Multi Panel LLM chat with Next JS, Vercel AI sdk. with separate system messages and model selection

The video demonstrates the creation of a Next.js application featuring six resizable chat bots with individual system messages and the Vercel AI SDK integration. Users can customize their chat experience by resizing panels, selecting different models, and toggling between light and dark modes, showcasing a dynamic and interactive chat application development process.

In the video, the presenter showcases a Next.js application featuring six chat bots with resizable React components and the Vercel AI SDK integration. Each chat bot has its own system message and the ability to switch between different models and light/dark modes. The system messages range from answering in JSON to Morse Code in French. Users can resize the panels to chat with different numbers of bots, from one to six, offering a customizable chat experience.

The code structure of the Next.js project includes an API folder and a chat folder under it, utilizing folder-based routing. The application uses the React Resizable Panels library for handling panel resizing. The main page, page.tsx, defines the layout of the chat panels using the PanelGroup and PanelResizeHandle components. The chat content within the panels is sourced from separate components, such as the ChatPanel, which leverages the Vercel AI SDK for chat functionality.

Within the ChatPanel component, state variables are defined for settings like temperature, model selection, light/dark mode, and system messages. The component utilizes hooks like useState, useEffect, and useRef to manage chat state and interactions. The useChat hook facilitates handling chat messages, input changes, and form submissions to the Vercel AI API. The component also includes functionality for scrolling to the end of messages and styling based on the selected model and theme.

The configuration panel allows users to adjust settings like temperature, model selection, system messages, and dark mode/light mode. Dropdowns and buttons enable users to toggle between different models and themes. The chat messages display area showcases the conversation history with styling based on message sender. The input form allows users to send messages, trigger form submissions, and interact with the chat bots seamlessly.

The API setup involves importing the Vercel AI and Entropic libraries for handling streaming responses from the AI models. An async function processes post requests, logging message details and interacting with the AI models based on the selected configuration. The backend logic ensures proper model selection, temperature adjustment, and message streaming to the front end. Overall, the video provides a detailed walkthrough of building a dynamic chat application with Next.js, resizable panels, and the Vercel AI SDK integration for interactive chatbot experiences.