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Model Context Protocol (MCP) Server

by infinyte
direct-test.js1.92 kB
require('dotenv').config(); const { OpenAI } = require('openai'); const fs = require('fs'); const path = require('path'); const axios = require('axios'); // Check if OpenAI API key is available console.log('OpenAI API Key available:', Boolean(process.env.OPENAI_API_KEY)); // Initialize OpenAI client const openai = new OpenAI({ apiKey: process.env.OPENAI_API_KEY, }); async function generateImage() { try { console.log('Generating image with DALL-E...'); console.log('Using API key:', process.env.OPENAI_API_KEY ? `${process.env.OPENAI_API_KEY.substring(0, 10)}...` : 'None'); // Try with DALL-E 2 which might have different requirements const response = await openai.images.generate({ model: 'dall-e-2', prompt: 'A cute golden retriever puppy playing in a park on a sunny day', n: 1, size: '1024x1024' }); console.log('Image generated successfully'); console.log('Image URL:', response.data[0].url); // Download the image const imageUrl = response.data[0].url; const imageResponse = await axios({ url: imageUrl, method: 'GET', responseType: 'arraybuffer' }); // Save the image const imageDir = path.join(__dirname, 'public/images'); if (!fs.existsSync(imageDir)) { fs.mkdirSync(imageDir, { recursive: true }); } const timestamp = Date.now(); const fileName = `direct_test_${timestamp}.png`; const filePath = path.join(imageDir, fileName); fs.writeFileSync(filePath, Buffer.from(imageResponse.data)); console.log('Image saved to:', filePath); return { success: true, image_url: `/images/${fileName}`, file_path: filePath }; } catch (error) { console.error('Error generating image:', error.message); return { success: false, error: error.message }; } } // Run the test generateImage();

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