# Ideogram V4.0q LoRA Trainer API

> Melatih LoRA kustom untuk Ideogram V4 dari zip gambar bercaption

Menyesuaikan LoRA pada dataset Anda sendiri untuk personalisasi atau gaya tertentu. `images_data_url` menunjuk ke zip gambar, dengan takarir yang dibaca dari file .txt bernama sama, dan `default_caption` mengisi takarir yang hilang. `steps` berada dalam rentang 100 hingga 40000 (bawaan 1000), dan `learning_rate` serta `resolution` dapat disesuaikan. Mengembalikan file bobot LoRA dan file konfigurasi.

- Model id: `ideogram/v4/trainer`
- Made by: Ideogram
- Category: Training
- Output: file
- Price: $0.00675 / step (cheapest run $6.75 (6750 API credits))
- Run: `POST https://api.doitong.com/v1/run/ideogram/v4/trainer`
- Quote: `POST https://api.doitong.com/v1/quote/ideogram/v4/trainer`
- Docs page: https://doitong.com/id/developers/models/ideogram/v4/trainer

## Pricing

Price: **$0.00675 / step**. Billed per training step (`steps`).

The full example input below costs $6.75 = 6750 API credits (1000 steps × 6.75 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/ideogram/v4/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 |
|---|---|---|---|---|---|---|
| `images_data_url` |  | string | yes |  |  | URL ZIP data pelatihan yang berisi gambar dan caption, dengan setiap caption disimpan dalam file .txt yang menggunakan stem nama file gambarnya. Trainer bekerja dari dataset khusus target yang disiapkan oleh prepare_dataset_dir. |
| `steps` |  | integer | no | `1000` | 100 – 40,000 | Jumlah langkah untuk pelatihan LoRA. |
| `default_caption` |  | string \| null | no |  |  | Caption yang diterapkan ke setiap gambar saat force_default_caption bernilai true, menggantikan file caption; jika tidak, caption ini hanya digunakan untuk gambar yang tidak memiliki file caption. |
| `resolution` |  | string | no | `auto` |  | Dimensi gambar pelatihan, yang ditentukan sebagai preset, auto, atau string WIDTHxHEIGHT kustom dengan setiap dimensi habis dibagi 16. Pemotongan tengah tidak pernah memperbesar gambar; auto memilih potongan terbesar yang sama-sama dimiliki dataset dan tidak memerlukan pembesaran. Presetnya adalah 1024x1024 (square), 1536x1024 (landscape), 1024x1536 (portrait), 1920x1088 (widescreen), 2048x768 (ultrawide), 1024x1792 (phone_wallpaper), dan 1584x400 (social_banner). |
| `learning_rate` |  | number | no | `0.0001` | 0.000001 – 0.01 |  |

## Example input

Required parameters only:

```json
{
  "images_data_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
}
```

A fuller example:

```json
{
  "images_data_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
}
```

## 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/ideogram/v4/trainer?wait=20" \
  -H "Authorization: Bearer $DOITONG_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "images_data_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
  }'

# 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/ideogram/v4/trainer?wait=20", {
  method: "POST",
  headers,
  body: JSON.stringify({
    "images_data_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
  }),
});
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 = {
    "images_data_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg",
}

# Run the model; wait up to 20 s for the finished result in the same call
r = requests.post(API + "/run/ideogram/v4/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": "ideogram/v4/trainer",
      "input": {
        "images_data_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
      },
      "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": "ideogram/v4/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": 6750,
    "usd": "6.75",
    "charged": 6750,
    "refunded": 0
  },
  "input": {
    "images_data_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
  },
  "output": {
    "diffusers_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
    }
  },
  "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 |
|---|---|---|
| `diffusers_lora_file` | object {url, content_type, file_name, file_size} | URL bobot LoRA Ideogram V4 yang dihasilkan oleh pelatihan. |
| `config_file` | object {url, content_type, file_name, file_size} | URL konfigurasi pelatihan yang tersedia untuk publik. |

## Related models

- [Ideogram V4.0 Text to Image](https://doitong.com/developers/models/ideogram/v4.md) (`ideogram/v4`): from $0.0075 / megapixel of output image
- [Ideogram V4.0q \[fast\]](https://doitong.com/developers/models/ideogram/v4/fast.md) (`ideogram/v4/fast`): from $0.00525 / megapixel of output image
- [Ideogram V4.0q \[instant\]](https://doitong.com/developers/models/ideogram/v4/instant.md) (`ideogram/v4/instant`): $0.0075 / megapixel of output image
- [Ideogram V4.0q Text to Image (LoRA)](https://doitong.com/developers/models/ideogram/v4/lora.md) (`ideogram/v4/lora`): from $0.0113 / megapixel of output image
- [Ideogram V4.0q Image to Image](https://doitong.com/developers/models/ideogram/v4/image-to-image.md) (`ideogram/v4/image-to-image`): from $0.0075 / megapixel of output image
- [Ideogram V4.0q Image to Image LoRA](https://doitong.com/developers/models/ideogram/v4/image-to-image/lora.md) (`ideogram/v4/image-to-image/lora`): from $0.0113 / megapixel of output image
- [Ideogram V4.0q Tiling](https://doitong.com/developers/models/ideogram/v4/tiling.md) (`ideogram/v4/tiling`): from $0.03 / megapixel
- [Ideogram V4.0q Tiling LoRA](https://doitong.com/developers/models/ideogram/v4/tiling/lora.md) (`ideogram/v4/tiling/lora`): from $0.0338 / megapixel

## Links

- HTML page: https://doitong.com/developers/models/ideogram/v4/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=ideogram/v4/trainer
- Errors: https://doitong.com/developers/docs/errors
- Model details as JSON: https://api.doitong.com/v1/models/ideogram/v4/trainer