# LTX-2.3 22B Video to Video Trainer API

> Uči LoRA LTX-2.3 22B za transformacijo videa ali ustvarjanje, pogojeno z referenčnimi videi

Uči LoRA na modelu LTX-2.3 22B za transformacijo videa z uporabo arhiva zip videov ali slik (mp4, mov, avi, mkv, png, jpg, jpeg); priporočenih je vsaj približno 10 datotek. `number_of_steps` sega od 1 do 20000 (privzeto 2000), `frame_rate` pa je privzeto 25. `first_frame_conditioning_p` je privzeto 0.1. Validacija sprejme največ 2 poziva z referenčnimi videi.

- 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.ru/v1/run/ltx23-v2v-trainer`
- Quote: `POST https://api.doitong.ru/v1/quote/ltx23-v2v-trainer`
- Docs page: https://doitong.com/sl/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.ru/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 arhiva ZIP za nabor podatkov, ki vsebuje izključno slike ali izključno videe; mešani nabori predstavnosti niso podprti. Priporočamo 10 datotek ali več, po možnosti večjo zbirko. Sprejete končnice so .png, .jpg, .jpeg za slike ter .mp4, .mov, .avi, .mkv za videe. Predstavnost lahko spremljajo neobvezne besedilne datoteke z napisi, pri čemer mora biti ime vsake datoteke z napisom enako imenu povezane predstavnostne datoteke. |
| `rank` |  | enum (integer) | no | `32` | `8`, `16`, `32`, `64`, `128` | Rang prilagoditve LoRA, pri katerem večja nastavitev pomeni večjo porabo pomnilnika in večjo zmogljivost. |
| `number_of_steps` |  | integer | no | `2000` | 1 – 20,000 | Skupno število korakov učenja. |
| `learning_rate` |  | number | no | `0.0002` | 0.000001 – 1 | Stopnja učenja optimizacije, ki uravnava morebitno pohitritev učenja in tveganje preprileganja pri povečanju. |
| `number_of_frames` |  | integer | no | `89` | 9 – 121 | Število sličic za vsak učni vzorec. Deljenje števila z 8 mora pustiti ostanek 1; primeri so 1, 9, 17, 25, 33, 41, 49, 57, 65, 73, 81, 89, 97. |
| `frame_rate` |  | integer | no | `25` | 8 – 60 | Ciljna hitrost sličic videa, merjena v sličicah na sekundo. |
| `resolution` |  | enum (string) | no | `medium` | `low`, `medium`, `high` | Ločljivost učenja. Povečanje ločljivosti poveča zahteve po pomnilniku. |
| `aspect_ratio` |  | enum (string) | no | `1:1` | `16:9`, `1:1`, `9:16` | Razmerje stranic pri učenju. |
| `trigger_phrase` |  | string | no | `` |  | Besedna zveza za aktivacijo sloga LoRA, vstavljena na začetek opisov med učenjem. |
| `auto_scale_input` |  | boolean | no | `false` |  | Samodejna prilagoditev videa zahtevanemu FPS in številu sličic, ko je omogočena; nabori slik ostanejo nespremenjeni. |
| `split_input_into_scenes` |  | boolean | no | `true` |  | Razdeljevanje prizorov pri videih, ki presegajo prag trajanja, omogočeno, ko je true. |
| `split_input_duration_threshold` |  | number | no | `30` | 1 – 60 | Sprožilec razdeljevanja prizorov, izražen kot trajanje v sekundah: razdelijo se samo videi, daljši od praga. |
| `debug_dataset` |  | boolean | no | `false` |  | Način pregleda predobdelave za preverjanje videov, slik in opisov pred celotnim učenjem. Z omogočanjem trener vrne obdelani učni nabor v arhivu, ki ga je mogoče prenesti in ročno pregledati. |
| `first_frame_conditioning_p` |  | number | no | `0.1` | 0 – 1 | Dajte prednost pretvorbi video-to-video tako, da zmanjšate pogostost uporabe pogojevanja na prvi sličici pri učenju; ta vrednost določa verjetnost. |
| `validation` |  | array of object {prompt, reference_video_url} | no | `[]` | ≤ 2 items | Seznam vhodov za preverjanje, ki vsebuje pozive, povezane z referenčnimi videi. |
| `validation[].prompt` |  | string | yes |  |  | Poziv, uporabljen med preverjanjem. |
| `validation[].reference_video_url` |  | string (video URL) | yes |  | ≥ 1 characters | Video za pretvorbo med validacijo IC-LoRA posredujte prek njegovega URL-ja. |
| `validation_negative_prompt` |  | string | no | `worst quality, inconsistent motion, blurry, jittery, distorted` |  | Negativni poziv, uporabljen med validacijo. |
| `validation_number_of_frames` |  | integer | no | `89` | 9 – 121 | Število sličic za vsak video preverjanja. |
| `validation_frame_rate` |  | integer | no | `25` | 8 – 60 | Ciljna hitrost sličic validacijskega videa, merjena v sličicah na sekundo. |
| `validation_resolution` |  | enum (string) | no | `high` | `low`, `medium`, `high` | Ločljivost, uporabljena med preverjanjem. |
| `validation_aspect_ratio` |  | enum (string) | no | `1:1` | `16:9`, `1:1`, `9:16` | Razmerje stranic, uporabljeno med preverjanjem. |
| `stg_scale` |  | number | no | `1` | 0 – 3 | Merilo prostorsko-časovnega vodenja (STG), pri čemer je priporočena vrednost 1.0, vrednost 0.0 pa STG izklopi. |

## 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.ru/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.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/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.ru/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.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": "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.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} \| null | URL vseh razpoložljivih validacijskih videov, prikazanih ob njihovih referenčnih videih. |
| `lora_file` | object {url, content_type, file_name, file_size} | URL datoteke uteži naučenega IC-LoRA v obliki .safetensors. |
| `config_file` | object {url, content_type, file_name, file_size} | Konfiguracija za nastavitev končne točke sklepanja. |
| `debug_dataset` | object {url, content_type, file_name, file_size} \| null | Arhiv za odpravljanje napak, na voljo samo za vhode, ki omogočajo `debug_dataset`; njegova vsebina učnih podatkov je predobdelana in vključuje videe v dekodirani obliki. |

## 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.ru/v1/models/ltx23-v2v-trainer