# Optimized Latent Consistency (SDv1.5) API

> Transformasi gambar-ke-gambar dengan sedikit langkah pada Stable Diffusion 1.5 menggunakan konsistensi laten, dengan kontrol kekuatan

Mengubah gaya atau memodifikasi gambar dasar dari prompt teks menggunakan pendekatan konsistensi laten yang hanya memerlukan beberapa langkah. `num_inference_steps` default-nya 4 dan dapat mencapai 12. `strength` (0 hingga 1) menentukan seberapa jauh hasil menyimpang dari input, dan hingga 8 gambar dapat dikembalikan per panggilan. Menerima `mask_url`, `negative_prompt`, dan `seed` opsional.

- Model id: `lcm-sd15-i2i`
- Made by: Open model
- Category: Image Editing
- Output: image
- Estimated price per run: $0.007 / image (cheapest run $0.007 (7 API credits))
- Run: `POST https://api.doitong.com/v1/run/lcm-sd15-i2i`
- Quote: `POST https://api.doitong.com/v1/quote/lcm-sd15-i2i`
- Docs page: https://doitong.com/id/developers/models/lcm-sd15-i2i

## Pricing

Price: **$0.007 / image**. Estimated from the typical cost of one run, per output (`num_images`). The quote is exactly what the run charges.

The full example input below costs $0.007 = 7 API credits (1 image × 7 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/lcm-sd15-i2i` 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 |  |  | Jelaskan gambar yang ingin dibuat sedetail mungkin untuk memperoleh hasil terbaik. |
| `image_url` | `image` | string (image URL) | yes |  |  | Gambar dasar untuk pemrosesan. |
| `mask_url` | `mask` | string (image URL) \| null | no |  |  | URL yang mengarah ke mask, disediakan untuk kompatibilitas pemrosesan LCM umum. |
| `strength` |  | number | no | `0.8` | 0 – 1 | Pengaturan kekuatan gambar. |
| `negative_prompt` |  | string | no | `` |  | Negative prompt yang menentukan detail gambar yang tidak diinginkan. Prompt ini dapat mengecualikan warna, objek, pemandangan, atau fitur dan kualitas yang lebih halus, seperti kumis, buram, atau resolusi rendah. |
| `seed` |  | integer \| null | no |  |  | Seed untuk mereproduksi gambar dalam Stable Diffusion. Gambar dapat direproduksi secara persis pada setiap proses dengan mempertahankan versi model, prompt, dan seed. |
| `guidance_scale` |  | number | no | `1` | 0 – 16 | Kekuatan kepatuhan terhadap prompt untuk pemilihan gambar, dinyatakan sebagai CFG (Classifier Free Guidance). |
| `num_inference_steps` |  | integer | no | `4` | 1 – 12 | Jumlah langkah inferensi pembuatan gambar, dengan kualitas gambar yang lebih baik pada jumlah lebih besar tetapi waktu pembuatan lebih lama. |
| `num_images` | `num_outputs` | integer | no | `1` | 1 – 8 | Ukuran daftar gambar yang dikembalikan, dibuat menggunakan prompt dan negative prompt bersama, tetapi seed yang berbeda untuk setiap gambar. |
| `enable_safety_checks` |  | boolean | no | `true` |  | Toggle pemeriksaan keamanan output yang hanya dapat dinonaktifkan oleh akun berotorisasi; semua permintaan tanpa otorisasi tetap menjalani pemeriksaan. Saat true, gambar hasil diperiksa untuk konten yang mungkin tidak aman dan diganti dengan gambar hitam jika terdeteksi. |
| `request_id` |  | string | no | `` |  | Pengenal permintaan untuk menghubungkan respons dengan permintaan yang menghasilkannya. |
| `enable_safety_checker` |  | boolean | no | `true` |  | Penyaringan dapat dilonggarkan dengan menetapkan false, jika pemanggil berwenang. |

File parameters (`image`, `mask`) take a public `https://` URL, a `data:` URI up to 10 MB, or the `file_url` of an upload from `POST /files`.

## Example input

Required parameters only:

```json
{
  "prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
  "image": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
}
```

A fuller example:

```json
{
  "prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
  "image_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/lcm-sd15-i2i?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",
    "image_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/lcm-sd15-i2i?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",
    "image_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 = {
    "prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
    "image_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/lcm-sd15-i2i", 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": "lcm-sd15-i2i",
      "input": {
        "prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
        "image_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": "lcm-sd15-i2i",
  "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": 7,
    "usd": "0.007",
    "charged": 7,
    "refunded": 0
  },
  "input": {
    "prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
    "image_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
  },
  "output": {
    "images": [
      {
        "url": "https://content.doitong.com/dev-api/2026/10/20/req_8k2m4q7x1z9c3v5b6n0p2r4t/0-output.jpeg",
        "width": 1024,
        "height": 768,
        "content_type": "image/jpeg"
      }
    ],
    "timings": {},
    "seed": 42,
    "num_inference_steps": 4,
    "request_id": "",
    "nsfw_content_detected": [
      false
    ]
  },
  "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, width, height, content_type} | Informasi file untuk gambar yang dihasilkan. |
| `timings` | object |  |
| `seed` | integer | Seed pembuatan gambar, termasuk nilai yang dipilih secara acak jika input tidak menyertakan seed; jika tidak, nilai yang diberikan akan diulang. |
| `num_inference_steps` | integer | Jumlah langkah inference yang ditetapkan untuk pembuatan gambar, diambil dari input jika diberikan, dan jika tidak dari bawaan. |
| `request_id` | string | Pengenal permintaan untuk menghubungkan respons dengan permintaan yang menghasilkannya. |
| `nsfw_content_detected` | array of boolean | Hasil keamanan per gambar sebagai daftar boolean: setiap entri menunjukkan konten yang mungkin tidak aman, atau false jika pemeriksaan keamanan dinonaktifkan. |

## Related models

- [FLUX.1 Kontext \[pro\]](https://doitong.com/developers/models/flux-pro/kontext.md) (`flux-pro/kontext`): $0.04 / image
- [GPT Image 2.5 Edit](https://doitong.com/developers/models/openai/gpt-image-2.5/flare/edit.md) (`openai/gpt-image-2.5/flare/edit`): from $0.12 / image
- [Nano Banana 2 Edit](https://doitong.com/developers/models/nano-banana-2/edit.md) (`nano-banana-2/edit`): from $0.06 / image
- [Nano Banana Pro Edit](https://doitong.com/developers/models/nano-banana-pro/edit.md) (`nano-banana-pro/edit`): from $0.15 / image
- [Qwen Image 3 Edit](https://doitong.com/developers/models/alibaba/qwen-image-3/edit.md) (`alibaba/qwen-image-3/edit`): from $0.04 / image
- [Seedream 5.0 Pro Edit](https://doitong.com/developers/models/bytedance/seedream/v5/pro/edit.md) (`bytedance/seedream/v5/pro/edit`): from $0.0675 / run of output image
- [Bernini-R Edit Image](https://doitong.com/developers/models/bernini-r/edit-image.md) (`bernini-r/edit-image`): $0.03 / megapixel of output image
- [Boogu Image · Edit](https://doitong.com/developers/models/boogu-image/edit.md) (`boogu-image/edit`): $0.08 / image

## Links

- HTML page: https://doitong.com/developers/models/lcm-sd15-i2i
- 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=lcm-sd15-i2i
- Errors: https://doitong.com/developers/docs/errors
- Model details as JSON: https://api.doitong.com/v1/models/lcm-sd15-i2i