# Chrono Edit Lora API

> Chrono-Edit-Variante, die bis zu 3 zusätzliche LoRAs in jede Bearbeitungsanfrage integriert

Bildbearbeitung anhand eines Prompts mit denselben Optionen wie Chrono Edit: temporales Reasoning, Prompt-Erweiterung, Turbo-Modus, 480p- oder 720p-Auflösung sowie jpeg-, png- oder webp-Ausgabe. Das zusätzliche `loras`-Array integriert bis zu 3 weitere LoRAs in die Anfrage und ermöglicht benutzerdefinierte Bearbeitungsstile.

- 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/de/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 |  |  | Zur Bearbeitung bereitgestelltes Bild. |
| `prompt` |  | string | yes |  |  | Prompt, der die Bildbearbeitungen beschreibt. |
| `num_inference_steps` |  | integer | no | `8` | 2 – 50 | Anzahl der auszuführenden Inferenzschritte. |
| `guidance_scale` |  | number | no | `1` | 0 – 10 | Während der Inferenz angewendete Führungsskala. |
| `enable_prompt_expansion` |  | boolean | no | `true` |  | Steuert, ob die Prompt-Erweiterung aktiviert ist. |
| `enable_temporal_reasoning` |  | boolean | no | `false` |  | Steuert, ob zeitliches Schlussfolgern aktiviert ist. |
| `num_temporal_reasoning_steps` |  | integer | no | `8` | 2 – 12 | Anzahl der für das zeitliche Schlussfolgern verwendeten Schritte. |
| `resolution` |  | enum (string) | no | `480p` | `480p`, `720p` | Auflösung des resultierenden Bildes. |
| `enable_safety_checker` |  | boolean | no | `true` |  | Schalter für die Sicherheitsprüfung, dessen Deaktivierung nur für autorisierte Konten berücksichtigt wird. Alle Anfragen ohne diese Autorisierung werden Sicherheitsprüfungen unterzogen. |
| `seed` |  | integer \| null | no |  |  | Während der Inferenz verwendeter Seed. |
| `output_format` |  | enum (string) | no | `jpeg` | `jpeg`, `png`, `webp` | Dateiformat des resultierenden Bildes. |
| `turbo_mode` |  | boolean | no | `true` |  | Turbo-Modus zum Beschleunigen der Inferenz. |
| `loras` |  | array of object {path, scale} | no | `[]` |  | Optionale zusätzliche LoRAs zum Zusammenführen mit dieser Anfrage, bis zu 3. |
| `loras[].path` |  | string | yes |  |  | Speicherort der LoRA-Gewichte im Safetensors-Format, angegeben als URL oder Pfad. |
| `loras[].scale` |  | number | no | `1` | 0 – 4 | Skalierungsmultiplikator, der die LoRA-Stärke festlegt. |

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} | Aus der Bearbeitung resultierendes Bild. |
| `prompt` | string | Dem Inferenzprozess übergebener Prompt. |
| `seed` | integer | Während der Inferenz verwendeter Seed. |

## 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