Chat Memory with OpenAI Integration

mkdir chat-memory
cd chat-memory
npm init -y
npm install express dotenv node-fetch openai

PAPR_API_KEY=your_papr_api_key_here
OPENAI_API_KEY=your_openai_api_key_here

import { OpenAI } from 'openai';
import { Papr } from '@papr/sdk';
import express from 'express';
import dotenv from 'dotenv';

dotenv.config();

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

// Initialize OpenAI and Papr client
const openai = new OpenAI({
  apiKey: process.env.OPENAI_API_KEY
});

const paprClient = new Papr({
  apiKey: process.env.PAPR_API_KEY
});

// Save chat message to Papr Memory
async function saveToMemory(message, role, conversationId) {
  try {
    const response = await paprClient.memory.add({
      content: message,
      type: 'text',
      metadata: {
        role,
        conversationId,
        timestamp: new Date().toISOString()
      }
    });
    
    return response;
  } catch (error) {
    throw new Error(`Failed to save message: ${error.message}`);
  }
}

// Search conversation history
async function searchMemory(query, conversationId) {
  try {
    const searchResponse = await paprClient.memory.search({
      query: `Find our recent conversation history for conversation ${conversationId}, especially messages related to: "${query}". Include both the user's questions and the assistant's responses to provide full context.`
    });
    
    return searchResponse;
  } catch (error) {
    throw new Error(`Failed to search memory: ${error.message}`);
  }
}

// Process a chat message
app.post('/chat', async (req, res) => {
  try {
    const { message, conversationId } = req.body;
    
    if (!message || !conversationId) {
      return res.status(400).json({ error: 'Missing required fields' });
    }
    
    // Save user message to memory
    await saveToMemory(message, 'user', conversationId);
    
    // Search for relevant conversation history
    const memoryResults = await searchMemory(message, conversationId);
    
    // Extract relevant context from memory
    let context = "";
    if (memoryResults.data && memoryResults.data.memories) {
      context = memoryResults.data.memories
        .map(mem => {
          const role = mem.metadata?.role || 'unknown';
          return `${role}: ${mem.content}`;
        })
        .join('\n');
    }
    
    // Create messages for OpenAI, including context if available
    const messages = [
      { role: "system", content: "You are a helpful assistant. Use the conversation history provided to give contextual responses." }
    ];
    
    if (context) {
      messages.push({ 
        role: "system", 
        content: `Here is the relevant conversation history:\n${context}` 
      });
    }
    
    messages.push({ role: "user", content: message });
    
    // Get response from OpenAI
    const completion = await openai.chat.completions.create({
      model: "gpt-3.5-turbo",
      messages: messages,
    });
    
    const aiResponse = completion.choices[0].message.content;
    
    // Save assistant response to memory
    await saveToMemory(aiResponse, 'assistant', conversationId);
    
    // Send response to client
    res.json({ 
      message: aiResponse,
      conversationId
    });
    
  } catch (error) {
    console.error('Error processing chat:', error);
    res.status(500).json({ error: error.message });
  }
});

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

{
  "name": "chat-memory",
  "version": "1.0.0",
  "description": "Chat app with Papr Memory and OpenAI",
  "main": "app.js",
  "type": "module",
  "scripts": {
    "start": "node app.js"
  },
  "dependencies": {
    "@papr/sdk": "^1.0.0",
    "dotenv": "^16.3.1",
    "express": "^4.18.2",
    "openai": "^4.0.0"
  }
}

npm start

curl -X POST http://localhost:3000/chat \
  -H "Content-Type: application/json" \
  -d '{
    "message": "What are the benefits of using a vector database?",
    "conversationId": "conv123"
  }'

curl -X POST http://localhost:3000/chat \
  -H "Content-Type: application/json" \
  -d '{
    "message": "How does that compare to traditional databases?",
    "conversationId": "conv123"
  }'