Chatbot

<a href="https://chatbot.ai-sdk.dev/demo"> <img alt="Chatbot" src="app/(chat)/opengraph-image.png"> <h1 align="center">Chatbot</h1> </a> <p align="center"> Chatbot (formerly AI Chatbot) is a free, open-source template built with Next.js and the AI SDK that helps you quickly build powerful chatbot applications. </p> <p align="center"> <a href="https://chatbot.ai-sdk.dev/docs"><strong>Read Docs</strong></a> · <a href="#features"><strong>Features</strong></a> · <a href="#model-providers"><strong>Model Providers</strong></a> · <a href="#deploy-your-own"><strong>Deploy Your Own</strong></a> · <a href="#running-locally"><strong>Running locally</strong></a> </p> <br/>

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, Anthropic, Google, xAI, and other model providers via AI Gateway
• shadcn/ui
  • Styling with Tailwind CSS
  • Component primitives from Radix UI for accessibility and flexibility
• Data Persistence
  • Neon Serverless Postgres for saving chat history and user data
  • Vercel Blob for efficient file storage
• Auth.js
  • Simple and secure authentication

Model Providers

This template uses the Vercel AI Gateway to access multiple AI models through a unified interface. Models are configured in lib/ai/models.ts with per-model provider routing. Included models: Mistral, Moonshot, DeepSeek, OpenAI, and xAI.

AI Gateway Authentication

For Vercel deployments: Authentication is handled automatically via OIDC tokens.

For non-Vercel deployments: You need to provide an AI Gateway API key by setting the AI_GATEWAY_API_KEY environment variable in your .env.local file.

With the AI SDK, you can also switch to direct LLM providers like OpenAI, Anthropic, Cohere, and many more with just a few lines of code.

Deploy Your Own

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

Running locally

You will need to use the environment variables defined in .env.example to run 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 AI 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. Download your environment variables: vercel env pull

pnpm install
pnpm db:migrate # Setup database or apply latest database changes
pnpm dev

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