AI-Powered API Documentation Indexing and Query System 🤖

A powerful document (especially API documentation) indexing and querying system that leverages LlamaIndex, pgvector, and Hugging Face embeddings to provide intelligent search and question-answering capabilities through a FastAPI interface.

🌟 Features

• Web Page Indexing: Automatically extract and index content from web pages
• Vector Similarity Search: Utilize pgvector for efficient similarity-based search
• AI-Powered Q&A: Generate intelligent responses using LlamaIndex and Llama 2
• RESTful API: Easy-to-use FastAPI endpoints
• Docker Support: Fully containerized application
• Scalable Architecture: Built with production-ready components

🛠️ Technical Stack

• FastAPI: Modern web framework for building APIs
• LlamaIndex: Advanced document indexing and querying
• pgvector: PostgreSQL extension for vector similarity search
• Hugging Face: State-of-the-art text embeddings (BAAI/bge-small-en-v1.5)
• Docker & Docker Compose: Application containerization
• PostgreSQL: Reliable database storage

📋 Prerequisites

• Docker and Docker Compose installed
• Python 3.9 or higher
• At least 4GB of available RAM
• Internet connection for pulling Docker images and accessing APIs