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Vespa is a distributed search engine, vector database, and machine learning ranking engine. It serves as an AI search platform designed to handle large-scale document indexing and complex query processing across a cluster of nodes, combining keyword retrieval with high-dimensional embedding storage for semantic similarity search. The platform distinguishes itself by integrating machine learning models directly into the search pipeline to perform real-time inference and ranking. It converts these models into ranking expressions to score and order results based on relevance, while providing a s

This project serves as a comprehensive educational resource for implementing modular monoliths and microservices within .NET environments. It focuses on applying domain-driven design principles to manage complex business logic, providing a structured approach to building systems that can evolve alongside changing requirements. The architecture is defined by its emphasis on modularity and clear boundaries, utilizing vertical slices and bounded contexts to organize code by business process rather than technical layer. It distinguishes itself through a systematic migration framework that allows