# LTX-2.3 22B Video to Video Trainer API

> Trenira LTX-2.3 22B LoRA za transformaciju videozapisa ili generiranje uvjetovano videozapisom iz referentnih videozapisa

Trenira LoRA na modelu LTX-2.3 22B za transformaciju videozapisa, koristeći zip-arhivu videozapisa ili slika (mp4, mov, avi, mkv, png, jpg, jpeg), uz preporučenih najmanje približno 10 datoteka. `number_of_steps` kreće se od 1 do 20000 (zadano 2000), a `frame_rate` prema zadanim je postavkama 25. `first_frame_conditioning_p` prema zadanim je postavkama 0.1. Validacija prihvaća najviše 2 prompta s referentnim videozapisima.

- Model id: `ltx23-v2v-trainer`
- Made by: Lightricks
- Category: Training
- Output: file
- Price: $0.0135 / step (cheapest run $27.00 (27000 API credits))
- Run: `POST https://api.doitong.com/v1/run/ltx23-v2v-trainer`
- Quote: `POST https://api.doitong.com/v1/quote/ltx23-v2v-trainer`
- Docs page: https://doitong.com/hr/developers/models/ltx23-v2v-trainer

## Pricing

Price: **$0.0135 / step**. Billed per training step (`number_of_steps`).

The full example input below costs $27.00 = 27000 API credits (2000 steps × 13.5 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-v2v-trainer` 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 ZIP arhive skupa podataka koji sadrži isključivo slike ili isključivo videozapise; skupovi s miješanim medijima nisu podržani. Ciljajte na 10 ili više datoteka, po mogućnosti veću zbirku. Prihvaćeni nastavci su .png, .jpg, .jpeg za slike te .mp4, .mov, .avi, .mkv za videozapise. Medije mogu pratiti neobavezne tekstne datoteke s opisima, pri čemu naziv svake datoteke s opisom mora odgovarati pridruženoj medijskoj datoteci. |
| `rank` |  | enum (integer) | no | `32` | `8`, `16`, `32`, `64`, `128` | Rang LoRA prilagodbe, pri čemu veća postavka povećava kapacitet uz veću potrošnju memorije. |
| `number_of_steps` |  | integer | no | `2000` | 1 – 20,000 | Ukupan broj koraka obuke. |
| `learning_rate` |  | number | no | `0.0002` | 0.000001 – 1 | Stopa učenja optimizacije koja uravnotežuje moguće ubrzanje treninga i rizik od prenaučenosti pri povećanju. |
| `number_of_frames` |  | integer | no | `89` | 9 – 121 | Broj sličica za svaki uzorak obuke. Dijeljenjem broja s 8 ostatak mora biti 1; primjeri uključuju 1, 9, 17, 25, 33, 41, 49, 57, 65, 73, 81, 89, 97. |
| `frame_rate` |  | integer | no | `25` | 8 – 60 | Ciljani broj sličica videa, mjeren u sličicama u sekundi. |
| `resolution` |  | enum (string) | no | `medium` | `low`, `medium`, `high` | Razlučivost obuke. Povećanje razlučivosti povećava zahtjeve za memorijom. |
| `aspect_ratio` |  | enum (string) | no | `1:1` | `16:9`, `1:1`, `9:16` | Omjer stranica obuke. |
| `trigger_phrase` |  | string | no | `` |  | Izraz za aktivaciju LoRA stila, umetnut na početak opisa tijekom obuke. |
| `auto_scale_input` |  | boolean | no | `false` |  | Automatsko prilagođavanje videa traženom FPS-u i broju sličica kada je omogućeno; skupovi podataka slika ostaju nepromijenjeni. |
| `split_input_into_scenes` |  | boolean | no | `true` |  | Dijeljenje scena za videozapise koji premašuju prag trajanja, omogućeno kada je true. |
| `split_input_duration_threshold` |  | number | no | `30` | 1 – 60 | Okidač dijeljenja scena izražen trajanjem u sekundama: dijele se samo videozapisi dulji od praga. |
| `debug_dataset` |  | boolean | no | `false` |  | Način pregleda pretprocesiranja za provjeru videozapisa, slika i opisa prije potpunog pokretanja obuke. Njegovim omogućivanjem alat za obuku vraća obrađeni skup podataka za obuku u arhivi dostupnoj za preuzimanje radi ručnog pregleda. |
| `first_frame_conditioning_p` |  | number | no | `0.1` | 0 – 1 | Dajte prednost transformaciji video-to-video smanjenjem učestalosti korištenja uvjetovanja prvom sličicom tijekom treninga; ova vrijednost određuje tu vjerojatnost. |
| `validation` |  | array of object {prompt, reference_video_url} | no | `[]` | ≤ 2 items | Popis ulaza za provjeru koji sadrži promptove uparene s referentnim videozapisima. |
| `validation[].prompt` |  | string | yes |  |  | Prompt koji se upotrebljava tijekom provjere. |
| `validation[].reference_video_url` |  | string (video URL) | yes |  | ≥ 1 characters | Zadajte URL videa koji se transformira tijekom provjere IC-LoRA. |
| `validation_negative_prompt` |  | string | no | `worst quality, inconsistent motion, blurry, jittery, distorted` |  | Negativni prompt primijenjen tijekom provjere. |
| `validation_number_of_frames` |  | integer | no | `89` | 9 – 121 | Broj sličica za svaki video za provjeru. |
| `validation_frame_rate` |  | integer | no | `25` | 8 – 60 | Ciljani broj sličica videozapisa za provjeru, mjeren u sličicama u sekundi. |
| `validation_resolution` |  | enum (string) | no | `high` | `low`, `medium`, `high` | Razlučivost koja se upotrebljava tijekom provjere. |
| `validation_aspect_ratio` |  | enum (string) | no | `1:1` | `16:9`, `1:1`, `9:16` | Omjer stranica koji se upotrebljava tijekom provjere. |
| `stg_scale` |  | number | no | `1` | 0 – 3 | Skala prostorno-vremenskog usmjeravanja (STG), pri čemu se preporučuje 1.0, a 0.0 isključuje 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-v2v-trainer?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-v2v-trainer?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-v2v-trainer", 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-v2v-trainer",
      "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-v2v-trainer",
  "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": 27000,
    "usd": "27.00",
    "charged": 27000,
    "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
    },
    "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 | URL svih dostupnih videozapisa za provjeru, prikazanih uz njihove referentne videozapise. |
| `lora_file` | object {url, content_type, file_name, file_size} | URL datoteke težina treniranog IC-LoRA u formatu .safetensors. |
| `config_file` | object {url, content_type, file_name, file_size} | Konfiguracija postavljanja krajnje točke za zaključivanje. |
| `debug_dataset` | object {url, content_type, file_name, file_size} \| null | Preuzimljiva arhiva za otklanjanje pogrešaka, dostupna samo za ulaze koji omogućuju `debug_dataset`; njezin sadržaj podataka za trening unaprijed je obrađen i uključuje videozapise u dekodiranom obliku. |

## 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-v2v-trainer
- 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-v2v-trainer
- Errors: https://doitong.com/developers/docs/errors
- Model details as JSON: https://api.doitong.com/v1/models/ltx23-v2v-trainer