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所在平台: Udemy |
课程主页: https://www.udemy.com/course/dspy-develop-a-rag-app-using-dspy-weaviate-and-fastapi/
课程评论：没有评论
Coursera 课程总结：使用 DSPy、Weaviate 和 FastAPI 开发 RAG 应用 本课程将引导您从零开始构建一个完整的、全栈的检索增强生成（RAG）应用程序。您将学习如何运用 FastAPI 构建强大的后端，利用 DSPy 处理文档上传和解析，并通过 Weaviate 管理矢量数据存储。同时，您还将创建一个响应式的 React 前端，为用户提供交互式界面。 **课程主要内容涵盖：** * **FastAPI 后端开发：** 学习如何使用 FastAPI 构建 RESTful API，包括基础的文件上传路由和改进的版本。 * **DSPy 文档解析：** 掌握使用 DSPy 解析文本文档和包含 OCR（光学字符识别）技术的 PDF 文档。 * **Weaviate 矢量数据库：** 了解如何设置 Weaviate 矢量存储，以及如何集成到您的应用程序中。 * **后台任务处理：** 学习如何实现后台任务，以提高应用程序的效率和响应能力。 * **React 前端开发：** 构建用户友好的 React 前端界面，实现与后端的交互。 * **额外的音频 AI 助手项目：** 课程包含一个额外的模块，教您如何构建一个音频 AI 助手，涵盖其前端和后端的实现。 通过本课程的学习，您将获得开发和部署利用检索增强生成技术、实现智能数据处理和响应生成的 AI 应用程序的实践技能。
Learn to build a comprehensive full-stack Retrieval Augmented Generation (RAG) application from scratch using cutting-edge technologies like FastAPI, Weaviate, DSPy, and React. In this hands-on course, you will master the process of developing a robust backend with FastAPI, handling document uploads and parsing with DSPy, and managing vector data storage using Weaviate. You'll also create a responsive React frontend to provide users with an interactive interface. By the end of the course, you'll have the practical skills to develop and deploy AI-powered applications that leverage retrieval-augmented generation techniques for smarter data handling and response generation.Here's the structured outline of your course with sections and lectures:Section 1: IntroductionLecture 1: IntroductionLecture 2: Extra: Learn to Build an Audio AI AssistantLecture 3: Building the API with FastAPISection 2: File UploadLecture 4: Basic File Upload RouteLecture 5: Improved Upload RouteSection 3: Parsing DocumentsLecture 6: Parsing Text DocumentsLecture 7: Parsing PDF Documents with OCRSection 4: Vector Database, Background Tasks, and FrontendLecture 8: Setting Up a Weaviate Vector StoreLecture 9: Adding Background TasksLecture 10: The Frontend, Finally!Section 5: Extra - Build an Audio AI AssistantLecture 11: What You Will BuildLecture 12: The FrontendLecture 13: The BackendLecture 14: The End
