# Optimized Latent Consistency (SDv1.5) API

> Ātra attēla pārveide, izmantojot Stable Diffusion 1.5 un latento konsekvenci, ar stipruma vadību

Pārveido bāzes attēla stilu vai saturu no teksta uzvednes, izmantojot latento konsekvences pieeju, kurai nepieciešams tikai nedaudz soļu. `num_inference_steps` noklusējuma vērtība ir 4, maksimālā — 12. `strength` (no 0 līdz 1) nosaka, cik ļoti rezultāts atšķiras no ievades, un vienā izsaukumā var atgriezt līdz 8 attēliem. Tiek pieņemti arī neobligātie `mask_url`, `negative_prompt` un `seed`.

- 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/lv/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 |  |  | Aprakstiet ģenerējamo attēlu ar pēc iespējas lielāku detalizāciju, lai iegūtu labākos rezultātus. |
| `image_url` | `image` | string (image URL) | yes |  |  | Pamata attēls apstrādei. |
| `mask_url` | `mask` | string (image URL) \| null | no |  |  | URL, kas norāda uz masku un tiek nodrošināts vispārīgas LCM apstrādes saderībai. |
| `strength` |  | number | no | `0.8` | 0 – 1 | Attēla stipruma iestatījums. |
| `negative_prompt` |  | string | no | `` |  | Negatīva uzvedne ar nevēlamām attēla detaļām. Tā var izslēgt krāsas, objektus, ainavu vai smalkākas detaļas un īpašības, piemēram, ūsas, izplūdumu vai zemu izšķirtspēju. |
| `seed` |  | integer \| null | no |  |  | Sākumvērtība attēlu atkārtošanai Stable Diffusion. Attēlu var atkārtot pilnīgi identiski katrā palaišanas reizē, nemainot modeļa versiju, uzvedni un sākumvērtību. |
| `guidance_scale` |  | number | no | `1` | 0 – 16 | Uzvednes ievērošanas stiprums attēlu atlasē, izteikts kā CFG (Classifier Free Guidance). |
| `num_inference_steps` |  | integer | no | `4` | 1 – 12 | Attēla ģenerēšanas secināšanas soļu skaits; lielāks skaits uzlabo attēla kvalitāti, bet pagarina ģenerēšanas laiku. |
| `num_images` | `num_outputs` | integer | no | `1` | 1 – 8 | Atgriežamā attēlu saraksta izmērs; attēli tiek ģenerēti, izmantojot kopīgu uzvedni un negatīvu uzvedni, bet katram attēlam — atšķirīgu sēklu. |
| `enable_safety_checks` |  | boolean | no | `true` |  | Izvades drošības pārbaudes pārslēgs, ko drīkst atspējot tikai autorizēti konti; visi neautorizētie pieprasījumi tiek pārbaudīti neatkarīgi no iestatījuma. Ja true, iegūtais attēls tiek pārbaudīts attiecībā uz potenciāli nedrošu saturu un, ja tas tiek atrasts, aizstāts ar melnu attēlu. |
| `request_id` |  | string | no | `` |  | Pieprasījuma identifikators atbildes sasaistīšanai ar pieprasījumu, kas to izveidoja. |
| `enable_safety_checker` |  | boolean | no | `true` |  | Pārbaudi var atslābināt, iestatot false, ja izsaucējam ir atļauja. |

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} | Ģenerēto attēlu failu informācija. |
| `timings` | object |  |
| `seed` | integer | Attēla ģenerēšanas sēkla, tostarp nejauši izvēlētā vērtība, ja ievadē sēkla nebija norādīta; pretējā gadījumā atkārto norādīto vērtību. |
| `num_inference_steps` | integer | Atrisinātais secināšanas soļu skaits attēla ģenerēšanai; ja ievade ir norādīta, tas tiek ņemts no tās, pretējā gadījumā — no noklusējuma. |
| `request_id` | string | Pieprasījuma identifikators atbildes sasaistīšanai ar pieprasījumu, kas to izveidoja. |
| `nsfw_content_detected` | array of boolean | Drošības rezultāti katram attēlam kā Būla vērtību saraksts: katrs ieraksts norāda uz potenciāli nedrošu saturu vai ir false, ja drošības pārbaude ir atspējota. |

## 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