AI

Mem0 Provider

The Mem0 Provider is a library developed by Mem0 to integrate with the AI SDK. This library brings enhanced AI interaction capabilities to your applications by introducing persistent memory functionality.

🎉 Exciting news! Mem0 AI SDK now supports Tools Call.

Setup

The Mem0 provider is available in the @mem0/vercel-ai-provider module. You can install it with:

pnpm
npm
yarn
pnpm add @mem0/vercel-ai-provider

Provider Instance

First, get your Mem0 API Key from the Mem0 Dashboard.

Then initialize the Mem0 Client in your application:

import { createMem0 } from '@mem0/vercel-ai-provider';


const mem0 = createMem0({
  provider: 'openai',
  mem0ApiKey: 'm0-xxx',
  apiKey: 'provider-api-key',
  config: {
    compatibility: 'strict',
  },
  // Optional Mem0 Global Config
  mem0Config: {
    user_id: 'mem0-user-id',
    org_id: 'mem0-org-id',
    project_id: 'mem0-project-id',
  },
});

The openai provider is set as default. Consider using MEM0_API_KEY and OPENAI_API_KEY as environment variables for security.

The mem0Config is optional. It is used to set the global config for the Mem0 Client (eg. user_id, agent_id, app_id, run_id, org_id, project_id etc).

  • Add Memories to Enhance Context:
import { LanguageModelV1Prompt } from 'ai';
import { addMemories } from '@mem0/vercel-ai-provider';


const messages: LanguageModelV1Prompt = [
  { role: 'user', content: [{ type: 'text', text: 'I love red cars.' }] },
];


await addMemories(messages, { user_id: 'borat' });

Features

Adding and Retrieving Memories

  • retrieveMemories(): Retrieves memory context for prompts.
  • getMemories(): Get memories from your profile in array format.
  • addMemories(): Adds user memories to enhance contextual responses.
await addMemories(messages, {
  user_id: 'borat',
  mem0ApiKey: 'm0-xxx',
  org_id: 'org_xx',
  project_id: 'proj_xx',
});
await retrieveMemories(prompt, {
  user_id: 'borat',
  mem0ApiKey: 'm0-xxx',
  org_id: 'org_xx',
  project_id: 'proj_xx',
});
await getMemories(prompt, {
  user_id: 'borat',
  mem0ApiKey: 'm0-xxx',
  org_id: 'org_xx',
  project_id: 'proj_xx',
});

For standalone features, such as addMemories, retrieveMemories, and getMemories, you must either set MEM0_API_KEY as an environment variable or pass it directly in the function call.

getMemories will return raw memories in the form of an array of objects, while retrieveMemories will return a response in string format with a system prompt ingested with the retrieved memories.

Generate Text with Memory Context

You can use language models from OpenAI, Anthropic, Cohere, and Groq to generate text with the generateText function:

import { generateText } from 'ai';
import { createMem0 } from '@mem0/vercel-ai-provider';


const mem0 = createMem0();


const { text } = await generateText({
  model: mem0('gpt-4-turbo', { user_id: 'borat' }),
  prompt: 'Suggest me a good car to buy!',
});

Structured Message Format with Memory 

import { generateText } from 'ai';
import { createMem0 } from '@mem0/vercel-ai-provider';


const mem0 = createMem0();


const { text } = await generateText({
  model: mem0('gpt-4-turbo', { user_id: 'borat' }),
  messages: [
    {
      role: 'user',
      content: [
        { type: 'text', text: 'Suggest me a good car to buy.' },
        { type: 'text', text: 'Why is it better than the other cars for me?' },
      ],
    },
  ],
});

Streaming Responses with Memory Context 

import { streamText } from 'ai';
import { createMem0 } from '@mem0/vercel-ai-provider';


const mem0 = createMem0();


const { textStream } = await streamText({
  model: mem0('gpt-4-turbo', {
    user_id: 'borat',
  }),
  prompt:
    'Suggest me a good car to buy! Why is it better than the other cars for me? Give options for every price range.',
});


for await (const textPart of textStream) {
  process.stdout.write(textPart);
}

Generate Responses with Tools Call 

import { generateText } from 'ai';
import { createMem0 } from '@mem0/vercel-ai-provider';
import { z } from 'zod';


const mem0 = createMem0({
  provider: 'anthropic',
  apiKey: 'anthropic-api-key',
  mem0Config: {
    // Global User ID
    user_id: 'borat',
  },
});


const prompt = 'What the temperature in the city that I live in?';


const result = await generateText({
  model: mem0('claude-3-5-sonnet-20240620'),
  tools: {
    weather: tool({
      description: 'Get the weather in a location',
      parameters: z.object({
        location: z.string().describe('The location to get the weather for'),
      }),
      execute: async ({ location }) => ({
        location,
        temperature: 72 + Math.floor(Math.random() * 21) - 10,
      }),
    }),
  },
  prompt: prompt,
});


console.log(result);

Get sources from memory 

const { text, sources } = await generateText({
  model: mem0('gpt-4-turbo'),
  prompt: 'Suggest me a good car to buy!',
});


console.log(sources);

This same functionality is available in the streamText function.

Best Practices

  • User Identification: Use a unique user_id for consistent memory retrieval.
  • Memory Cleanup: Regularly clean up unused memory data.

We also have support for agent_id, app_id, and run_id. Refer Docs.

Help

  • For more details on Vercel AI SDK, visit the Vercel AI SDK documentation.
  • For Mem0 documentation, refer to the Mem0 Platform.
  • If you need further assistance, please feel free to reach out to us through following methods:

References