# Nano Banana Pro Edit API

> Қарапайым тілдегі нұсқаулармен фотосуреттерді өңдейді немесе біріктіреді, беттер мен өнімдерді сақтайды, 4K-ға дейін.

Nano Banana Pro өңдеу режимі: бір немесе бірнеше кескін беріп, фонды ауыстыру, адам мен өнімді бір көрініске біріктіру, стильді өзгерту немесе маңдайшадағы мәтінді түзету сияқты өзгерісті сипаттаңыз. Өңдеулер арасында тұлғалар мен бөлшектерді тұрақты сақтайды. Кез келген кең таралған кадр пішімінде 1K, 2K немесе 4K шығысы, қосымша веб-негіздеу, әр сұрауда төрт нәтижеге дейін.

- Model id: `nano-banana-pro/edit`
- Made by: Google
- Category: Image Editing
- Output: image
- Price: from $0.15 / image (cheapest run $0.15 (150 API credits))
- Run: `POST https://api.doitong.com/v1/run/nano-banana-pro/edit`
- Quote: `POST https://api.doitong.com/v1/quote/nano-banana-pro/edit`
- Docs page: https://doitong.com/kk/developers/models/nano-banana-pro/edit

## Pricing

Price: **from $0.15 / image** (the lowest tier; the quote prices your exact input). Billed per generated image (`num_images`, default 1).

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

- When `resolution` = 4K and `enable_web_search` = true: $0.315 (315 API credits) / image
- When `resolution` = 4K: $0.30 (300 API credits) / image
- When `enable_web_search` = true: $0.165 (165 API credits) / image

The full example input below costs $0.15 = 150 API credits (1 image × 150 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/nano-banana-pro/edit` 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 |  | 3 – 50000 characters | Кескінді өңдеуге арналған мәтіндік нұсқаулар. |
| `num_images` | `num_outputs` | integer | no | `1` | 1 – 4 | Генерацияға сұралған кескіндер саны. |
| `seed` |  | integer \| null | no |  |  | Кездейсоқ сандар генерациясын бастайтын seed мәні. |
| `aspect_ratio` |  | enum (string) \| null | no | `auto` | `auto`, `21:9`, `16:9`, `3:2`, `4:3`, `5:4`, `1:1`, `4:5`, `3:4`, `2:3`, `9:16` | Нәтиже кескінінің пропорциясы. |
| `output_format` |  | enum (string) | no | `png` | `jpeg`, `png`, `webp` | Нәтижедегі кескіннің файл пішімі. |
| `safety_tolerance` |  | enum (string) | no | `4` | `1`, `2`, `3`, `4`, `5`, `6` | Мазмұнды модерациялау төзімділігін ең жұмсақ 6 деңгейі мен ең қатаң, көп мазмұнды бұғаттайтын 1 деңгейі аралығында орнатады. |
| `image_urls` | `images` | array of image URL | yes |  |  | Өңдеу немесе кескіннен кескін жасауға арналған бастапқы кескіндерді анықтайтын URL мекенжайлары. |
| `system_prompt` |  | string | no | `` | ≤ 50000 characters | Сұрауға ортақ қосымша персона және шығыс стилі бойынша нұсқаулар. Олар Gemini-ге жүйелік нұсқау, ал OpenAI-үйлесімді провайдерлерге жүйелік хабарлама ретінде жіберіледі. Мән бос болса, бұл нұсқау үшін ештеңе жіберілмейді. |
| `resolution` |  | enum (string) | no | `1K` | `1K`, `2K`, `4K` | Шығыс кескінінің ажыратымдылығы. |
| `limit_generations` |  | boolean | no | `true` |  | Эксперименттік генерация шегі: `True` нұсқаудағы кескін саны туралы нұсқауларды қайта анықтап, әр нұсқау раундын 1 генерациямен шектейді. |
| `enable_web_search` |  | boolean | no | `false` |  | Кескін генерациясына арналған веб-іздеу ауыстырғышы; модельге интернеттен алынған өзекті ақпаратты кескінге енгізуге мүмкіндік береді. |

File parameters (`images`) 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": "Put this white sneaker on a sunlit marble pedestal in a minimalist gallery, keep the shoe exactly as it is",
  "images": [
    "https://content.doitong.com/images/showcase/v3/gen_sneaker_ad.jpg"
  ]
}
```

A fuller example:

```json
{
  "prompt": "Put this white sneaker on a sunlit marble pedestal in a minimalist gallery, keep the shoe exactly as it is",
  "images": [
    "https://content.doitong.com/images/showcase/v3/gen_sneaker_ad.jpg"
  ],
  "resolution": "1K"
}
```

## 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/nano-banana-pro/edit?wait=20" \
  -H "Authorization: Bearer $DOITONG_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "prompt": "Put this white sneaker on a sunlit marble pedestal in a minimalist gallery, keep the shoe exactly as it is",
    "images": [
      "https://content.doitong.com/images/showcase/v3/gen_sneaker_ad.jpg"
    ],
    "resolution": "1K"
  }'

# 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/nano-banana-pro/edit?wait=20", {
  method: "POST",
  headers,
  body: JSON.stringify({
    "prompt": "Put this white sneaker on a sunlit marble pedestal in a minimalist gallery, keep the shoe exactly as it is",
    "images": [
      "https://content.doitong.com/images/showcase/v3/gen_sneaker_ad.jpg"
    ],
    "resolution": "1K"
  }),
});
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": "Put this white sneaker on a sunlit marble pedestal in a minimalist gallery, keep the shoe exactly as it is",
    "images": [
        "https://content.doitong.com/images/showcase/v3/gen_sneaker_ad.jpg",
    ],
    "resolution": "1K",
}

# Run the model; wait up to 20 s for the finished result in the same call
r = requests.post(API + "/run/nano-banana-pro/edit", 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": "nano-banana-pro/edit",
      "input": {
        "prompt": "Put this white sneaker on a sunlit marble pedestal in a minimalist gallery, keep the shoe exactly as it is",
        "images": [
          "https://content.doitong.com/images/showcase/v3/gen_sneaker_ad.jpg"
        ],
        "resolution": "1K"
      },
      "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": "nano-banana-pro/edit",
  "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": 150,
    "usd": "0.15",
    "charged": 150,
    "refunded": 0
  },
  "input": {
    "prompt": "Put this white sneaker on a sunlit marble pedestal in a minimalist gallery, keep the shoe exactly as it is",
    "images": [
      "https://content.doitong.com/images/showcase/v3/gen_sneaker_ad.jpg"
    ],
    "resolution": "1K"
  },
  "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
      }
    ],
    "description": "string"
  },
  "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} | Өңдеу нәтижесінде алынған кескіндер. |
| `description` | string | Жасалған кескіндерге қоса берілетін сипаттама. |

## Related models

- [Nano Banana Pro](https://doitong.com/developers/models/nano-banana-pro.md) (`nano-banana-pro`): from $0.15 / image
- [Nano Banana 2 Edit](https://doitong.com/developers/models/nano-banana-2/edit.md) (`nano-banana-2/edit`): from $0.06 / image
- [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
- [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
- [Gemini 2.5 Flash Image · Edit](https://doitong.com/developers/models/gemini-25-flash-image/edit.md) (`gemini-25-flash-image/edit`): $0.0398 / image
- [Gemini 3 Pro Image Preview · Edit](https://doitong.com/developers/models/gemini-3-pro-image-preview/edit.md) (`gemini-3-pro-image-preview/edit`): from $0.15 / image

## Links

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