# LTX 2.3 Trainer (V2) - Keyframe Interpolation API

> Uči LoRA, ki ustvari gibanje med prvim in zadnjim ključnim kadrom, po želji tudi s srednjim kadrom

Uči LoRA za interpolacijo ključnih kadrov: pri izvajanju podate prvi in zadnji kader, model pa ustvari vmesni video. Omogočite `include_middle_keyframe`, da se model uči na prvem, srednjem in zadnjem kadru; vsak validacijski vzorec mora nato zagotoviti `middle_image_url`. Podatki so v arhivu zip prek `training_data_url`, z največ 2 validacijskima vnosoma.

- Model id: `ltx23-trainer-v2/interpolate`
- Made by: Lightricks
- Category: Training
- Output: file
- Price: $0.0024 / step (cheapest run $4.80 (4800 API credits))
- Run: `POST https://api.doitong.com/v1/run/ltx23-trainer-v2/interpolate`
- Quote: `POST https://api.doitong.com/v1/quote/ltx23-trainer-v2/interpolate`
- Docs page: https://doitong.com/sl/developers/models/ltx23-trainer-v2/interpolate

## Pricing

Price: **$0.0024 / step**. Billed per training step (`number_of_steps`).

The full example input below costs $4.80 = 4800 API credits (2000 steps × 2.4 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/interpolate` 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 datoteke `.zip` s podatki za učenje, organiziranimi glede na izbrani način učenja. Vsaka predstavnostna datoteka ima lahko spremljajoč opis `.txt` z enakim osnovnim imenom. |
| `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` | 100 – 10,000 | Skupno število korakov učenja. |
| `learning_rate` |  | number | no | `0.0002` | 0.000001 – 1 | Hitrost učenja pri optimizaciji. |
| `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 | `24` | 8 – 60 | Ciljna hitrost sličic učnega videa v sličicah na sekundo. Naravna hitrost za LTX-2.3 je 24. |
| `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. |
| `validation` |  | array of object {prompt, start_image_url, end_image_url, middle_image_url} | no | `[]` | ≤ 2 items | Validacijski podatki, posredovani kot seznam; vnos združuje ključne sličice s pozivom. |
| `validation[].prompt` |  | string | yes |  |  | Poziv, uporabljen med preverjanjem. |
| `validation[].start_image_url` |  | string (image URL) | yes |  | ≥ 1 characters | URL slike ključne sličice za začetno sličico. |
| `validation[].end_image_url` |  | string (image URL) | yes |  | ≥ 1 characters | URL slike ključne sličice za končno sličico. |
| `validation[].middle_image_url` |  | string (image URL) \| null | no |  |  | URL slike srednje ključne sličice za interpolacijo first+middle+last. Izvajanja z `include_middle_keyframe=true` jo zahtevajo; sicer je neobvezna. |
| `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.` |  | Negativni poziv, uporabljen med preverjanjem, ki uporablja predogledni proces z eno stopnjo. Ker ta proces približa destilirano produkcijsko sklepanje z dvema stopnjama, se njegovo vodenje in kakovost predogleda razlikujeta od končnih rezultatov. |
| `validation_number_of_frames` |  | integer | no | `89` | 9 – 121 | Število sličic za vsak video preverjanja. |
| `validation_frame_rate` |  | integer | no | `24` | 8 – 60 | Ciljna hitrost sličic za videe preverjanja v sličicah na sekundo; LTX-2.3 izvorno deluje pri 24. |
| `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. |
| `include_middle_keyframe` |  | boolean | no | `false` |  | Vključitev srednje ključne sličice pri generiranju videa: true zahteva `middle_image_url` v vsakem validacijskem vzorcu in ohrani srednjo sličico skupaj s prvo in zadnjo, namesto uporabe samo prve in zadnje. |

## 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/interpolate?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/interpolate?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/interpolate", 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/interpolate",
      "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/interpolate",
  "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": 4800,
    "usd": "4.80",
    "charged": 4800,
    "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 | Združen video predogled preverjanja, kadar je na voljo za končne točke, ki ustvarjajo video. |
| `audio` | object {url, content_type, file_name, file_size} \| null | Združen zvok preverjanja, na voljo kot predogled za te poti samo z zvokom: /audio-inpaint, /audio-extend-suffix, /audio-extend-prefix, /t2a, /a2a in /v2a. |
| `lora_file` | object {url, content_type, file_name, file_size} | URL uteži naučenega 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 | Izhod za odpravljanje napak, na voljo ob omogočenem `debug_dataset`: arhiv, ki ga je mogoče prenesti in vsebuje učne podatke po predobdelavi. |

## 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/interpolate
- 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/interpolate
- Errors: https://doitong.com/developers/docs/errors
- Model details as JSON: https://api.doitong.com/v1/models/ltx23-trainer-v2/interpolate