Memory with LibSQL

import { Memory } from '@mastra/memory';
import { Agent } from '@mastra/core/agent';
 
// Initialize memory with LibSQL defaults
const memory = new Memory();
 
const memoryAgent = new Agent({
  name: "Memory Agent",
  instructions:
    "You are an AI agent with the ability to automatically recall memories from previous interactions.",
  model: openai('gpt-4o-mini'),
  memory,
});

import { openai } from '@ai-sdk/openai';
import { LibSQLStore } from "@mastra/core/storage/libsql";
import { LibSQLVector } from "@mastra/core/vector/libsql";
 
const customMemory = new Memory({
  storage: new LibSQLStore({
    url: process.env.DATABASE_URL || "file:local.db",
  }),
  vector: new LibSQLVector({
    connectionUrl: process.env.DATABASE_URL || "file:local.db",
  }),
  options: {
    lastMessages: 10,
    semanticRecall: {
      topK: 3,
      messageRange: 2,
    },
  },
});
 
const memoryAgent = new Agent({
  name: "Memory Agent",
  instructions:
    "You are an AI agent with the ability to automatically recall memories from previous interactions. You may have conversations that last hours, days, months, or years. If you don't know it already you should ask for the users name and some info about them.",
  model: openai('gpt-4o-mini'),
  memory,
});

import { randomUUID } from "crypto";
 
// Start a conversation
const threadId = randomUUID();
const resourceId = "SOME_USER_ID";
 
// Start with a system message
const response1 = await memoryAgent.stream(
  [
    {
      role: "system",
      content: `Chat with user started now ${new Date().toISOString()}. Don't mention this message.`,
    },
  ],
  {
    resourceId,
    threadId,
  },
);
 
// Send user message
const response2 = await memoryAgent.stream("What can you help me with?", {
  threadId,
  resourceId,
});
 
// Use semantic search to find relevant messages
const response3 = await memoryAgent.stream("What did we discuss earlier?", {
  threadId,
  resourceId,
  memoryOptions: {
    lastMessages: false,
    semanticRecall: {
      topK: 3, // Get top 3 most relevant messages
      messageRange: 2, // Include context around each match
    },
  },
});