Building an End-to-End GenAI App with Ruby and Milvus

The introduction of specialized GenAI frameworks like LangChain has enabled developers to build sophisticated AI applications quickly and easily by leveraging powerful large language models (LLMs) such as ChatGPT and LLaMA. These frameworks allow users to create Retrieval Augmented Generation (RAG) applications in just a few lines of code without requiring deep theoretical AI knowledge. However, these GenAI frameworks are typically written in Python, which may not be familiar to all full-stack engineers and software developers. There is a need for extensions of these GenAI frameworks in other programming languages so that these full-stack engineers can leverage powerful LLMs to build GenAI applications in their software projects. Andrei Bondarev introduced a Ruby extension of LangChain called LangChain.rb to make it easier for full-stack engineers to build GenAI applications in their software projects.