# FLUX 2 Lora API

> Kuputuhi-ki-te-whakaahua FLUX 2 e whakamahi ana kia 3 ngā taumaha LoRA ritenga mō te āhua, te putanga pai ake rānei

Ka whakaputa atahanga mai i tētahi tohutohu me te whakamahi i ngā taumahatanga LoRA kei `loras`, kia 3 te mōrahi, hei URL, repo ID, ara rānei. Kei roto ko `guidance_scale` (0 ki te 20), 4 ki te 50 ngā kaupae whakatauira, he taumata `acceleration`, me te whakawhānui tohutohu hei kōwhiringa. Kia 4 ngā atahanga ka whakaputaina hei jpeg, png, webp rānei.

- Model id: `flux-2/lora`
- Made by: Black Forest Labs
- Category: Text to Image
- Output: image
- Price: $0.021 / megapixel (cheapest run $0.021 (21 API credits))
- Run: `POST https://api.doitong.com/v1/run/flux-2/lora`
- Quote: `POST https://api.doitong.com/v1/quote/flux-2/lora`
- Docs page: https://doitong.com/mi/developers/models/flux-2/lora

## Pricing

Price: **$0.021 / megapixel**. Billed per megapixel of output (width × height of every image). Each image is rounded up to a whole megapixel.

The full example input below costs $0.021 = 21 API credits (1 MP × 21 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/flux-2/lora` 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

Send either the canonical name or the native field name (not both). Canonical names are the same across models.

| Parameter | Canonical name | Type | Required | Default | Allowed values / range | Description |
|---|---|---|---|---|---|---|
| `prompt` |  | string | yes |  |  | Te tohutohu e ārahi ana i te whakaputanga atahanga. |
| `guidance_scale` |  | number | no | `2.5` | 0 – 20 | Te tautuhinga ū ki te tohutohu mō te rapunga a te tauira i tētahi atahanga pānga hei whakaatu, ka whakaaturia hei tauine ārahitanga. |
| `seed` |  | integer \| null | no |  |  | Te whakakapi kākano whakaputanga; mā te waiho ka kōwhiri matapōkere te whakaputanga i tētahi kākano. |
| `num_inference_steps` |  | integer | no | `28` | 4 – 50 | Tau o ngā hipanga whakatauira hei whakahaere. |
| `image_size` |  | object {width, height} \| enum (string) | no | `landscape_4_3` | `square_hd`, `square`, `portrait_4_3`, `portrait_16_9`, `landscape_4_3`, `landscape_16_9` | Te rahi atahanga putanga, mai i te iti rawa 512 ki te nui rawa 2048 pika mō ia tuaka. |
| `num_images` | `num_outputs` | integer | no | `1` | 1 – 4 | Te tatau atahanga e tonoa ana mō te whakaputanga. |
| `acceleration` |  | enum (string) | no | `regular` | `none`, `regular`, `high` | Tautuhinga whakatere mō te whakaputa atahanga. |
| `enable_prompt_expansion` |  | boolean | no | `false` |  | Te whakarei tohutohu aunoa: mā true e whakawhānui te tohutohu hei whakapai i ngā hua. |
| `enable_safety_checker` |  | boolean | no | `true` |  | Te tirotiro haumaru, ka whakahoki atahanga pango hei whakakapi i ngā atahanga kua tohungia he haumaru-kore. Mā true e whakahohe te tirotiro; mā false e mono anake mō ngā pūkete whai mana, ā, ka tirotirohia ngā tono kāore he mana ahakoa te aha. |
| `output_format` |  | enum (string) | no | `png` | `jpeg`, `png`, `webp` | Te hōputu kōnae mō te atahanga ka puta. |
| `loras` |  | array of object {path, scale} | no | `[]` |  | Whakamahia kia 3 ngā taumaha LoRA mā te whakarārangi i ō rātou wāhi hei URL, ID putunga HuggingFace, ara paetata rānei. |
| `loras[].path` |  | string | yes |  |  | Te wāhi o ngā taumaha LoRA, kua whakaahuatia hei URL, hei ID putunga HuggingFace i te momo owner/repo, hei ara paetata rānei. |
| `loras[].scale` |  | number | no | `1` | 0 – 4 | Te tauwehe tauine mō LoRA, mai i te 0.0 ki te 4.0. |

