chatbot-widget-creator

To add an AI chat widget with SSE streaming, you mount the widget in your React app root and configure backend endpoints for SSE streaming and optional RAG data sources. This provides a ChatGPT-like interface with real-time responses.

RAG integration for chat widgets retrieves and cites source content from documents via a vector-store. It enables the widget to answer user questions using context from integrated documents, improving accuracy on documentation sites and knowledge bases.

Yes, the chat widget requires a React and TypeScript frontend and ships with a compact, glassy UI featuring theme-aware styling and mobile responsiveness for optimal display across various devices and product dashboards.

Yes, the widget includes a text selection Ask AI feature that allows users to highlight page content and ask contextual questions. This works alongside SSE streaming and RAG retrieval for interactive documentation sites.

You need a backend SSE streaming endpoint for real-time AI responses and an optional vector-store content retrieval setup for RAG integration. Configure these endpoints after mounting the widget in your React application root.

Without a vector store, the widget loses RAG-backed content retrieval and citation capabilities, operating only on standard SSE streaming. You still get real-time conversational UX, but cannot retrieve and cite source content from integrated documents.