# Train Flux LoRA API

> Bir kişiyi, konuyu veya stili öğrenmek için görüntülerinizin bulunduğu bir zip'te Flux LoRA'sı eğitir

Eşleşen başlık metni dosyaları içerebilen bir görüntü zip arşivinden (`images_data_url`) LoRA'yı ince ayarlar. Kavramı adlandırmak için `trigger_word`, stil eğitimi için ise segmentasyon ve başlıklandırmayı kapatan `is_style` kullanılır. `create_masks` kaybı konulara göre ağırlıklandırır; `steps` 1 ile 10000 arasında olabilir. Diffusers LoRA ağırlıkları ile bir yapılandırma dosyasını döndürür.

- Model id: `flux-lora-fast-training`
- Made by: Black Forest Labs
- Category: Training
- Output: file
- Price per run: from $0.002 / run (cheapest run $0.002 (2 API credits))
- Run: `POST https://api.doitong.com/v1/run/flux-lora-fast-training`
- Quote: `POST https://api.doitong.com/v1/quote/flux-lora-fast-training`
- Docs page: https://doitong.com/tr/developers/models/flux-lora-fast-training

## Pricing

Price: **from $0.002 / run** (the lowest tier; the quote prices your exact input). Price per run: the input files are measured before the run (length, resolution, frame rate). The quote measures the same files and is exactly what the run charges.

The full example input below costs $2.00 = 2000 API credits (1 run × $2.00).

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/flux-lora-fast-training` 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 |  |  | Görselleri bir ZIP arşivi URL'si üzerinden sağlayın; isteğe bağlı olarak her görseli aynı adlı bir açıklama metni dosyasıyla eşleştirin. En az 4 görsel hedefleyin; daha büyük görsel kümeleri genellikle daha iyidir. |
| `trigger_word` |  | string \| null | no |  |  | Açıklamalar eksik olduğunda açıklama yerine kullanılacak bir tetikleyici sözcük sağlayın; mevcut açıklamalar trigger_word kullanımını engeller. Tetikleyici sözcük kullanmamak için None olarak ayarlayın. |
| `create_masks` |  | boolean | no | `true` |  | True ile eğitim kaybının maske tabanlı ağırlıklandırmasını etkinleştirin; insan görsellerinde mümkün olduğunda yüz maskesi kullanılır. |
| `steps` |  | integer \| null | no |  | 1 – 10,000 | LoRA için eğitim adımı sayısı. |
| `is_style` |  | boolean | no | `false` |  | True ile stil eğitimini etkinleştirin ve stili tetikleyici sözcükle belirtin. Bu modda tetikleyici sözcük açıklamanın yerini alır ve segmentasyon devre dışı bırakılır. |
| `is_input_format_already_preprocessed` |  | boolean | no | `false` |  | Sağlanan verilerin ön işleme durumu: True, veri kümesinin zaten ön işlenmiş olduğunu belirtir. Varsayılan False ise 'photo.jpg' ve 'photo.txt' gibi eşleşen temel adlara sahip ham görsel/açıklama çiftleri gerekir. |
| `data_archive_format` |  | string \| null | no |  |  | Atlanırsa URL'sinden çıkarılan arşiv biçimi. |

## 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/flux-lora-fast-training?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/flux-lora-fast-training?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/flux-lora-fast-training", 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": "flux-lora-fast-training",
      "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": "flux-lora-fast-training",
  "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": 2000,
    "usd": "2.00",
    "charged": 2000,
    "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
    },
    "debug_preprocessed_output": {
      "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} | diffusers biçimindeki eğitilmiş LoRA ağırlıklarına işaret eden URL. |
| `config_file` | object {url, content_type, file_name, file_size} | Eğitim yapılandırma dosyası URL'si. |
| `debug_preprocessed_output` | object {url, content_type, file_name, file_size} \| null | Ön işlemeden sonra görselleri bulunduran URL. |

## Related models

- [FLUX 2 \[klein\] 9b Base Trainer](https://doitong.com/developers/models/flux-2-klein-9b-base-trainer.md) (`flux-2-klein-9b-base-trainer`): $0.0043 / step
- [Flux 2 Klein 9B Base Trainer](https://doitong.com/developers/models/flux-2-klein-9b-base-trainer/edit.md) (`flux-2-klein-9b-base-trainer/edit`): $0.0139 / step
- [FLUX 2 Trainer](https://doitong.com/developers/models/flux-2-trainer.md) (`flux-2-trainer`): $0.0064 / step
- [FLUX 2 Trainer Edit](https://doitong.com/developers/models/flux-2-trainer/edit.md) (`flux-2-trainer/edit`): $0.0389 / step
- [FLUX 2 Trainer V2](https://doitong.com/developers/models/flux-2-trainer-v2.md) (`flux-2-trainer-v2`): $0.0064 / step
- [FLUX 2 Trainer V2 Edit](https://doitong.com/developers/models/flux-2-trainer-v2/edit.md) (`flux-2-trainer-v2/edit`): $0.0389 / step
- [Flux Kontext Trainer](https://doitong.com/developers/models/flux-kontext-trainer.md) (`flux-kontext-trainer`): from $1.25 / run
- [Train Flux LoRAs For Portraits](https://doitong.com/developers/models/flux-lora-portrait-trainer.md) (`flux-lora-portrait-trainer`): from $2.40 / run

## Links

- HTML page: https://doitong.com/developers/models/flux-lora-fast-training
- 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=flux-lora-fast-training
- Errors: https://doitong.com/developers/docs/errors
- Model details as JSON: https://api.doitong.com/v1/models/flux-lora-fast-training