包阅导读总结
1.
– `Microsoft`、`Prompty`、`.NET 开发`、`语言模型`、`VS Code 扩展`
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Microsoft 发布了名为 Prompty 的新 VS Code 扩展，用于将大型语言模型集成到.NET 开发工作流程中，该工具免费，提供直观界面，虽创新但有人对其可用性存忧，文中还介绍了使用步骤和实际案例。
3.
– Microsoft 发布新 VS Code 扩展 Prompty
– 旨在将大型语言模型如 GPT-4o 直接融入.NET 开发流程
– 免费工具，简化添加 AI 驱动能力的过程
– 可用性及反馈
– 可在 Visual Studio Code Marketplace 免费获取
– 但有社区成员对其在 Visual Studio Professional 上的不可用表示失望
– 使用步骤
– 从市场安装
– 安装后配置，提供 API 密钥和设置参数连接语言模型
– 集成到开发流程，可创建或修改文件，插入提示
– 直接在代码中写提示与语言模型交互，支持多种格式和语法高亮
– 支持快速迭代和测试以优化提示
– 实际案例
– Bruno Capuano 展示如何增强.NET WebAPI 项目，生成详细天气预报描述
– 可在扩展页面或 GitHub 上的源代码获取更多信息
思维导图：
文章来源：infoq.com
作者：Robert Krzaczyński
发布时间：2024/8/28 0:00
语言：英文
总字数：413字
预计阅读时间：2分钟
评分：86分
标签：AI 集成,.NET 开发,Visual Studio Code,大型语言模型,Prompty
以下为原文内容
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Microsoft released a new Visual Studio Code extension called Prompty, designed to integrate Large Language Models (LLMs) like GPT-4o directly into .NET development workflows. This free tool aims to simplify the process of adding AI-driven capabilities to applications. The official release post includes a practical example demonstrating how Prompty can be used in real-world scenarios.
Prompty is available for free on the Visual Studio Code Marketplace and offers .NET developers an intuitive interface to interact with LLMs. Whether creating chatbots, generating content, or enhancing other AI-driven functionalities, Prompty provides an easy way to integrate these capabilities into existing development environments.
While Prompty has been well-received for its innovative approach to integrating AI into .NET development, some community members have expressed concerns about its availability. On LinkedIn, Jordi Gonzalez Segura expressed disappointment that Prompty is not accessible to those using Visual Studio Professional.
Using Prompty in Visual Studio Code involves several steps:
- Installation: Developers start by installing the Prompty extension from the Visual Studio Code Marketplace.
- Setup: After installation, users configure the extension by providing API keys and setting up necessary parameters to connect to the LLM, such as GPT-4o.
- Integration: Prompty integrates into the development workflow by allowing users to create new files or modify existing ones with embedded prompts. Commands and snippets are provided to easily insert prompts and handle responses from the LLM.
- Development: Developers can write prompts directly in the codebase to interact with the LLM. Prompty supports various prompt formats and offers syntax highlighting, making it easier to read and maintain prompts. These prompts help in generating code snippets, creating documentation, or troubleshooting by querying the LLM for specific issues.
- Testing: Prompty enables rapid iteration and testing, allowing developers to refine prompts to improve response accuracy and relevance.
Bruno Capuano, a principal cloud advocate at Microsoft, prepared a real-world use case demonstrating how Prompty can enhance a .NET WebAPI project. In this example, Prompty generates detailed weather forecast descriptions, transforming the standard output into richer and more engaging content. Developers can dynamically produce detailed weather summaries by defining prompts within a .prompty file and setting up the necessary configurations to interact with the LLM. This practical application leverages the Semantic Kernel to automate the generation of descriptive text, improving the quality and informativeness of the application’s output.
Additional information about Prompty, its features, and integration into development workflows can be found on the Prompty Visual Studio Code extension page or in the Prompty source code available on GitHub.
