The Mem0 AI SDK Provider is a library developed by Mem0 to integrate with the Vercel AI SDK. This library brings enhanced AI interaction capabilities to your applications by introducing persistent memory functionality.
🎉 Exciting news! Mem0 AI SDK now supports Vercel AI SDK V5.
Overview
- 🧠 Offers persistent memory storage for conversational AI
- 🔄 Enables smooth integration with the Vercel AI SDK
- 🚀 Ensures compatibility with multiple LLM providers
- 📝 Supports structured message formats for clarity
- ⚡ Facilitates streaming response capabilities
Setup and Configuration
Install the SDK provider using npm:
npm install @mem0/vercel-ai-provider
Getting Started
Setting Up Mem0
-
Get your Mem0 API Key from the Mem0 Dashboard.
-
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: {
// Options for LLM Provider
},
// Optional Mem0 Global Config
mem0Config: {
user_id: "mem0-user-id",
},
});
Note: The openai provider is set as default. Consider using MEM0_API_KEY and OPENAI_API_KEY as environment variables for security.
Note: 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 { LanguageModelV2Prompt } from "@ai-sdk/provider";
import { addMemories } from "@mem0/vercel-ai-provider";
const messages: LanguageModelV2Prompt = [
{ role: "user", content: [{ type: "text", text: "I love red cars." }] },
];
await addMemories(messages, { user_id: "borat" });
Standalone Features:
await addMemories(messages, { user_id: "borat", mem0ApiKey: "m0-xxx" });
await retrieveMemories(prompt, { user_id: "borat", mem0ApiKey: "m0-xxx" });
await getMemories(prompt, { user_id: "borat", mem0ApiKey: "m0-xxx" });
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.
getMemories is an object with two keys: results and relations if enable_graph is enabled. Otherwise, it will return an array of objects.
1. Basic Text Generation with Memory Context
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!",
});
2. Combining OpenAI Provider with Memory Utils
import { generateText } from "ai";
import { openai } from "@ai-sdk/openai";
import { retrieveMemories } from "@mem0/vercel-ai-provider";
const prompt = "Suggest me a good car to buy.";
const memories = await retrieveMemories(prompt, { user_id: "borat" });
const { text } = await generateText({
model: openai("gpt-4-turbo"),
prompt: prompt,
system: memories,
});
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?" },
],
},
],
});
3. Streaming Responses with Memory Context
import { streamText } from "ai";
import { createMem0 } from "@mem0/vercel-ai-provider";
const mem0 = createMem0();
const { textStream } = 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);
}
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);
5. 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);
The same can be done for streamText as well.
Graph Memory
Mem0 AI SDK now supports Graph Memory. You can enable it by setting enable_graph to true in the mem0Config object.
const mem0 = createMem0({
mem0Config: { enable_graph: true },
});
You can also pass enable_graph in the standalone functions. This includes getMemories, retrieveMemories, and addMemories.
const memories = await getMemories(prompt, { user_id: "borat", mem0ApiKey: "m0-xxx", enable_graph: true });
The getMemories function will return an object with two keys: results and relations, if enable_graph is set to true. Otherwise, it will return an array of objects.
Supported LLM Providers
| Provider | Configuration Value |
|---|
| OpenAI | openai |
| Anthropic | anthropic |
| Google | google |
| Groq | groq |
Note: You can use google as provider for Gemini (Google) models. They are same and internally they use @ai-sdk/google package.
Key Features
createMem0(): Initializes a new Mem0 provider instance.
retrieveMemories(): Retrieves memory context for prompts.
getMemories(): Get memories from your profile in array format.
addMemories(): Adds user memories to enhance contextual responses.
Best Practices
-
User Identification: Use a unique
user_id for consistent memory retrieval.
-
Memory Cleanup: Regularly clean up unused memory data.
Note: We also have support for agent_id, app_id, and run_id. Refer Docs.
Conclusion
Mem0’s Vercel AI SDK enables the creation of intelligent, context-aware applications with persistent memory and seamless integration.
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