π‘ Examples
π‘ Examples
OpenAI Inbuilt Tools
π‘ Examples
OpenAI Inbuilt Tools
Integrate Mem0βs memory capabilities with OpenAIβs Inbuilt Tools to create AI agents with persistent memory.
Getting Started
Installation
npm install mem0ai openai zod
Environment Setup
Save your Mem0 and OpenAI API keys in a .env
file:
MEM0_API_KEY=your_mem0_api_key
OPENAI_API_KEY=your_openai_api_key
Get your Mem0 API key from the Mem0 Dashboard.
Configuration
const mem0Config = {
apiKey: process.env.MEM0_API_KEY,
user_id: "sample-user",
};
const openAIClient = new OpenAI();
const mem0Client = new MemoryClient(mem0Config);
Adding Memories
Store user preferences, past interactions, or any relevant information:
async function addUserPreferences() {
const mem0Client = new MemoryClient(mem0Config);
const userPreferences = "I Love BMW, Audi and Porsche. I Hate Mercedes. I love Red cars and Maroon cars. I have a budget of 120K to 150K USD. I like Audi the most.";
await mem0Client.add([{
role: "user",
content: userPreferences,
}], mem0Config);
}
await addUserPreferences();
Retrieving Memories
Search for relevant memories based on the current user input:
const relevantMemories = await mem0Client.search(userInput, mem0Config);
Structured Responses with Zod
Define structured response schemas to get consistent output formats:
// Define the schema for a car recommendation
const CarSchema = z.object({
car_name: z.string(),
car_price: z.string(),
car_url: z.string(),
car_image: z.string(),
car_description: z.string(),
});
// Schema for a list of car recommendations
const Cars = z.object({
cars: z.array(CarSchema),
});
// Create a function tool based on the schema
const carRecommendationTool = zodResponsesFunction({
name: "carRecommendations",
parameters: Cars
});
// Use the tool in your OpenAI request
const response = await openAIClient.responses.create({
model: "gpt-4o",
tools: [{ type: "web_search_preview" }, carRecommendationTool],
input: `${getMemoryString(relevantMemories)}\n${userInput}`,
});
Using Web Search
Combine memory with web search for up-to-date recommendations:
const response = await openAIClient.responses.create({
model: "gpt-4o",
tools: [{ type: "web_search_preview" }, carRecommendationTool],
input: `${getMemoryString(relevantMemories)}\n${userInput}`,
});
Examples
Complete Car Recommendation System
import MemoryClient from "mem0ai";
import { OpenAI } from "openai";
import { zodResponsesFunction } from "openai/helpers/zod";
import { z } from "zod";
import dotenv from 'dotenv';
dotenv.config();
const mem0Config = {
apiKey: process.env.MEM0_API_KEY,
user_id: "sample-user",
};
async function run() {
// Responses without memories
console.log("\n\nRESPONSES WITHOUT MEMORIES\n\n");
await main();
// Adding sample memories
await addSampleMemories();
// Responses with memories
console.log("\n\nRESPONSES WITH MEMORIES\n\n");
await main(true);
}
// OpenAI Response Schema
const CarSchema = z.object({
car_name: z.string(),
car_price: z.string(),
car_url: z.string(),
car_image: z.string(),
car_description: z.string(),
});
const Cars = z.object({
cars: z.array(CarSchema),
});
async function main(memory = false) {
const openAIClient = new OpenAI();
const mem0Client = new MemoryClient(mem0Config);
const input = "Suggest me some cars that I can buy today.";
const tool = zodResponsesFunction({ name: "carRecommendations", parameters: Cars });
// Store the user input as a memory
await mem0Client.add([{
role: "user",
content: input,
}], mem0Config);
// Search for relevant memories
let relevantMemories = []
if (memory) {
relevantMemories = await mem0Client.search(input, mem0Config);
}
const response = await openAIClient.responses.create({
model: "gpt-4o",
tools: [{ type: "web_search_preview" }, tool],
input: `${getMemoryString(relevantMemories)}\n${input}`,
});
console.log(response.output);
}
async function addSampleMemories() {
const mem0Client = new MemoryClient(mem0Config);
const myInterests = "I Love BMW, Audi and Porsche. I Hate Mercedes. I love Red cars and Maroon cars. I have a budget of 120K to 150K USD. I like Audi the most.";
await mem0Client.add([{
role: "user",
content: myInterests,
}], mem0Config);
}
const getMemoryString = (memories) => {
const MEMORY_STRING_PREFIX = "These are the memories I have stored. Give more weightage to the question by users and try to answer that first. You have to modify your answer based on the memories I have provided. If the memories are irrelevant you can ignore them. Also don't reply to this section of the prompt, or the memories, they are only for your reference. The MEMORIES of the USER are: \n\n";
const memoryString = memories.map((mem) => `${mem.memory}`).join("\n") ?? "";
return memoryString.length > 0 ? `${MEMORY_STRING_PREFIX}${memoryString}` : "";
};
run().catch(console.error);
Responses
{
"cars": [
{
"car_name": "Toyota Camry",
"car_price": "$25,000",
"car_url": "https://www.toyota.com/camry/",
"car_image": "https://link-to-toyota-camry-image.com",
"car_description": "Reliable mid-size sedan with great fuel efficiency."
},
{
"car_name": "Honda Accord",
"car_price": "$26,000",
"car_url": "https://www.honda.com/accord/",
"car_image": "https://link-to-honda-accord-image.com",
"car_description": "Comfortable and spacious with advanced safety features."
},
{
"car_name": "Ford Mustang",
"car_price": "$28,000",
"car_url": "https://www.ford.com/mustang/",
"car_image": "https://link-to-ford-mustang-image.com",
"car_description": "Iconic sports car with powerful engine options."
},
{
"car_name": "Tesla Model 3",
"car_price": "$38,000",
"car_url": "https://www.tesla.com/model3",
"car_image": "https://link-to-tesla-model3-image.com",
"car_description": "Electric vehicle with advanced technology and long range."
},
{
"car_name": "Chevrolet Equinox",
"car_price": "$24,000",
"car_url": "https://www.chevrolet.com/equinox/",
"car_image": "https://link-to-chevron-equinox-image.com",
"car_description": "Compact SUV with a spacious interior and user-friendly technology."
}
]
}