Building an Intelligent QA System with NLP and Milvus

What this post added

This post details the architecture and steps for building an intelligent QA system using Milvus and the BERT NLP model. It describes how to convert questions into feature vectors using BERT, store these vectors in Milvus for similarity search, and use PostgreSQL to retrieve corresponding answers based on the vector IDs. The system architecture, data preparation, feature vector generation, and answer retrieval process are explained with diagrams and code snippets.