mem0-vercel-ai-sdk

Name: mem0-vercel-ai-sdk
Availability: InStock
Author: Mem0

Retrieve and store memories around LLM calls in Vercel AI SDK applications.

62.9k|7.3k|Updated Jun 20, 2023

Search Tags:#typescript #memory #nextjs #provider #ai-sdk #mem0 #vercel-ai-provider

Ready to run

npx skills add https://github.com/mem0ai/mem0 --skill mem0-vercel-ai-sdk

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: mem0-vercel-ai-sdk
Source: https://github.com/mem0ai/mem0/tree/main/skills/mem0-vercel-ai-sdk
Command: npx skills add https://github.com/mem0ai/mem0 --skill mem0-vercel-ai-sdk

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

Mem0 provides a memory-augmented AI provider for Vercel AI SDK applications, enabling seamless retrieval and storage of memories around LLM calls.

Core Features & Use Cases

Memory-aware LLM integration via wrapped model pattern with automatic memory retrieval before a call and memory storage after
Standalone utilities to retrieve, store, and search memories for flexible workflows
Streaming support with memory-augmented responses across Next.js API routes and multi-provider setups

Quick Start

Install the Mem0 Vercel AI SDK provider and wrap your LLM calls to enable automatic memory retrieval and storage.

Frequently Asked Questions about mem0-vercel-ai-sdk

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I add memory to LLM calls in a Vercel AI SDK application?▼

To add memory to LLM calls in a Vercel AI SDK application, you can wrap your model calls with the Mem0 provider to automatically retrieve relevant memories before generation and store new memories after the response.

Can I use memory-augmented AI with streaming responses in Next.js?▼

Yes, memory-augmented AI supports streaming responses in Next.js API routes, allowing you to retrieve and store memories seamlessly while streaming outputs across multi-provider configurations.

What standalone utilities are available for storing and retrieving memories outside of LLM calls?▼

Standalone memory utilities include functions to retrieve, store, and search memories independently, such as addMemories, getMemories, searchMemories, and retrieveMemories for flexible workflow integration.

Does the Mem0 Vercel AI provider work with multiple LLM configurations?▼

Yes, the Mem0 Vercel AI provider supports multi-provider configurations, enabling memory retrieval and storage around LLM calls across different AI models within your application setup.

How does the wrapped model pattern handle memory retrieval and storage?▼

The wrapped model pattern handles memory by automatically injecting retrieved memories as context before an LLM call and extracting new information to store as memories after the call completes.

What is the best way to search through stored memories in a TypeScript AI application?▼

The best way to search stored memories in a TypeScript AI application is using the searchMemories function, which queries previously saved context to provide relevant historical data for your workflows.