🧠 Cortex™ Context Management

// Initialize Cortex with Redis connection
import { Cortex } from '@microsaasfactory/cortex';

// Setup Cortex with Redis connection
const cortex = new Cortex({
  redis: {
    host: process.env.REDIS_HOST,
    port: process.env.REDIS_PORT,
    password: process.env.REDIS_PASSWORD
  },
  memoryConfig: {
    ttl: 86400 * 30, // 30 days
    compressionLevel: 'high',
    prioritization: 'recency_and_relevance'
  }
});

// API route handler for chat
export async function POST(req) {
  const { userId, message } = await req.json();
  
  // Store the new message
  await cortex.remember({
    userId,
    memoryType: 'message',
    data: {
      role: 'user',
      content: message,
      timestamp: Date.now()
    }
  });
  
  // Retrieve relevant context
  const context = await cortex.recall({
    userId,
    query: message,
    maxTokens: 1000,
    recencyWeight: 0.7
  });
  
  // Generate AI response with optimized context
  const aiResponse = await openai.chat.completions.create({
    model: "gpt-4o",
    messages: [
      { role: "system", content: "You are a helpful assistant." },
      ...context.memories.map(m => ({
        role: m.role,
        content: m.content
      })),
      { role: "user", content: message }
    ]
  });
  
  // Store the AI response
  await cortex.remember({
    userId,
    memoryType: 'message',
    data: {
      role: 'assistant',
      content: aiResponse.choices[0].message.content,
      timestamp: Date.now()
    }
  });
  
  return Response.json({
    message: aiResponse.choices[0].message.content,
    tokensSaved: context.tokensSaved
  });
}