Nano Banana Pro Serverless API

 1import requests
 2import json
 3
 4url = "https://api.segmind.com/v1/nano-banana-pro"
 5headers = {
 6    "x-api-key": "YOUR_API_KEY",
 7    "Content-Type": "application/json"
 8}
 9
10data = {
11    "prompt": "Create a multi-panel GTA-style comic page featuring one woman and one man as office coworkers working on a new product launch. Use bold outlines, dramatic GTA loading-screen shading, expressive faces, modern tech office backgrounds.\n\nPanel 1 — Narration:\nThe woman enters the office early, holding a laptop. She looks stressed but determined.\nText: ‘Launch day. Weeks of work… all coming down to this.’\n\nPanel 2 — Dialogue:\nMan appears behind her with a calm, confident smile.\nMan: ‘You’re here early. Ready for the big ship?’\nWoman: ‘Trying to be.’\n\nPanel 3 — Action:\nBoth sit at a desk with screens showing graphs, bugs, and a countdown timer.\nText: ‘One critical bug left… time running out.’\n\nPanel 4 — Dialogue:\nClose-up of the man pointing at the screen.\nMan: ‘Wait—I see it. We can fix this.’\nWoman: ‘Let’s do it.’\n\nPanel 5 — Action:\nBoth typing fast, dramatic GTA-style lighting, code streaming across screens.\nText: ‘Two minds. One mission.’\n\nPanel 6 — Victory:\nThe laptop shows PRODUCT SHIPPED — SUCCESS. Both cheer and laugh in relief.\nWoman: ‘We did it!’\nMan: ‘Told you we’d make it.’\n\nPanel 7 — Narration:\nFinal shot: team walking out of the office at night, city lights behind them.\nText: ‘In tech, wins aren’t solo. They’re shared.’\n\nArt style: GTA loading-screen style, bold color blocks, high contrast shadows, confident comic composition, cinematic frames.",
12    "image_urls": [
13        "https://segmind-inference-inputs.s3.amazonaws.com/ad93498e-3370-432b-8dd7-bc3f4aa1b39a-black-man-image.jpeg",
14        "https://segmind-inference-inputs.s3.amazonaws.com/8bdc63b0-79ed-4369-a4af-e7284f5bde33-image (86).png"
15    ],
16    "aspect_ratio": "9:16",
17    "output_format": "jpg",
18    "output_resolution": "4K",
19    "response_modalities": "TEXT_AND_IMAGE"
20}
21
22response = requests.post(url, headers=headers, json=data)
23
24if response.status_code == 200:
25    result = response.json()
26    print(json.dumps(result, indent=2))
27else:
28    print(f"Error: {response.status_code}")
29    print(response.text)