使用Java和Spring AI解锁OpenAI的ChatGPT人工智能（AI）功能 (英文)

Spring AI: 从初学者到大师

发布日期：2024年5月 创建者：John Thompson • 全球超过500,000名注册学员 格式：MP4 | 视频：h264, 1280×720 | 音频：AAC, 44.1 KHz, 2声道 类型：电子学习 | 语言：英语 | 时长：61讲 (4小时28分钟) | 大小：2.61 GB

使用Java和Spring AI解锁OpenAI的ChatGPT人工智能（AI）功能

你将学到：

• 学习如何使用Spring AI与OpenAI进行交互
• 学习如何为大型语言模型编写有效的提示
• 使用检索增强生成（RAG）来提高响应能力
• 将文本生成语音
• 将语音转化为文本

要求：

• 需要Java和Spring经验
• 了解如何使用RESTful API
• 能够使用Docker运行Docker Compose脚本

课程描述：

传统上，访问人工智能模型（如OpenAI的ChatGPT）主要使用编程语言Python和JavaScript。现在，情况不再是这样了。Spring AI为Java开发者解锁了生成式AI的力量。Spring AI项目旨在简化包含人工智能功能的应用程序的开发，而不增加不必要的复杂性。Spring AI支持所有主要的人工智能模型，包括：

• OpenAI
• Azure OpenAI
• Amazon Bedrock
• HuggingFace
• Ollama
• Google VertextAI (PaLM2 和 Gemini)
• Mistral AI
• Anthropic
• WatsonxAI

Spring AI还支持来自OpenAI和Stability的图像生成AI模型。检索增强生成（RAG）是处理AI模型的重要用例。Spring AI包括对所有主要嵌入模型和所有流行向量数据库的强大支持。本课程不需要AI经验。你将从对人工智能的全面概述开始课程。接下来，你将进行一个动手部分，开发一个RESTful API，向OpenAI的ChatGPT提问。在这一部分，你将学习如何指示模型以我们所需的格式返回数据。

由于不需要AI经验，本课程的下一部分将基于你所学的内容，正式介绍提示工程。提示工程是一组提高AI模型响应质量和准确性的技术。检索增强生成（RAG）是一种重要的技术，用于向大型语言模型提供完成用户查询所需的额外信息，以完成专门任务。你将看到如何使用RAG开发AI专家来执行高度专业化的任务。

AI模型不仅限于处理文本信息。在本课程中，你还将了解如何使用AI创建图像、从文本创建音频文件，以及如何将音频文件转录为文本。在《Spring AI: 从初学者到大师》中学习所有这些内容以及更多内容。今天就报名吧！

Spring AI: Beginner to Guru

Published 5/2024
Created by John Thompson • 500,000+ Enrollments Worldwide
MP4 | Video: h264, 1280×720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English | Duration: 61 Lectures ( 4h 28m ) | Size: 2,61 GB

Use Java to Unlock the Power of OpenAI’s ChatGPT Artificial Intelligence (AI) with Spring AI

What you’ll learn:
Learn how to use Spring AI to interact with OpenAI
How to write effective Prompts for Large Language Models
Use Retrieval Augmented Generation to Improve Response Capabilities
Generate Speech from Text
Generate Text from Speech

Requirements:
Java and Spring Experience is Required
Understanding of working with RESTful APIs
Able to use Docker to run a Docker Compose Script

Description:
Traditionally accessing Artificial Intelligence Models, such as OpenAI’s ChatGPT, has been the domain of programming languages Python and Javascript. Not any more. Spring AI unlocks the power of Generative AI for Java developers. The Spring AI project aims to streamline the development of applications that incorporate artificial intelligence functionality without unnecessary complexity. Spring AI provides support for all major Artificial Intelligence models, including:OpenAIAzure OpenAIAmazon BedrockHuggingFaceOllama Google VertextAI (PaLM2 and Gemini)Mistral AIAntrhopicWatsonxAISpring AI also supports image generation AI models from OpenAI and Stability. Retrieval Augmented Generation is an important use case for dealing with AI models. Spring AI includes robust support for all major Embedding Models and all popular vector databases. No prior experience with AI is needed for this course. You will start the course with a solid overview of what Artificial Intelligence is. Next you’ll have a hands on section to develop a RESTful API to ask OpenAI’s ChatGPT questions. In this section, you will learn how we can instruct the model to return data in the format we desire. Since no AI experience is required, the next section of the course builds upon what you learned with a formal look at Prompt Engineering. Prompt Engineering is a collection techniques to improve the quality and accuracy of responses from AI Models.Retrieval Augmented Generation (RAG) is an important technique to provide Large Language Models with additional information required to the user’s query to complete specialized tasks. You will see how we can use RAG to develop AI experts to perform high specialized tasks. The AI models are not just limited to working with textual information. In this course you will also see how to use AI to create images, create audio files from text, and how to transcribe audio files to text. Learn all this and more in Spring A:I Beginner to Guru. Enroll today!

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