AI Chatbot

An Open-Source AI Chatbot Template Built With Next.js and the AI SDK by Vercel.

Features · Model Providers · Deploy Your Own · Running locally

Features

• Next.js App Router
  • Advanced routing for seamless navigation and performance
  • React Server Components (RSCs) and Server Actions for server-side rendering and increased performance
• AI SDK
  • Unified API for generating text, structured objects, and tool calls with LLMs
  • Hooks for building dynamic chat and generative user interfaces
  • Supports OpenAI (default), Anthropic, Cohere, and other model providers
• shadcn/ui
  • Styling with Tailwind CSS
  • Component primitives from Radix UI for accessibility and flexibility
• Data Persistence
  • Vercel Postgres powered by Neon for saving chat history and user data
  • Vercel Blob for efficient file storage
• NextAuth.js
  • Simple and secure authentication

Model Providers

This template ships with OpenAI gpt-4o as the default. However, with the AI SDK, you can switch LLM providers to OpenAI, Anthropic, Cohere, and many more with just a few lines of code.

Deploy Your Own

You can deploy your own version of the AI Chatbot to Vercel with one click:

Running locally

You will need to use the environment variables defined in .env.example to run AI Chatbot. It's recommended you use Vercel Environment Variables for this, but a .env file is all that is necessary.

Note: You should not commit your .env file or it will expose secrets that will allow others to control access to your various OpenAI and authentication provider accounts.

1. Install Vercel CLI: npm i -g vercel
2. Link local instance with Vercel and GitHub accounts (creates .vercel directory): vercel link
3. Create a Postgres database with your Vercel Storage
4. Create a Blob store with your Vercel Storage
5. Add the required environment variables to your Vercel project:
   • Database connection string (from step 3)
   • Blob connection string (from step 4)
   • Other variables from .env.example
6. Download your environment variables: vercel env pull
7. Install dependencies:

   pnpm i

8. Run the database migrations:

   pnpm db:push

9. Run the app locally:

   pnpm dev

Your app template should now be running on localhost:3000.