Build a document-based AI chatbot with Google Drive, Llama 3, and Qdrant RAG

Overview This template allows users to set up an AI-powered chatbot that retrieves and processes knowledge from Google Drive documents using Retrieval-Augmented Generation (RAG). By leveraging Llama 3 for natural language responses and Qdrant vector storage for document embeddings, this chatbot provides accurate, context-aware answers based on stored files.

Problem It Solves Standard AI chatbots often rely on predefined models with limited real-time knowledge access. This workflow overcomes that limitation by:

Automatically fetching new documents from Google Drive.

Embedding knowledge for fast retrieval using Qdrant.

Generating human-like responses with Llama 3 AI.

Providing accurate, source-backed answers in conversations.

Use Cases ✔️ Customer Support – Retrieve and summarize FAQs stored in Google Drive. ✔️ Internal Knowledge Base – Automate document-based query responses. ✔️ AI-powered Research Assistant – Search and generate insights from uploaded files. ✔️ Business Automation – Enhance workflows with document-aware chat interactions.

Setup Instructions 1️⃣ Google Drive Trigger: Detect & Fetch New Documents Watches for new files added to a specific Google Drive folder.