Adopting Hybrid Search with Azure Cosmos DB
In an era where data accessibility and retrieval are crucial, Azure Cosmos DB introduces Hybrid Search, a cutting-edge feature that merges the capabilities of Vector Search and Full-Text Search. This integration enhances search relevance by combining semantic understanding with traditional keyword-based methods, making it ideal for diverse applications such as e-commerce, content management, and AI-driven chatbots. The blog provides a comprehensive guide on enabling and configuring Hybrid Search within Azure Cosmos DB, detailing the processes for setting up Vector Search and Full-Text Search. It also explores the underlying mechanics of Hybrid Search, which utilizes Reciprocal Rank Fusion (RRF) to combine multiple scoring functions for more accurate search results. Additionally, practical use cases and a step-by-step project example demonstrate how to implement an enterprise knowledge management system using Nest.js integrated with Azure Cosmos DB's Hybrid Search capabilities. This powerful combination offers developers and businesses the tools needed to create sophisticated, efficient, and intelligent search experiences within their applications.Optimizing Retrieval for RAG Apps: Vector Search and Hybrid Techniques
In this blog we are going to dive into optimizing our search strategy with Hybrid search techniques. Common practices for implementing the retrieval step in retrieval-augmented generation (RAG) applications are; Keyword search Vector Search Hybrid search (Keyword + Vector) Hybrid + Semantic ranker
