# Optimized Latent Consistency (SDv1.5) API

> Transformasi imej-ke-imej dengan beberapa langkah pada Stable Diffusion 1.5 menggunakan konsistensi laten, dengan kawalan kekuatan

Menggayakan semula atau mengubah imej asas daripada prompt teks menggunakan pendekatan konsistensi laten yang hanya memerlukan beberapa langkah. `num_inference_steps` lalai kepada 4 dan boleh mencapai 12. `strength` (0 hingga 1) menetapkan sejauh mana hasil menyimpang daripada input, dan sehingga 8 imej boleh dikembalikan bagi setiap panggilan. `mask_url`, `negative_prompt` dan `seed` adalah pilihan.

- 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.ru/v1/run/lcm-sd15-i2i`
- Quote: `POST https://api.doitong.ru/v1/quote/lcm-sd15-i2i`
- Docs page: https://doitong.com/ms/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.ru/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 |  |  | Terangkan imej yang anda mahu dijana dengan sedetail mungkin untuk mendapatkan hasil terbaik. |
| `image_url` | `image` | string (image URL) | yes |  |  | Imej asas untuk pemprosesan. |
| `mask_url` | `mask` | string (image URL) \| null | no |  |  | URL yang menunjuk kepada topeng, disediakan untuk keserasian pemprosesan LCM umum. |
| `strength` |  | number | no | `0.8` | 0 – 1 | Tetapan kekuatan imej. |
| `negative_prompt` |  | string | no | `` |  | Prompt negatif yang menyatakan butiran imej tidak diingini. Ia boleh mengecualikan warna, objek, pemandangan atau ciri dan kualiti halus seperti misai, kabur atau resolusi rendah. |
| `seed` |  | integer \| null | no |  |  | Seed untuk menghasilkan semula imej dalam Stable Diffusion. Imej boleh dihasilkan semula dengan tepat pada setiap larian dengan mengekalkan versi model, prompt dan seed tanpa perubahan. |
| `guidance_scale` |  | number | no | `1` | 0 – 16 | Kekuatan pematuhan prompt untuk pemilihan imej, dinyatakan sebagai CFG (Classifier Free Guidance). |
| `num_inference_steps` |  | integer | no | `4` | 1 – 12 | Bilangan langkah inferens penjanaan imej, dengan kualiti imej lebih baik pada bilangan lebih tinggi tetapi masa penjanaan lebih lama. |
| `num_images` | `num_outputs` | integer | no | `1` | 1 – 8 | Saiz senarai imej yang dikembalikan, dijana menggunakan prompt dan prompt negatif yang sama tetapi seed berbeza bagi setiap imej. |
| `enable_safety_checks` |  | boolean | no | `true` |  | Suis pemeriksaan keselamatan output yang hanya boleh dilumpuhkan oleh akaun yang diberi kuasa; semua permintaan tanpa kebenaran tetap diperiksa. Apabila true, ia menyaring imej yang terhasil untuk kandungan yang mungkin tidak selamat dan menggantikannya dengan imej hitam jika dikesan. |
| `request_id` |  | string | no | `` |  | Pengecam permintaan untuk mengaitkan respons dengan permintaan yang menghasilkannya. |
| `enable_safety_checker` |  | boolean | no | `true` |  | Pemeriksaan boleh dilonggarkan dengan menetapkannya kepada false, jika pemanggil dibenarkan. |

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.ru/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.ru/v1/requests/REQUEST_ID?wait=20" \
  -H "Authorization: Bearer $DOITONG_API_KEY"
```

### JavaScript

```javascript
const API = "https://api.doitong.ru/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.ru/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.ru/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.ru/v1/requests/req_8k2m4q7x1z9c3v5b6n0p2r4t",
    "cancel": "https://api.doitong.ru/v1/requests/req_8k2m4q7x1z9c3v5b6n0p2r4t/cancel"
  }
}
```

### Output fields (`output`)

| Field | Type | Description |
|---|---|---|
| `images` | array of object {url, width, height, content_type} | Maklumat fail untuk imej yang dijana. |
| `timings` | object |  |
| `seed` | integer | Seed penjanaan imej, termasuk nilai yang dipilih secara rawak jika input tidak membekalkan seed; jika tidak, nilai yang dibekalkan diulang. |
| `num_inference_steps` | integer | Bilangan langkah inferens yang diselesaikan untuk penjanaan imej, diambil daripada input jika dibekalkan dan sebaliknya daripada lalai. |
| `request_id` | string | Pengecam permintaan untuk mengaitkan respons dengan permintaan yang menghasilkannya. |
| `nsfw_content_detected` | array of boolean | Hasil keselamatan bagi setiap imej sebagai senarai boolean: setiap entri menunjukkan kandungan yang mungkin tidak selamat, atau false apabila pemeriksaan keselamatan dilumpuhkan. |

## 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.ru/v1/models/lcm-sd15-i2i