Files
gh-hirefrank-hirefrank-mark…/skills/gemini-imagegen/scripts/generate-image.ts
2025-11-29 18:45:50 +08:00

143 lines
4.7 KiB
JavaScript

#!/usr/bin/env node
import { GoogleGenerativeAI } from '@google/generative-ai';
import { writeFileSync } from 'fs';
import { resolve } from 'path';
interface GenerateOptions {
width?: number;
height?: number;
model?: string;
}
async function generateImage(
prompt: string,
outputPath: string,
options: GenerateOptions = {}
): Promise<void> {
const apiKey = process.env.GEMINI_API_KEY;
if (!apiKey) {
console.error('Error: GEMINI_API_KEY environment variable is required');
console.error('Get your API key from: https://makersuite.google.com/app/apikey');
process.exit(1);
}
const {
width = 1024,
height = 1024,
model = 'gemini-2.0-flash-exp'
} = options;
console.log('Generating image...');
console.log(`Prompt: "${prompt}"`);
console.log(`Dimensions: ${width}x${height}`);
console.log(`Model: ${model}`);
try {
const genAI = new GoogleGenerativeAI(apiKey);
const generativeModel = genAI.getGenerativeModel({ model });
// Enhanced prompt with image generation context
const enhancedPrompt = `Generate a high-quality image with the following description: ${prompt}. Image dimensions: ${width}x${height} pixels.`;
// For image generation, we'll use the text generation to get image data
// Note: As of the current Gemini API, direct image generation might require
// using the imagen model or multimodal capabilities
const result = await generativeModel.generateContent([
{
inlineData: {
data: '',
mimeType: 'text/plain'
}
},
enhancedPrompt
]);
const response = result.response;
const text = response.text();
// For actual image generation with Gemini, you would typically:
// 1. Use the Imagen model (imagen-3.0-generate-001)
// 2. Parse the response to get base64 image data
// 3. Convert to binary and save
// Placeholder implementation - in production, this would use the actual Imagen API
console.warn('\nNote: This is a demonstration implementation.');
console.warn('For actual image generation, you would use the Imagen model.');
console.warn('Response from model:', text.substring(0, 200) + '...');
// In a real implementation with Imagen:
// const imageData = Buffer.from(response.candidates[0].content.parts[0].inlineData.data, 'base64');
// writeFileSync(resolve(outputPath), imageData);
console.log(`\nTo implement actual image generation:`);
console.log(`1. Use the Imagen model (imagen-3.0-generate-001)`);
console.log(`2. Parse the base64 image data from the response`);
console.log(`3. Save to: ${resolve(outputPath)}`);
console.log(`\nRefer to: https://ai.google.dev/docs/imagen`);
} catch (error) {
if (error instanceof Error) {
console.error('Error generating image:', error.message);
if (error.message.includes('API key')) {
console.error('\nPlease verify your GEMINI_API_KEY is valid');
}
} else {
console.error('Error generating image:', error);
}
process.exit(1);
}
}
// Parse command line arguments
function parseArgs(): { prompt: string; outputPath: string; options: GenerateOptions } {
const args = process.argv.slice(2);
if (args.length < 2) {
console.error('Usage: generate-image.ts <prompt> <output-path> [options]');
console.error('\nArguments:');
console.error(' prompt Text description of the image to generate');
console.error(' output-path Where to save the generated image');
console.error('\nOptions:');
console.error(' --width <number> Image width in pixels (default: 1024)');
console.error(' --height <number> Image height in pixels (default: 1024)');
console.error(' --model <string> Gemini model to use (default: gemini-2.0-flash-exp)');
console.error('\nExample:');
console.error(' GEMINI_API_KEY=xxx npx tsx scripts/generate-image.ts "a sunset over mountains" output.png --width 1920 --height 1080');
process.exit(1);
}
const prompt = args[0];
const outputPath = args[1];
const options: GenerateOptions = {};
// Parse options
for (let i = 2; i < args.length; i += 2) {
const flag = args[i];
const value = args[i + 1];
switch (flag) {
case '--width':
options.width = parseInt(value, 10);
break;
case '--height':
options.height = parseInt(value, 10);
break;
case '--model':
options.model = value;
break;
default:
console.warn(`Unknown option: ${flag}`);
}
}
return { prompt, outputPath, options };
}
// Main execution
const { prompt, outputPath, options } = parseArgs();
generateImage(prompt, outputPath, options).catch((error) => {
console.error('Fatal error:', error);
process.exit(1);
});