|
所在平台: Udemy |
课程主页: https://www.udemy.com/course/build-ai-apps-with-spring-ai-openai-springboot/
课程评论：没有评论
课程名称：使用Spring AI、OpenAI、Ollama和SpringBoot构建AI应用 课程概述： 本课程旨在帮助您在Java应用中解锁生成性AI的强大功能，使用Spring AI、OpenAI和Ollama。通过实践操作，您将学习如何利用强大的Spring Boot生态系统构建智能、可扩展的AI驱动应用。课程内容涵盖从创作提示到构建完整的基于RAG（检索增强生成）的系统，您将获得将大语言模型（LLMs）整合到实际项目中的实用技能。 课程内容包括： 1. 课程介绍与环境设置： - 理解课程结构、先决条件和如何设置Java及Spring AI环境。 2. 大语言模型（LLMs）、OpenAI和ChatGPT简介： - 学习LLM的基本知识、演变和应用，以及OpenAI的ChatGPT如何融入现代AI工作流。 3. 开始使用Spring AI和OpenAI API： - 配置项目和IDE，创建第一个基于聊天的应用，理解提示、标记和OpenAI请求参数。 4. 与Chat模型和OpenAI的工作： - 自定义LLM响应，启用流式传输，构建响应式AI聊天应用。 5. 提示工程与Spring AI： - 掌握提示工程技术，如零-shot、few-shot、思维链和多步骤提示，有效引导AI输出。 6. 使用Spring AI生成结构化数据： - 学习使用提示模板和Spring的转换器创建结构化输出，包括列表、映射和实体对象。 7. 使用Spring AI进行功能调用： - 将外部系统整合到AI应用中，通过OpenAI的工具调用获取实时数据，如天气、货币汇率等。 8. 构建基于RAG的应用： - 使用PgVector、文档分块、索引和语义检索构建端到端的RAG驱动问答系统。 9. 文档导入策略： - 探索如何使用不同的读取器和拆分器导入和分块各种文档类型，包括PDF、Word文件和纯文本。 10. 探索多模态性：视觉能力： - 利用OpenAI的图像模型生成、分析和处理图像，展示现实世界的实例，如发票解析。 11. 探索多模态性：音频能力： - 使用文本转语音（TTS）技术将文本转换为真实语音，利用Whisper API将语音转录或翻译为文本。 12. 使用Spring AI和Ollama构建本地AI应用： - 本地运行LLM，借助Ollama与Spring AI集成，无需依赖外部API构建应用。 课程结束时，您将具备使用Java和Spring Boot构建全栈AI驱动应用的能力，整合云模型、本地部署、视觉、音频和检索增强技术。您将自信满满，具备将生成性AI应用于生产就绪的Java应用中的经验。
Course DescriptionUnlock the power of Generative AI within your Java applications using Spring AI, OpenAI, and Ollama!In this hands-on course, you'll learn how to build intelligent, scalable AI-driven applications using the robust Spring Boot ecosystem. From crafting prompts to building full RAG-based systems, you'll gain practical skills to integrate LLMs into real-world projects.Here's a breakdown of what you'll learn in each section:Course Introduction & SetupUnderstand the course structure, prerequisites, and how to set up your Java and Spring AI environment.Introduction to Large Language Models (LLMs), OpenAI & ChatGPTLearn the basics of LLMs, their evolution, applications, and how OpenAI's ChatGPT fits into modern AI workflows.Getting Started with Spring AI and OpenAI APIConfigure your project and IDE, create your first chat-based app using ChatClient, and understand prompts, tokens, and OpenAI request parameters.Working with Chat Models and OpenAIChatModelCustomize LLM responses using ChatOptions, enable streaming, and build responsive AI chat applications.Prompt Engineering with Spring AIMaster prompt engineering techniques like zero-shot, few-shot, chain-of-thought, and multi-step prompting to guide AI outputs effectively.Generating Structured Data with Spring AILearn to create structured outputs using prompt templates and Spring's converters, including lists, maps, and entity objects.Tool Calling (Function Calling) with Spring AIIntegrate external systems into your AI apps with OpenAI's tool calling-fetch live data like weather, currency rates, and more.Building RAG Applications (Retrieval-Augmented Generation)Build an end-to-end RAG-powered Q & A system using PgVector, document chunking, indexing, and semantic retrieval.Document Ingestion StrategiesExplore how to ingest and chunk various document types including PDFs, Word files, and plain text using different readers and splitters.Exploring Multimodality: Vision CapabilitiesLeverage OpenAI's image models to generate, analyze, and process images including real-world examples like invoice parsing.Exploring Multimodality: Audio CapabilitiesConvert text to realistic voice using TTS, and transcribe or translate speech to text using the Whisper API.Building Local AI Apps with Spring AI and OllamaRun LLMs locally using Ollama, integrate it with Spring AI, and build applications without relying on external APIs.By the end of this course, you'll be equipped to build full-stack AI-powered applications using Java and Spring Boot, with integrations that span cloud-based models, local deployments, vision, audio, and retrieval-augmented techniques.You'll walk away with the confidence and experience to bring Generative AI into production-ready Java applications.
