# Ideogram V4.0q LoRA Trainer API

> Entraîne un LoRA personnalisé pour Ideogram V4 à partir d’un zip d’images légendées

Entraîne un LoRA sur votre propre jeu de données pour la personnalisation ou un style particulier. `images_data_url` pointe vers un zip d’images, dont les légendes sont lues dans des fichiers .txt de même nom, et `default_caption` complète celles qui manquent. `steps` va de 100 à 40000 (par défaut 1000), tandis que `learning_rate` et `resolution` sont réglables. Renvoie le fichier de poids LoRA et un fichier de configuration.

- 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/fr/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 d'un ZIP de données d'entraînement contenant des images et des légendes, chaque légende étant stockée dans un fichier .txt partageant le nom de base de son image. L'entraîneur utilise le jeu de données limité aux cibles préparé par prepare_dataset_dir. |
| `steps` |  | integer | no | `1000` | 100 – 40,000 | Nombre d'étapes pour l'entraînement LoRA. |
| `default_caption` |  | string \| null | no |  |  | Légende appliquée à chaque image lorsque force_default_caption vaut true, remplaçant les fichiers de légendes ; sinon, elle ne s'applique qu'aux images dépourvues de fichier de légende. |
| `resolution` |  | string | no | `auto` |  | Dimensions des images d'entraînement, spécifiées par un préréglage, auto ou une chaîne WIDTHxHEIGHT personnalisée, chaque dimension étant divisible par 16. Le recadrage centré n'agrandit jamais les images ; auto sélectionne le recadrage maximal commun au jeu de données ne nécessitant aucun agrandissement. Les préréglages sont 1024x1024 (carré), 1536x1024 (paysage), 1024x1536 (portrait), 1920x1088 (écran large), 2048x768 (ultra-large), 1024x1792 (phone_wallpaper) et 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 des poids LoRA d'Ideogram V4 produits par l'entraînement. |
| `config_file` | object {url, content_type, file_name, file_size} | URL de la configuration d'entraînement disponible publiquement. |

## 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