# Chrono Edit Lora API

> 각 편집 요청에 최대 3개의 추가 LoRA를 병합할 수 있는 Chrono Edit 변형

기본 Chrono Edit와 동일한 제어 기능으로 프롬프트 기반 이미지 편집을 수행합니다. 시간적 추론, 프롬프트 확장, 터보 모드, 480p 또는 720p 해상도, jpeg, png 또는 webp 출력을 지원합니다. 추가된 `loras` 배열은 요청에 최대 3개의 추가 LoRA를 병합하여 사용자 지정 편집 스타일을 제공합니다.

- Model id: `chrono-edit-lora`
- Made by: NVIDIA
- Category: Image Editing
- Output: image
- Price: from $0.02 / image (cheapest run $0.02 (20 API credits))
- Run: `POST https://api.doitong.com/v1/run/chrono-edit-lora`
- Quote: `POST https://api.doitong.com/v1/quote/chrono-edit-lora`
- Docs page: https://doitong.com/ko/developers/models/chrono-edit-lora

## Pricing

Price: **from $0.02 / image** (the lowest tier; the quote prices your exact input). Billed per generated image.

Price rules (the first rule that matches the input wins; a parameter you leave out counts as its default):

- When `resolution` = 720p: $0.03 (30 API credits) / image

The full example input below costs $0.02 = 20 API credits (1 image × 20 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/chrono-edit-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 |
|---|---|---|---|---|---|---|
| `image_url` | `image` | string (image URL) | yes |  |  | 편집에 제공되는 이미지입니다. |
| `prompt` |  | string | yes |  |  | 이미지 편집 내용을 설명하는 프롬프트입니다. |
| `num_inference_steps` |  | integer | no | `8` | 2 – 50 | 실행할 추론 단계 수입니다. |
| `guidance_scale` |  | number | no | `1` | 0 – 10 | 추론 중 적용되는 가이던스 스케일입니다. |
| `enable_prompt_expansion` |  | boolean | no | `true` |  | 프롬프트 확장 활성화 여부를 제어합니다. |
| `enable_temporal_reasoning` |  | boolean | no | `false` |  | 시간적 추론 활성화 여부를 제어합니다. |
| `num_temporal_reasoning_steps` |  | integer | no | `8` | 2 – 12 | 시간적 추론에 사용되는 단계 수입니다. |
| `resolution` |  | enum (string) | no | `480p` | `480p`, `720p` | 결과 이미지의 해상도입니다. |
| `enable_safety_checker` |  | boolean | no | `true` |  | 안전 검사를 제어하는 스위치입니다. 끄기 설정은 승인된 계정에서만 적용됩니다. 해당 승인이 없는 모든 요청은 안전 검사를 거칩니다. |
| `seed` |  | integer \| null | no |  |  | 추론 중 사용되는 시드입니다. |
| `output_format` |  | enum (string) | no | `jpeg` | `jpeg`, `png`, `webp` | 결과 이미지의 파일 형식입니다. |
| `turbo_mode` |  | boolean | no | `true` |  | 추론 속도를 높이는 Turbo 모드 전환입니다. |
| `loras` |  | array of object {path, scale} | no | `[]` |  | 이 요청에 병합할 선택적 추가 LoRA로, 최대 3개까지 지정할 수 있습니다. |
| `loras[].path` |  | string | yes |  |  | Safetensors 형식의 LoRA 가중치 위치로, URL 또는 경로로 지정합니다. |
| `loras[].scale` |  | number | no | `1` | 0 – 4 | LoRA 강도를 설정하는 스케일링 배수입니다. |

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

A fuller example:

```json
{
  "image_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg",
  "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/chrono-edit-lora?wait=20" \
  -H "Authorization: Bearer $DOITONG_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "image_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg",
    "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/chrono-edit-lora?wait=20", {
  method: "POST",
  headers,
  body: JSON.stringify({
    "image_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg",
    "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 = {
    "image_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg",
    "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/chrono-edit-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": "chrono-edit-lora",
      "input": {
        "image_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg",
        "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": "chrono-edit-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": 20,
    "usd": "0.02",
    "charged": 20,
    "refunded": 0
  },
  "input": {
    "image_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg",
    "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
      }
    ],
    "prompt": "The user wants to add a surfer to the wave in the illustration while preserving the original ukiyo-e woodblock art style. The surfer should be depicted mid-action, crouched low on a modern-style surfboard, carving through the crest of the wave with one arm extended for balance and the other gripping the board. Their wavy hair and athletic physique should match the dynamic motion. The background must remain unchanged, including the iconic Mount Fuji and the traditional Japanese text, to maintain the artwork's historical aesthetic and composition.",
    "seed": 42
  },
  "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} | 편집 결과 이미지입니다. |
| `prompt` | string | 추론 프로세스에 제공되는 프롬프트입니다. |
| `seed` | integer | 추론 중 사용되는 시드입니다. |

## 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
- [Chrono Edit](https://doitong.com/developers/models/chrono-edit.md) (`chrono-edit`): from $0.01 / image
- [Chrono Edit Lora Gallery · Paintbrush](https://doitong.com/developers/models/chrono-edit-lora-gallery/paintbrush.md) (`chrono-edit-lora-gallery/paintbrush`): from $0.02 / image

## Links

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