AI-Powered RAG Q&A Chatbot with OpenAI, Google Sheets, Glide & Supabase

This project is an intelligent Retrieval-Augmented Generation (RAG) chatbot built using n8n that answers user queries by retrieving relevant information from a custom knowledge base instead of relying solely on a language model's pre-trained knowledge. Documents stored in Google Drive are automatically downloaded, processed, converted into embeddings using OpenAI Embeddings, and indexed into a Qdrant Vector Database for semantic search.

When a user submits a question through a webhook, the chatbot retrieves the most relevant document chunks from Qdrant and provides accurate, context-aware responses using the OpenAI GPT-4 model. If the requested information is unavailable, the chatbot responds appropriately instead of generating misleading answers. Additionally, the workflow includes integrations for Google Calendar to retrieve appointment information and API-based tracking, demonstrating how multiple AI-powered services can be orchestrated within a single workflow.

This automation eliminates the need for manual document searching, enables intelligent knowledge retrieval, and provides a scalable foundation for enterprise knowledge bases, internal support systems, educational assistants, customer support bots, and AI-powered business applications. It combines document indexing, semantic search, conversational AI, calendar integration, and webhook APIs into a single automated solution that delivers fast, reliable, and context-aware responses.