Why Build a Custom Chatbot?
Standard chatbots answer using hardcoded FAQ flows. With LLM integrations like OpenAI, you can train a chatbot on your specific knowledge database, giving responses that feel personalized, helpful, and brand-aware.
1. Secure Backend API Routes
Never call OpenAI directly from client-side React code. Doing so leaks your private API keys! Instead, create an API route in Next.js (e.g. src/app/api/chat/route.ts) that forwards user messages safely to the LLM backend.
2. Handling Conversation Threads
AI assistants require context. Use OpenAI's Assistants API to manage message history threads. Store the threadId in the user's session or browser local storage to resume conversations across tabs.
3. Building the Floating Widget UI
A great chatbot needs an interactive interface. Build a responsive overlay that includes a text area, input validations, loading indicators, and smooth scroll buttons that automatically lock to the latest messages.
Conclusion
Integrating AI helps businesses capture leads, automate answers, and decrease customer support tickets. Test our floating widget on the bottom right to see it in action!