Generate images using Nano Banana using an OpenRouter API key.

nano-banana-open-router-generate-image.js

#!/usr/bin/env node

import fs from 'node:fs/promises';

// extract inputs
const OPENROUTER_API_KEY = process.env.OPENROUTER_API_KEY;
const IMAGE_NAME = process.env.IMAGE_NAME;
const AI_MODEL = process.env.AI_MODEL || 'google/gemini-3-pro-image-preview';
const ASPECT_RATIO = process.env.ASPECT_RATIO || '1:1';
const IMAGE_SIZE = process.env.IMAGE_SIZE || '1K';

// read prompt from text file
const inputFileName = `./${IMAGE_NAME}.txt`;
const IMAGE_PROMPT = (await fs.readFile(inputFileName)).toString();

// don't allow script to run in output file exists
const outputFileName = `./${IMAGE_NAME}.json`;
const outputFileAlreadyExists = await fileExists(outputFileName);
if (outputFileAlreadyExists) {
  console.error(`output file exists, overwrite not allowed: ${outputFileName}`);
  process.exit(-1);
}

// make the API request to nano banana
const requestBody = {
  model: AI_MODEL,
  messages: [{ role: 'user', content: IMAGE_PROMPT }],
  modalities: ['image', 'text'],
  image_config: {
    aspect_ratio: ASPECT_RATIO,
    image_size: IMAGE_SIZE,
  }
};
console.log(requestBody);
const response = await fetch(
  'https://openrouter.ai/api/v1/chat/completions', {
  method: 'POST',
  headers: {
    Authorization: `Bearer ${OPENROUTER_API_KEY}`,
    'Content-Type': 'application/json',
  },
  body: JSON.stringify(requestBody),
});

// write the raw LLM response into a JSON file
const result = await response.json();
await fs.writeFile(outputFileName, JSON.stringify(result, undefined, 2));
console.log(`wrote raw response: ${outputFileName}`);

// parse the raw LLM response and create individual image files from each one
const responseImages = result?.choices[0].message?.images;
const writeImagePromises = responseImages.map((image, index) => {
  const imageBase64Url = image.image_url.url;
  const { fileType, fileBuffer } = parseImageBase64Url(imageBase64Url);
  const outputImageFileName = `${IMAGE_NAME}--${index + 1}.${fileType}`;
  console.log(`writing image file: ${outputImageFileName}`);
  return fs.writeFile(outputImageFileName, fileBuffer);
});
await Promise.all(writeImagePromises); // parallel
console.log('wrote all image files');

// utility function to convert base64 URIs to image data ready to be written to disk
function parseImageBase64Url(base64Url) {
  const matches = base64Url.match(/^data:image\/(\w+);base64,(.+)$/);
  if (!matches || matches.length !== 3) {
    throw new Error('invalid base64 image URL');
  }
  const [, imageType, base64Data] = matches;
  return {
    fileType: imageType,
    fileBuffer: Buffer.from(base64Data, 'base64')
  };
}

// utility function to check if file exists
async function fileExists(filePath) {
  try {
    await fs.access(filePath, fs.constants.F_OK);
    return true;
  } catch {
    return false;
  }
}