Comprehensive comparison for AI technology in Prompt Engineering applications

import { Latitude } from '@latitude-data/sdk';
import express from 'express';

// Initialize Latitude client with API key
const latitude = new Latitude({
  apiKey: process.env.LATITUDE_API_KEY,
  projectId: process.env.LATITUDE_PROJECT_ID
});

const app = express();
app.use(express.json());

// Product recommendation endpoint using Latitude prompt chain
app.post('/api/recommendations', async (req, res) => {
  try {
    const { userId, browsing_history, budget, preferences } = req.body;

    // Validate required fields
    if (!userId || !browsing_history) {
      return res.status(400).json({ 
        error: 'Missing required fields: userId and browsing_history' 
      });
    }

    // Step 1: Analyze user preferences using a Latitude prompt
    const analysisResult = await latitude.prompts.run('user-preference-analyzer', {
      parameters: {
        browsing_history: browsing_history.join(', '),
        user_preferences: preferences || 'none specified',
        budget_range: budget || 'flexible'
      },
      // Enable streaming for real-time responses
      stream: false
    });

    // Extract analyzed preferences
    const analyzedPreferences = analysisResult.text;

    // Step 2: Generate personalized recommendations
    const recommendationResult = await latitude.prompts.run('product-recommender', {
      parameters: {
        user_analysis: analyzedPreferences,
        max_recommendations: 5,
        budget: budget || 1000
      },
      // Use conversation history for context
      conversationId: `user-${userId}-session`
    });

    // Step 3: Format and validate recommendations
    const recommendations = parseRecommendations(recommendationResult.text);

    // Log usage for analytics
    await logPromptUsage({
      userId,
      promptIds: ['user-preference-analyzer', 'product-recommender'],
      tokensUsed: analysisResult.usage.totalTokens + recommendationResult.usage.totalTokens,
      timestamp: new Date().toISOString()
    });

    return res.status(200).json({
      success: true,
      recommendations,
      metadata: {
        tokensUsed: analysisResult.usage.totalTokens + recommendationResult.usage.totalTokens,
        conversationId: `user-${userId}-session`
      }
    });

  } catch (error) {
    console.error('Recommendation error:', error);
    
    // Handle specific Latitude errors
    if (error.code === 'RATE_LIMIT_EXCEEDED') {
      return res.status(429).json({ 
        error: 'Too many requests. Please try again later.' 
      });
    }
    
    if (error.code === 'INVALID_PROMPT') {
      return res.status(400).json({ 
        error: 'Invalid prompt configuration' 
      });
    }

    return res.status(500).json({ 
      error: 'Failed to generate recommendations',
      message: process.env.NODE_ENV === 'development' ? error.message : undefined
    });
  }
});

// Helper function to parse AI-generated recommendations
function parseRecommendations(text) {
  try {
    // Attempt to parse JSON response
    const parsed = JSON.parse(text);
    return Array.isArray(parsed) ? parsed : [parsed];
  } catch {
    // Fallback: extract structured data from text
    return [{ raw_text: text }];
  }
}

// Helper function to log prompt usage
async function logPromptUsage(data) {
  // Implementation would connect to your analytics service
  console.log('Prompt usage:', data);
}

const PORT = process.env.PORT || 3000;
app.listen(PORT, () => {
  console.log(`Server running on port ${PORT}`);
});