Google Gemini Integration

npm install @google/generative-ai @memorystack/sdk

import { GoogleGenerativeAI } from "@google/generative-ai";
import { MemoryStackClient } from "@memorystack/sdk";

// Initialize clients
const genAI = new GoogleGenerativeAI(process.env.GOOGLE_API_KEY!);
const memoryOS = new MemoryStackClient({
  apiKey: process.env.MEMORYSTACK_API_KEY!
});

async function chatWithMemory(userMessage: string, userId?: string) {
  // Get memories for context
  const memories = await memoryOS.listMemories({
    user_id: userId,
    limit: 5
  });

  const context = memories.results
    .map(m => `[${m.memory_type}] ${m.content}`)
    .join("\n");

  // Initialize Gemini
  const model = genAI.getGenerativeModel({ model: "gemini-pro" });

  // Create prompt with context
  const prompt = `Context about the user:\n${context}\n\nUser: ${userMessage}`;

  // Generate response
  const result = await model.generateContent(prompt);
  const response = result.response.text();

  // Save to Memorystack
  await memoryOS.addConversation(userMessage, response, userId);

  return response;
}

// Usage
const response = await chatWithMemory(
  "What are my preferences?",
  "user_123"
);
console.log(response);

async function streamChatWithMemory(userMessage: string, userId?: string) {
  // Get context
  const memories = await memoryOS.getUserMemories(userId, 5);
  const context = memories.results
    .map(m => `[${m.memory_type}] ${m.content}`)
    .join("\n");

  const model = genAI.getGenerativeModel({ model: "gemini-pro" });
  const prompt = `Context: ${context}\n\nUser: ${userMessage}`;

  // Stream response
  const result = await model.generateContentStream(prompt);
  
  let fullResponse = "";
  for await (const chunk of result.stream) {
    const text = chunk.text();
    fullResponse += text;
    process.stdout.write(text);
  }

  // Save after streaming
  await memoryOS.addConversation(userMessage, fullResponse, userId);

  return fullResponse;
}