# google/nano-banana-pro/text-to-image

> Boasting sharper 2K imagery, intelligent 4K scaling, improved text rendering, and enhanced character consistency, Google DeepMind’s Nano Banana Pro represents a significant advancement in visual quality for creative and API-driven workflows.

## Overview

- **Endpoint**: `https://api.shortapi.ai/api/v1/job/create`
- **Model ID**: `google/nano-banana-pro/text-to-image`
- **Category**: text-to-image
- **Kind**: inference

## Pricing

The cost for 1K and 2K resolution images is $0.08 per request.The cost for 4K resolution images is $0.12 per request.

For more details, please check our pricing page.

## API Information

This model can be used via our HTTP API or more conveniently via our client libraries.
See the input and output schema below, as well as the usage examples.

### Input Schema

The API accepts the following input parameters:

- **`prompt`** (`string`, _required_):
  Text prompt
  - Examples: "An action shot of a black lab swimming..."

- **`num_images`** (`int`, _optional_):
  The number of images to generate
  - Default: `1`
  - Options: "1"

- **`aspect_ratio`** (`string`, _required_):
  The aspect ratio of the generated image
  - Options: "9:16", "2:3", "3:4", "4:5", "1:1", "5:4", "4:3", "3:2", "16:9", "21:9"

- **`resolution`** (`string`, _optional_):
  Output image resolution
  - Default: `1K`
  - Options: "1K", "2K", "4K"

### Output Schema

The API returns a JSON response with a `job_id` for tracking the request status.

**Create Job Response:**
```json
{
  "code": 0,
  "data": {
    "amount": "0.02",
    "job_id": "<JOB_ID>"
  }
}
```

**Query Job Result (when status is 2, meaning succeeded):**
```json
{
  "code": 0,
  "data": {
    "status": 2,
    "result": {
      "images": [{ "url": "https://..." }]
    }
  }
}
```

## Use Example

To use this model, make an HTTP POST request to the API endpoint, then poll for results using the returned `job_id`.

### Bash (cURL)
```bash
# Step 1: Create a job
response=$(curl --request POST \
  --url https://api.shortapi.ai/api/v1/job/create \
  --header "Authorization: Bearer $SHORTAPI_KEY" \
  --header "Content-Type: application/json" \
  --data '{
  "model": "google/nano-banana-pro/text-to-image",
  "args": {
    "prompt": "A vintage patent document for an early motion picture camera (chronophotographic apparatus), styled after late 1800s United States Patent Office filings. The page features precise technical drawings with numbered callouts (Fig. 1, Fig. 2, Fig. 3) showing the front housing, side profile with hand-crank mechanism, and an exploded view of the film transport assembly. Handwritten annotations in fountain-pen ink describe the intermittent shutter, sprocket wheels, and light-tight enclosure. The paper is aged ivory with foxing stains and soft fold creases. An official embossed seal and a deep red wax stamp appear in the lower right corner. A hand-signed inventor’s name and the date 1892 appear at the bottom. The entire image feels like a recovered archival document—authoritative, historic, and slightly mysterious.",
    "aspect_ratio": "16:9"
  },
  "callback_url": "CALLBACK_URL"
}')
JOB_ID=$(echo "$response" | grep -o '"job_id": *"[^"]*"' | sed 's/"job_id": *//; s/"//g')

# Step 2: Poll for results
curl --request GET \
  --url "https://api.shortapi.ai/api/v1/job/query?id=$JOB_ID" \
  --header "Authorization: Bearer $SHORTAPI_KEY"
```

### JavaScript (Fetch API)
```javascript
// Step 1: Create a job
const response = await fetch(`https://api.shortapi.ai/api/v1/job/create`, {
  method: "POST",
  headers: {
    "Authorization": `Bearer ${SHORTAPI_KEY}`,
    "Content-Type": "application/json"
  },
  body: JSON.stringify({
    "model": "google/nano-banana-pro/text-to-image",
    "args": {
      "prompt": "A vintage patent document for an early motion picture camera (chronophotographic apparatus), styled after late 1800s United States Patent Office filings. The page features precise technical drawings with numbered callouts (Fig. 1, Fig. 2, Fig. 3) showing the front housing, side profile with hand-crank mechanism, and an exploded view of the film transport assembly. Handwritten annotations in fountain-pen ink describe the intermittent shutter, sprocket wheels, and light-tight enclosure. The paper is aged ivory with foxing stains and soft fold creases. An official embossed seal and a deep red wax stamp appear in the lower right corner. A hand-signed inventor’s name and the date 1892 appear at the bottom. The entire image feels like a recovered archival document—authoritative, historic, and slightly mysterious.",
      "aspect_ratio": "16:9"
    },
    "callback_url": "CALLBACK_URL"
})
});
const data = await response.json();
const JOB_ID = data.job_id;

// Step 2: Poll for results
const result = await fetch(`https://api.shortapi.ai/api/v1/job/query?id=${JOB_ID}`, {
  method: "GET",
  headers: {
    "Authorization": `Bearer ${SHORTAPI_KEY}`
  }
});
const resultData = await result.json();
console.log(resultData);
```

### Python (Requests)
```python
import requests

# Step 1: Create a job
url = "https://api.shortapi.ai/api/v1/job/create"
payload = {
  "model": "google/nano-banana-pro/text-to-image",
  "args": {
    "prompt": "A vintage patent document for an early motion picture camera (chronophotographic apparatus), styled after late 1800s United States Patent Office filings. The page features precise technical drawings with numbered callouts (Fig. 1, Fig. 2, Fig. 3) showing the front housing, side profile with hand-crank mechanism, and an exploded view of the film transport assembly. Handwritten annotations in fountain-pen ink describe the intermittent shutter, sprocket wheels, and light-tight enclosure. The paper is aged ivory with foxing stains and soft fold creases. An official embossed seal and a deep red wax stamp appear in the lower right corner. A hand-signed inventor’s name and the date 1892 appear at the bottom. The entire image feels like a recovered archival document—authoritative, historic, and slightly mysterious.",
    "aspect_ratio": "16:9"
  },
  "callback_url": "CALLBACK_URL"
}
headers = {
    "Authorization": f"Bearer {SHORTAPI_KEY}",
    "Content-Type": "application/json"
}

response = requests.post(url, headers=headers, json=payload)
data = response.json()
JOB_ID = data.get("job_id")

# Step 2: Poll for results
result_url = f"https://api.shortapi.ai/api/v1/job/query?id={JOB_ID}"
result = requests.get(result_url, headers={"Authorization": f"Bearer {SHORTAPI_KEY}"})
print(result.json())
```