This paper presents the latest progress of GPTutor: a ChatGPT-powered programming tool extension in Visual Studio Code. The emergence of Large Language Models (LLMs) has improved software development efficiency, but their performance can be hindered by training data limitations and prompt design issues. Existing LLM development tools often operate as black boxes, with users unable to view the prompts used and unable to improve performance by correcting prompts when errors occur. To address the aforementioned issues, GPTutor was introduced as an open-source AI pair programming tool, offering an alternative to Copilot. GPTutor empowers users to customize prompts for various programming languages and scenarios, with support for 120+ human languages and 50+ programming languages. Users can fine-tune prompts to correct the errors from LLM for precision and efficient code generation. At the end of the paper, we underscore GPTutor's potential through examples, including demonstrating its proficiency in interpreting and generating Sui-Move, a newly introduced smart contract language, using prompt engineering.

翻译：本文介绍了基于ChatGPT的Visual Studio Code编程工具扩展GPTutor的最新进展。大语言模型的出现提升了软件开发效率，但其性能可能受到训练数据局限性和提示设计问题的制约。现有大语言模型开发工具常以黑箱模式运行，用户既无法查看所使用的提示信息，也无法在出现错误时通过修正提示来改进性能。针对上述问题，我们推出了开源AI结对编程工具GPTutor作为Copilot的替代方案。该工具支持用户针对不同编程语言和场景自定义提示，兼容120余种自然语言和50余种编程语言。用户可通过微调提示来纠正大语言模型生成的错误，从而实现精准高效的代码生成。在论文结尾部分，我们通过案例展示了GPTutor的潜力，包括该工具如何利用提示工程成功解读和生成Sui-Move（一种新推出的智能合约语言）代码。