pengesahan, dalam bingkai sesaat; LTX-2.3 berjalan secara asli pada 24. |
| `validation_resolution` |  | enum (string) | no | `high` | `low`, `medium`, `high` | Resolusi yang digunakan semasa pengesahan. |
| `validation_aspect_ratio` |  | enum (string) | no | `1:1` | `16:9`, `1:1`, `9:16` | Nisbah aspek yang digunakan semasa pengesahan. |
| `stg_scale` |  | number | no | `1` | 0 – 3 | Skala Panduan Ruang-Masa (STG), dengan 1.0 disyorkan dan 0.0 mematikan STG. |

## Example input

Required parameters only:

```json
{
  "training_data_url": "https://example.com/your-file.zip"
}
```

A fuller example:

```json
{
  "training_data_url": "https://example.com/your-file.zip"
}
```

## 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/ltx23-trainer-v2/v2a?wait=20" \
  -H "Authorization: Bearer $DOITONG_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "training_data_url": "https://example.com/your-file.zip"
  }'

# 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/ltx23-trainer-v2/v2a?wait=20", {
  method: "POST",
  headers,
  body: JSON.stringify({
    "training_data_url": "https://example.com/your-file.zip"
  }),
});
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 = {
    "training_data_url": "https://example.com/your-file.zip",
}

# Run the model; wait up to 20 s for the finished result in the same call
r = requests.post(API + "/run/ltx23-trainer-v2/v2a", 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": "ltx23-trainer-v2/v2a",
      "input": {
        "training_data_url": "https://example.com/your-file.zip"
      },
      "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": "ltx23-trainer-v2/v2a",
  "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": 9800,
    "usd": "9.80",
    "charged": 9800,
    "refunded": 0
  },
  "input": {
    "training_data_url": "https://example.com/your-file.zip"
  },
  "output": {
    "video": {
      "url": "https://content.doitong.com/dev-api/2026/10/20/req_8k2m4q7x1z9c3v5b6n0p2r4t/0-output.jpeg",
      "content_type": "image/jpeg",
      "file_name": "0-output.jpeg",
      "file_size": 1843200
    },
    "audio": {
      "url": "https://content.doitong.com/dev-api/2026/10/20/req_8k2m4q7x1z9c3v5b6n0p2r4t/0-output.jpeg",
      "content_type": "image/jpeg",
      "file_name": "0-output.jpeg",
      "file_size": 1843200
    },
    "lora_file": {
      "url": "https://content.doitong.com/dev-api/2026/10/20/req_8k2m4q7x1z9c3v5b6n0p2r4t/0-output.jpeg",
      "content_type": "image/jpeg",
      "file_name": "0-output.jpeg",
      "file_size": 1843200
    },
    "config_file": {
      "url": "https://content.doitong.com/dev-api/2026/10/20/req_8k2m4q7x1z9c3v5b6n0p2r4t/0-output.jpeg",
      "content_type": "image/jpeg",
      "file_name": "0-output.jpeg",
      "file_size": 1843200
    },
    "debug_dataset": {
      "url": "https://content.doitong.com/dev-api/2026/10/20/req_8k2m4q7x1z9c3v5b6n0p2r4t/0-output.jpeg",
      "content_type": "image/jpeg",
      "file_name": "0-output.jpeg",
      "file_size": 1843200
    }
  },
  "outputs": [
    {
      "type": "file",
      "url": "https://content.doitong.com/dev-api/2026/10/20/req_8k2m4q7x1z9c3v5b6n0p2r4t/0-output.jpeg",
      "content_type": "image/jpeg",
      "file_size": 1843200,
      "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} \| null | Pratonton video gabungan daripada pengesahan, apabila tersedia untuk endpoint yang menghasilkan video. |
| `audio` | object {url, content_type, file_name, file_size} \| null | Audio gabungan daripada pengesahan, diberikan sebagai pratonton apabila tersedia untuk laluan audio sahaja ini: /audio-inpaint, /audio-extend-suffix, /audio-extend-prefix, /t2a, /a2a dan /v2a. |
| `lora_file` | object {url, content_type, file_name, file_size} | URL untuk pemberat LoRA terlatih dalam format .safetensors. |
| `config_file` | object {url, content_type, file_name, file_size} | Konfigurasi untuk persediaan endpoint inferens. |
| `debug_dataset` | object {url, content_type, file_name, file_size} \| null | Output nyahpepijat yang tersedia apabila `debug_dataset` didayakan: arkib yang boleh dimuat turun dan mengandungi data latihan selepas prapemprosesan. |

## Related models

- [LTX 2.3 Trainer (V2) - Audio Inpainting](https://doitong.com/developers/models/ltx23-trainer-v2/audio-inpaint.md) (`ltx23-trainer-v2/audio-inpaint`): $0.0023 / step
- [LTX 2.3 Trainer (V2) - Audio+Video Reference IC-LoRA](https://doitong.com/developers/models/ltx23-trainer-v2/ic-lora/av2av.md) (`ltx23-trainer-v2/ic-lora/av2av`): $0.0068 / step
- [LTX 2.3 Trainer (V2) - Audio+Video Reference Transformation](https://doitong.com/developers/models/ltx23-trainer-v2/av2av.md) (`ltx23-trainer-v2/av2av`): $0.0068 / step
- [LTX 2.3 Trainer (V2) - Audio-to-Audio](https://doitong.com/developers/models/ltx23-trainer-v2/a2a.md) (`ltx23-trainer-v2/a2a`): $0.0023 / step
- [LTX 2.3 Trainer (V2) - Audio-to-Audio IC-LoRA](https://doitong.com/developers/models/ltx23-trainer-v2/ic-lora/a2a.md) (`ltx23-trainer-v2/ic-lora/a2a`): $0.0023 / step
- [LTX 2.3 Trainer (V2) - Audio-to-Video](https://doitong.com/developers/models/ltx23-trainer-v2/a2v.md) (`ltx23-trainer-v2/a2v`): $0.006 / step
- [LTX 2.3 Trainer (V2) - Backward Audio Extension](https://doitong.com/developers/models/ltx23-trainer-v2/audio-extend-suffix.md) (`ltx23-trainer-v2/audio-extend-suffix`): $0.0023 / step
- [LTX 2.3 Trainer (V2) - Backward Video Extension](https://doitong.com/developers/models/ltx23-trainer-v2/extend-suffix.md) (`ltx23-trainer-v2/extend-suffix`): $0.0061 / step

## Links

- HTML page: https://doitong.com/developers/models/ltx23-trainer-v2/v2a
- 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=ltx23-trainer-v2/v2a
- Errors: https://doitong.com/developers/docs/errors
- Model details as JSON: https://api.doitong.com/v1/models/ltx23-trainer-v2/v2a