test-local.js

// Simple test script to verify basic functionality without full dependencies
const express = require('express');
const multer = require('multer');
const cors = require('cors');

const app = express();
const PORT = process.env.PORT || 7860;

// Middleware
app.use(cors());
app.use(express.json({ limit: '50mb' }));
app.use(express.urlencoded({ extended: true, limit: '50mb' }));
app.use(express.static('public'));

// Configure multer for file uploads
const upload = multer({
  storage: multer.memoryStorage(),
  limits: {
    fileSize: 10 * 1024 * 1024, // 10MB limit
  },
  fileFilter: (req, file, cb) => {
    if (file.mimetype.startsWith('image/')) {
      cb(null, true);
    } else {
      cb(new Error('Only image files are allowed'), false);
    }
  }
});

// Health check endpoint
app.get('/', (req, res) => {
  res.json({
    status: 'ok',
    message: 'AI Image Upscaler API (Test Mode)',
    version: '1.0.0',
    note: 'This is a test version. Canvas and TensorFlow.js dependencies are required for full functionality.',
    endpoints: {
      upscale: 'POST /upscale',
      health: 'GET /'
    }
  });
});

// Test upscale endpoint
app.post('/upscale', upload.single('image'), async (req, res) => {
  try {
    if (!req.file) {
      return res.status(400).json({ error: 'No image file provided' });
    }

    const { scale = 2, modelType = 'esrgan-slim', patchSize = 128, padding = 8 } = req.body;
    
    console.log(`Test upscale request: ${req.file.originalname}, scale: ${scale}x, model: ${modelType}`);
    
    // Return the original image as base64 (test mode)
    const originalImageBase64 = `data:${req.file.mimetype};base64,${req.file.buffer.toString('base64')}`;
    
    // Simulate processing time
    await new Promise(resolve => setTimeout(resolve, 500));
    
    res.json({
      success: true,
      result: originalImageBase64,
      metadata: {
        scale: parseInt(scale),
        modelType: modelType,
        patchSize: parseInt(patchSize),
        padding: parseInt(padding),
        processingTime: 500,
        backend: 'test-mode',
        note: 'This is a test response. Original image returned without upscaling.'
      }
    });

  } catch (error) {
    console.error('Test upscaling error:', error);
    res.status(500).json({
      error: 'Failed to process image',
      message: error.message
    });
  }
});

// Error handling middleware
app.use((error, req, res, next) => {
  if (error instanceof multer.MulterError) {
    if (error.code === 'LIMIT_FILE_SIZE') {
      return res.status(400).json({ error: 'File too large. Maximum size is 10MB' });
    }
  }
  
  console.error('Unhandled error:', error);
  res.status(500).json({ error: 'Internal server error' });
});

// Start server
app.listen(PORT, '0.0.0.0', () => {
  console.log(`🧪 Test Upscaler API server running on port ${PORT}`);
  console.log(`📝 Note: This is a test version without AI processing`);
  console.log(`🔗 Health check: http://localhost:${PORT}/`);
  console.log(`🌐 Web interface: http://localhost:${PORT}/index.html`);
});

// Handle graceful shutdown
process.on('SIGTERM', () => {
  console.log('Received SIGTERM, shutting down gracefully...');
  process.exit(0);
});