Gemini Chatbot
Gemini Chatbot — Build your own generative UI chatbot using the Vercel AI SDK and Google Gemini
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What is Gemini Chatbot?
Gemini Chatbot — This is an open-source AI chatbot template powered by the Google Gemini model, built with Next.js and the AI SDK by Vercel. It provides developers with a complete starting point for building generative UI chatbots with a seamless chat experience using server-side streamText and client-side useChat hooks.
Key features include Next.js App Router for advanced routing, React Server Components for server-side rendering, AI SDK for unified LLM API access, support for multiple model providers (Google Gemini as default, plus OpenAI, Anthropic, Cohere), shadcn/ui styling with Tailwind CSS, Radix UI primitives for accessibility, Vercel Postgres powered by Neon for chat history persistence, Vercel Blob for object storage, and NextAuth.js for authentication.
The template is designed for developers who want to build AI-powered chat applications quickly. It is ideal for developers building chatbots, AI startup teams prototyping AI features, developers learning Next.js and AI integration, and anyone wanting to deploy a Gemini-powered chat app to Vercel with one click.
The template is completely free and open-source, available on GitHub. Users only pay for the AI API usage through their chosen model provider (like Google Gemini API), and the template includes rate limiting and authentication out of the box.
Gemini Chatbot pricing
Pricing model: Freemium
The template itself is completely free and open-source. Users only pay for Google Gemini API usage (or other LLM providers they choose) separately through their API provider account. Google's Gemini Developer API has a free tier available at Google AI Studio for obtaining API keys. When deploying to Vercel, the AI Gateway offers a free tier with $5 monthly credit for AI Gateway Credits. Once on paid tier, it is pay-as-you-go with no markup on provider list prices. BYOK (Bring Your Own Key) mode is supported with no additional markup from Vercel.
Gemini Chatbot pros
- Open-source and completely free to use
- Default Google Gemini gemini-1.5-pro model included
- Easy switching to OpenAI, Anthropic, Cohere with few lines of code
- Next.js App Router for advanced routing and performance
- React Server Components for server-side rendering
- AI SDK unified API for text, structured objects, and tool calls
- useChat hook for seamless client-side chat experience
- streamText function for server-side streaming
- shadcn/ui components with Tailwind CSS styling
- Radix UI primitives for accessibility
- Vercel Postgres powered by Neon for chat history
- Vercel Blob for efficient object storage
- NextAuth.js authentication built-in
- One-click deployment to Vercel
- Rate limiting included out of the box
- Data persistence for user chat history
- Supports file inputs including PDFs and images
Gemini Chatbot cons
- Requires Google Gemini API key (separate paid account needed)
- Must set up environment variables manually
- Requires Vercel CLI for optimal setup
- Not a hosted product - self-hosted template only
- Users pay separately for AI API token usage
- Requires Node.js/pnpm installation
- Learning curve for Next.js and AI SDK
- Authentication setup requires provider configuration
Frequently asked questions about Gemini Chatbot
What is the Gemini Chatbot template?
It is an open-source AI chatbot template built with Next.js and the AI SDK by Vercel, powered by Google Gemini. It provides a complete starting point for building generative UI chatbots with streaming text, authentication, data persistence, and support for multiple LLM providers.
Is the template free to use?
Yes, the template is completely free and open-source. You can clone it from GitHub and deploy it at no cost. However, you will need to pay for the AI API usage (Google Gemini or other providers) separately through your API provider account.
What model does it use by default?
The template ships with Google Gemini gemini-1.5-pro as the default model. However, with the AI SDK, you can easily switch to OpenAI, Anthropic, Cohere, and many other LLM providers with just a few lines of code.
How do I deploy it to Vercel?
You can deploy your own version to Vercel with one click using the Vercel deployment button. Alternatively, you can install Vercel CLI, link your local instance with Vercel and GitHub accounts, download environment variables, then run pnpm install and pnpm dev to run locally at localhost:3000.
What environment variables do I need?
You need to use the environment variables defined in .env.example to run the chatbot. This includes your Google Generative AI API key (GOOGLE_GENERATIVE_AI_API_KEY) and authentication provider secrets. It is recommended to use Vercel Environment Variables rather than a local .env file for production.
How do I get a Gemini API key?
You can obtain a free API key at Google AI Studio. Set the GOOGLE_GENERATIVE_AI_API_KEY environment variable with your API key to use Gemini models with the AI SDK.
Can I use other LLM providers besides Gemini?
Yes, the AI SDK allows you to switch LLM providers to OpenAI, Anthropic, Cohere, and many more with just a few lines of code. The unified API abstracts away differences between model providers.
Does it support chat history?
Yes, the template includes Vercel Postgres powered by Neon for saving chat history and user data. Data persistence is built-in so conversations are saved and can be retrieved later.
What authentication does it use?
The template uses NextAuth.js for simple and secure authentication. You will need to configure your authentication provider secrets in the environment variables.
Can I use it for commercial projects?
Yes, it is an open-source template available on GitHub that you can use for any purpose including commercial projects. You are free to modify, distribute, and deploy it as needed for your AI chatbot applications.