RAG-Based AI Assistant for Egyptian Landmarks

**RAG-Based AI Assistant for Egyptian Landmarks** Developed an intelligent AI assistant powered by a Retrieval-Augmented Generation (RAG) system, designed to deliver accurate and concise information about Egyptian tourist landmarks. ### Key Features: * Integrates a vector database (Pinecone) to retrieve verified historical and cultural data. * Processes user queries through an AI agent connected to OpenRouter chat models. * Ensures responses are grounded strictly in stored documents and trusted historical sources. * Provides precise answers including: * Landmark locations * Historical periods * Area measurements (square meters, km², acres) ### Workflow Automation: * Automated data ingestion pipeline using n8n: * Triggered by file uploads on Google Drive * Automatically processes and embeds documents into the vector database * Built-in conversational interface for real-time Q&A * Integrated email automation system for sending responses or updates ### Tech Stack: * n8n (Workflow Automation) * Pinecone (Vector Database) * OpenAI Embeddings * OpenRouter (LLM Access) * Google Drive API ### Use Case: Ideal for tourism platforms, educational tools, and cultural applications that require accurate, data-driven responses about historical landmarks. --- This system ensures high accuracy by minimizing hallucinations and relying only on verified data sources.