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所在平台: Udemy |
课程主页: https://www.udemy.com/course/build-ai-agent-chatbot-rag-langchain-local-llm/
课程评论：没有评论
课程名称：使用Ollama和本地LLM构建与测试AI代理、聊天机器人和RAG 课程概述： 本课程旨在教授完全初学者如何使用本地大型语言模型（LLM）逐步构建基于LLM的应用程序，适合没有任何LangChain知识的学习者。课程不仅涵盖了开发，还将深入评估和测试AI代理、RAG应用和聊天机器人，确保其提供准确可靠的结果，并遵循行业关键指标。 学习内容： - LangChain与LangSmith的基础知识 - 在LangChain中存储对话数据的聊天消息历史 - 并行运行多个链（如RunnableParallels等） - 使用LangChain和Streamlit构建带有消息历史的聊天机器人 - 理解LLM中的工具和工具链 - 为LLM构建工具和自定义工具 - 使用LangChain创建AI代理 - 使用向量存储和本地LLM嵌入实现RAG - 在构建LLM应用程序时结合使用AI代理和RAG工具 - 用LangSmith优化和调试AI应用程序 - 使用RAG对LLM应用进行评估和测试 - 实际项目和实践测试策略 - 使用RAG评估AI代理 整个课程在Jupyter Notebook和Visual Studio环境中进行，提供互动的引导体验，学习者可以无缝运行代码并轻松跟随课程进度。通过本课程结束后，您将能够自信地构建、测试和优化AI驱动的应用程序。
Build & Test AI Agents, Chatbots, and RAG with Ollama & Local LLMs This course is designed for complete beginners-even if you have zero knowledge of LangChain, you'll learn step by step how to build LLM-based applications using local Large Language Models (LLMs).We'll go beyond development and dive into evaluating and testing AI agents, RAG applications, and chatbots using RAGAs to ensure they deliver accurate and reliable results, following key industry metrics for AI performance.What You'll Learn:Fundamentals of LangChain & LangSmithChat Message History in LangChain for storing conversation dataRunning Parallel & Multiple Chains (RunnableParallels, etc.)Building Chatbots with LangChain & Streamlit (with message history)Understanding Tools and Tool chains in LLMBuilding Tools and Custom Tools for LLM Creating AI Agents using LangChainImplementing RAG with vector stores & local LLM embeddingsUsing AI Agents and RAG with Tooling while building LLM AppsOptimizing & Debugging AI applications with LangSmithEvaluating & Testing LLM applications with RAGAsReal-world projects & hands-on testing strategiesAssessing RAG & AI Agents with RAGAsThis entire course is taught inside Jupyter Notebook with Visual Studio, providing an interactive, guided experience where you can run the code seamlessly and follow along effortlessly.By the end of this course, you'll be able to build, test, and optimize AI-powered applications with confidence!
