🤖 AI Powered RAG Chatbot for Your Docs + Google Drive + Gemini + Qdrant

Description

🤖 AI-Powered RAG Chatbot with Google Drive Integration

This workflow creates a powerful RAG (Retrieval-Augmented Generation) chatbot that can process, store, and interact with documents from Google Drive using Qdrant vector storage and Google's Gemini AI.

How It Works

Document Processing & Storage 📚
Retrieves documents from a specified Google Drive folder
Processes and splits documents into manageable chunks
Extracts metadata using AI for enhanced search capabilities
Stores document vectors in Qdrant for efficient retrieval

Intelligent Chat Interface 💬
Provides a conversational interface powered by Google Gemini
Uses RAG to retrieve relevant context from stored documents
Maintains chat history in Google Docs for reference
Delivers accurate, context-aware responses

Vector Store Management 🗄️
Features secure delete operations with human verification
Includes Telegram notifications for important operations
Maintains data integrity with proper version control
Supports batch processing of documents

Setup Steps

Configure API Credentials:
Set up Google Drive & Docs access
Configure Gemini AI API
Set up Qdrant vector store connection
Add Telegram bot for notifications
Add OpenAI Api Key to the 'Delete Qdrant Points by File ID' node

Configure Document Sources:
Set Google Drive folder ID
Define Qdrant collection name
Set up document processing parameters

Test and Deploy:
Verify document processing
Test chat functionality
Confirm vector store operations
Check notification system


This workflow is ideal for organizations needing to create intelligent chatbots that can access and understand large document repositories while maintaining context and providing accurate responses through RAG technology.