# LTX 2.3 Trainer (V2) - Keyframe Interpolation API

> Hufunza LoRA inayozalisha mwendo kati ya fremu muhimu ya kwanza na ya mwisho, kwa hiari ikiwa na fremu ya kati

Hufunza LoRA kwa interpolation ya fremu muhimu: wakati wa inferensi unatoa fremu za kwanza na za mwisho, kisha modeli huzalisha video iliyo katikati. Washa `include_middle_keyframe` ili kufunza kwa fremu ya kwanza, ya kati na ya mwisho; kila sampuli ya uthibitishaji lazima itoe `middle_image_url`. Data huja kama zip kupitia `training_data_url`, ikiwa na hadi maingizo 2 ya uthibitishaji.

- 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/sw/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 ya `.zip` iliyo na data ya mafunzo, iliyopangwa kulingana na hali iliyochaguliwa ya mafunzo. Kila faili ya media inaweza kuwa na manukuu ya `.txt` yenye jina msingi linalolingana. |
| `rank` |  | enum (integer) | no | `32` | `8`, `16`, `32`, `64`, `128` | Daraja la urekebishaji la LoRA, linalobadilisha matumizi makubwa ya kumbukumbu kwa uwezo mkubwa zaidi kadiri mpangilio unavyoongezeka. |
| `number_of_steps` |  | integer | no | `2000` | 100 – 10,000 | Jumla ya idadi ya hatua za mafunzo. |
| `learning_rate` |  | number | no | `0.0002` | 0.000001 – 1 | Kasi ya ujifunzaji ya uboreshaji. |
| `number_of_frames` |  | integer | no | `89` | 9 – 121 | Idadi ya fremu kwa kila sampuli ya mafunzo. Kugawa idadi hiyo kwa 8 lazima kuache salio la 1; mifano ni 1, 9, 17, 25, 33, 41, 49, 57, 65, 73, 81, 89, 97. |
| `frame_rate` |  | integer | no | `24` | 8 – 60 | Kasi lengwa ya fremu ya video ya mafunzo kwa fremu kwa sekunde. Kasi asilia ya LTX-2.3 ni 24. |
| `resolution` |  | enum (string) | no | `medium` | `low`, `medium`, `high` | Mwonekano wa mafunzo. Kuongeza mwonekano huongeza mahitaji ya kumbukumbu. |
| `aspect_ratio` |  | enum (string) | no | `1:1` | `16:9`, `1:1`, `9:16` | Uwiano wa mafunzo. |
| `trigger_phrase` |  | string | no | `` |  | Kauli ya uanzishaji wa mtindo wa LoRA, inayowekwa mwanzoni mwa manukuu wakati wa mafunzo. |
| `auto_scale_input` |  | boolean | no | `false` |  | Marekebisho ya video kiotomatiki ili yalingane na FPS na idadi ya fremu iliyoombwa yanapowashwa; seti za data za picha hazibadilishwi. |
| `split_input_into_scenes` |  | boolean | no | `true` |  | Ugawaji wa mandhari kwa video zinazozidi kizingiti cha muda, ukiwashwa wakati true. |
| `split_input_duration_threshold` |  | number | no | `30` | 1 – 60 | Kichocheo cha kugawa mandhari kinachoonyeshwa kama muda kwa sekunde: video ndefu kuliko kizingiti pekee ndizo hugawanywa. |
| `debug_dataset` |  | boolean | no | `false` |  | Hali ya ukaguzi wa uchakataji awali kwa kuangalia video, picha na manukuu kabla ya uendeshaji kamili wa mafunzo. Kuiwasha humfanya mkufunzi arudishe seti ya data ya mafunzo iliyochakatwa katika jalada linaloweza kupakuliwa kwa ukaguzi wa mikono. |
| `validation` |  | array of object {prompt, start_image_url, end_image_url, middle_image_url} | no | `[]` | ≤ 2 items | Data ya uthibitishaji iliyotolewa kama orodha; ingizo linaunganisha picha za keyframe na kidokezo. |
| `validation[].prompt` |  | string | yes |  |  | Kidokezo kinachotumiwa wakati wa uthibitishaji. |
| `validation[].start_image_url` |  | string (image URL) | yes |  | ≥ 1 characters | URL ya picha ya keyframe kwa fremu ya mwanzo. |
| `validation[].end_image_url` |  | string (image URL) | yes |  | ≥ 1 characters | URL ya picha ya keyframe kwa fremu ya mwisho. |
| `validation[].middle_image_url` |  | string (image URL) \| null | no |  |  | URL ya picha ya keyframe ya kati kwa interpolation ya first+middle+last. Uendeshaji wenye `include_middle_keyframe=true` huuhitaji; vinginevyo ni ya hiari. |
| `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.` |  | Kidokezo hasi kinachotumiwa wakati wa uthibitishaji, ambao hutumia mchakato wa hakikisho wa hatua moja. Kwa kuwa mchakato huo hukadiria uelekezaji wa uzalishaji uliosafishwa wa hatua mbili, uelekezaji na ubora wa hakikisho hutofautiana na matokeo ya mwisho. |
| `validation_number_of_frames` |  | integer | no | `89` | 9 – 121 | Idadi ya fremu kwa kila video ya uthibitishaji. |
| `validation_frame_rate` |  | integer | no | `24` | 8 – 60 | Kasi lengwa ya fremu za video za uthibitishaji, kwa fremu kwa sekunde; LTX-2.3 huendesha asili kwa 24. |
| `validation_resolution` |  | enum (string) | no | `high` | `low`, `medium`, `high` | Mwonekano unaotumiwa wakati wa uthibitishaji. |
| `validation_aspect_ratio` |  | enum (string) | no | `1:1` | `16:9`, `1:1`, `9:16` | Uwiano unaotumiwa wakati wa uthibitishaji. |
| `stg_scale` |  | number | no | `1` | 0 – 3 | Kipimo cha Mwongozo wa Anga na Muda (STG), ambapo 1.0 inapendekezwa na 0.0 huzima STG. |
| `include_middle_keyframe` |  | boolean | no | `false` |  | Kujumuisha keyframe ya kati kwa uzalishaji wa video: true huhitaji `middle_image_url` katika kila sampuli ya uthibitishaji na huhifadhi fremu ya kati pamoja na ya kwanza na ya mwisho, badala ya kutumia ya kwanza na ya mwisho pekee. |

## 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 | Hakikisho la video lililounganishwa kutoka kwa uthibitishaji, linapopatikana kwa endpoint zinazozalisha video. |
| `audio` | object {url, content_type, file_name, file_size} \| null | Sauti iliyounganishwa kutoka kwa uthibitishaji, inayotolewa kama hakikisho inapopatikana kwa njia hizi za sauti pekee: /audio-inpaint, /audio-extend-suffix, /audio-extend-prefix, /t2a, /a2a, na /v2a. |
| `lora_file` | object {url, content_type, file_name, file_size} | URL ya uzito wa LoRA uliofunzwa katika umbizo la .safetensors. |
| `config_file` | object {url, content_type, file_name, file_size} | Usanidi wa kuweka endpoint ya uelekezaji. |
| `debug_dataset` | object {url, content_type, file_name, file_size} \| null | Tokeo la utatuzi linalopatikana `debug_dataset` inapowashwa: jalada linaloweza kupakuliwa na lenye data ya mafunzo baada ya uchakataji awali. |

## 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