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vercel/chatbot

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TLDR

A ready-to-deploy Next.js starter template for building AI chatbot applications with built-in authentication, chat history, and support for multiple AI model providers.

Mindmap

mindmap
  root((repo))
    What it does
      AI chatbot starter
      Multi-model support
      Ready to deploy
    Tech stack
      Next.js
      TypeScript
      Vercel AI SDK
      Auth.js
    Features included
      User authentication
      Chat persistence
      File uploads
      Streaming responses
    Deployment
      One-click Vercel
      Local development
      Environment config
    Use cases
      Custom chat products
      Internal tools
      Customer support bots

Things people build with this

USE CASE 1

Launch a custom AI chat product in minutes without building authentication and database infrastructure from scratch.

USE CASE 2

Build an internal team chatbot that connects to OpenAI, Anthropic, or other AI providers with a single configuration change.

USE CASE 3

Create a customer support chatbot with persistent conversation history and file upload capabilities.

USE CASE 4

Prototype a multi-model AI application that lets users switch between different AI providers on the fly.

Tech stack

TypeScriptNext.jsReactVercel AI SDKAuth.jsNeon PostgreSQLVercel BlobTailwind CSS

Getting it running

Difficulty · moderate Time to first run · 30min

Requires setting up Neon PostgreSQL database and configuring API keys for AI model providers and Auth.js.

Use freely for any purpose, including commercial use, as long as you keep the copyright notice and license text.

In plain English

Vercel Chatbot is a free, open-source starter template for building a full-featured AI chatbot application. It is not a chatbot itself, but rather a ready-made codebase that a developer can clone, configure, and deploy to have a working chat application in minutes, then customize it to their needs. The template is built with Next.js (a popular React-based web framework) and Vercel's AI SDK, which provides a unified interface to multiple large language model providers. Out of the box it supports models from OpenAI, Anthropic, Google, xAI, Mistral, Moonshot, and DeepSeek, all routed through Vercel's AI Gateway, so you can switch between providers with minimal code changes. Authentication (user login) is handled by Auth.js, chat history is stored in a Neon serverless PostgreSQL database, and file uploads go to Vercel Blob storage. The user interface is built with shadcn/ui components styled with Tailwind CSS. On Vercel's own platform, deploying takes a single click; running it locally requires Node.js, the pnpm package manager, and setting up environment variables for the AI gateway and database. The codebase is described as "hackable," meaning it is intended as a starting point to build upon rather than a finished product. You would use this template if you want to launch a custom AI chat product quickly without building all the plumbing from scratch, the authentication, conversation persistence, streaming responses, and multi-model routing are already wired together for you.

Copy-paste prompts

Prompt 1
Clone the Vercel chatbot template and deploy it to Vercel with my own OpenAI API key. What environment variables do I need to set?
Prompt 2
How do I modify this chatbot template to use Anthropic's Claude instead of OpenAI? Show me the code changes.
Prompt 3
I want to add a custom system prompt to this chatbot template so it behaves like a customer support agent. Where in the codebase do I make that change?
Prompt 4
How do I connect this chatbot template to my own PostgreSQL database instead of Neon? What files need to be updated?
Prompt 5
Show me how to add file upload functionality to this chatbot so users can upload documents and ask questions about them.
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Generated 2026-05-18 · Model: sonnet-4-6 · Verify against the repo before relying on details.