Internship Insights: Enhancing Code Generation with LLMs

This lecture presents an internship report from a student at Alibaba Cloud, focusing on the development of a framework to improve code generation accuracy using large language models (LLMs). The instructor discusses the role of LLMs in understanding and generating human language, emphasizing their application in code generation tasks. The process begins with user requirements, which are decomposed into multiple subtasks. The instructor explains how relevant APIs are identified from the company's library to address these subtasks. By vectorizing both the APIs and the subtasks, the framework, named EPIGEN, enhances the selection of appropriate APIs for code generation. The lecture highlights the importance of combining multiple APIs for certain tasks and introduces new methods for verifying API functionality. The results demonstrate that the EPIGEN framework significantly improves code output performance across various difficulty levels and models, showcasing its potential in the field of artificial intelligence and cloud computing.