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Liquid AI Chatbot Next.js AI template interface
AI Chatbot Template

Liquid AI Chatbot

Liquid AI Chatbot is an open-source Next.js AI template by Suhas Bhairav with a responsive UI, server-side AI route, environment setup, and production hardening notes.

Direct answer

Liquid AI Chatbot is a Next.js OpenRouter chatbot template for multi-model AI chat, free model experimentation, streaming responses, and server-side OpenRouter API key handling.

Features

Responsive UI
Server-side AI route
Environment variable setup
Open-source starter
Production hardening notes

Use cases

AI Chatbot TemplateLiquid AI ChatbotAI SaaS prototypeFounder prototypeOpen-source starter

Freshness and tested metadata

last Tested
2026-07-13
next Version
Next.js 16.2.1
node Version
Node.js 20+
runtime
Next.js App Router
deployment
Vercel-ready starter
license
MIT
status
Open Source

Architecture

Next.js App Router page for the user-facing interface.
React components for the responsive chat, workflow, or document interaction surface.
Server-side route for AI provider calls so credentials stay outside the browser.
Tailwind CSS styling for a mobile-ready interface.
OpenRouter SDK integration for multi-model routing, streaming responses, and model-specific experimentation.

Setup path

  1. 1Clone the GitHub repository linked above.
  2. 2Install dependencies with npm install.
  3. 3Create a local environment file from the example variables.
  4. 4Add the required AI provider API key on the server side.
  5. 5Run the local Next.js development server and test the primary workflow.

Related AI template categories

Internal template pathways

Frequently asked questions

What is Liquid AI Chatbot?

Liquid AI Chatbot is a Next.js OpenRouter chatbot template for multi-model AI chat, free model experimentation, streaming responses, and server-side OpenRouter API key handling.

Who should use Liquid AI Chatbot?

Use Liquid AI Chatbot if you are a Next.js developer, AI product builder, applied AI engineer, or founder looking for an open-source AI app starter instead of rebuilding the same AI interface and server route from scratch.

Is Liquid AI Chatbot production-ready?

It is a strong implementation starter, but production deployments should add authentication, persistent storage, monitoring, rate limits, policy checks, and business-specific UX before launch.