Building a Real Search Engine - BM25 Implementation with Vespa and Python - Part 1

Learn to build a complete BM25 keyword search engine from scratch using Vespa and Python in this 25-minute tutorial that launches a comprehensive series on constructing search and RAG systems. Master the fundamentals of creating a Vespa application package, defining schemas with proper fields and ranking profiles, and implementing BM25 scoring algorithms for effective document retrieval. Discover how to deploy Vespa within Docker containers, stream real-world web datasets directly from Hugging Face, and efficiently feed documents into your search system with built-in progress tracking capabilities. Practice executing BM25-ranked search queries to retrieve relevant results from your indexed document collection. Gain hands-on experience with the core components that form the foundation for advanced search technologies, preparing you for subsequent episodes that will cover vector search implementations, embedding techniques, hybrid retrieval methods, and complete RAG pipeline development.