## Example input

Required parameters only:

```json
{
  "prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
}
```

A fuller example:

```json
{
  "prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
}
```

## 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-2/lora?wait=20" \
  -H "Authorization: Bearer $DOITONG_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
  }'

# 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-2/lora?wait=20", {
  method: "POST",
  headers,
  body: JSON.stringify({
    "prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
  }),
});
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 = {
    "prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
}

# Run the model; wait up to 20 s for the finished result in the same call
r = requests.post(API + "/run/flux-2/lora", 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-2/lora",
      "input": {
        "prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
      },
      "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-2/lora",
  "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": 21,
    "usd": "0.021",
    "charged": 21,
    "refunded": 0
  },
  "input": {
    "prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
  },
  "output": {
    "images": [
      {
        "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,
        "width": 1024,
        "height": 768
      }
    ],
    "timings": {},
    "seed": 42,
    "has_nsfw_concepts": [
      false
    ],
    "prompt": "string"
  },
  "outputs": [
    {
      "type": "image",
      "url": "https://content.doitong.com/dev-api/2026/10/20/req_8k2m4q7x1z9c3v5b6n0p2r4t/0-output.jpeg",
      "content_type": "image/jpeg",
      "file_size": 1843200,
      "width": 1024,
      "height": 768,
      "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 |
|---|---|---|
| `images` | array of object {url, content_type, file_name, file_size, width, height} | Ngā atahanga i whakaputaina e te tauira. |
| `timings` | object |  |
| `seed` | integer | Kākano whakaputa atahanga, tae atu ki te uara i kōwhiria matapōkeretia mēnā kāore i tukuna he kākano ki te tāuru; ki te kore, ka tukurua te uara i tukuna. |
| `has_nsfw_concepts` | array of boolean | Ka tohu mēnā ka puta ngā ariā NSFW i ngā atahanga kua whakaputaina. |
| `prompt` | string | Te tohutohu e whakamahia ana i te whakaputanga atahanga. |

## Related models

- [FLUX 2 Flash](https://doitong.com/developers/models/flux-2/flash.md) (`flux-2/flash`): $0.005 / megapixel
- [FLUX 2 Turbo](https://doitong.com/developers/models/flux-2/turbo.md) (`flux-2/turbo`): $0.008 / megapixel
- [FLUX.2 \[dev\]](https://doitong.com/developers/models/flux-2.md) (`flux-2`): $0.012 / megapixel
- [FLUX.2 \[pro\]](https://doitong.com/developers/models/flux-2-pro.md) (`flux-2-pro`): $0.015 / megapixel of output image
- [FLUX 2 Edit](https://doitong.com/developers/models/flux-2/edit.md) (`flux-2/edit`): $0.012 / megapixel
- [FLUX 2 Flash Edit](https://doitong.com/developers/models/flux-2/flash/edit.md) (`flux-2/flash/edit`): $0.005 / megapixel
- [FLUX 2 Lora Edit](https://doitong.com/developers/models/flux-2/lora/edit.md) (`flux-2/lora/edit`): $0.021 / megapixel
- [FLUX 2 Pro Edit](https://doitong.com/developers/models/flux-2-pro/edit.md) (`flux-2-pro/edit`): $0.105 / run

## Links

- HTML page: https://doitong.com/developers/models/flux-2/lora
- 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-2/lora
- Errors: https://doitong.com/developers/docs/errors
- Model details as JSON: https://api.doitong.com/v1/models/flux-2/lora