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LangChain for RAG Beginners - Build Your First Powerful AI GPT Agent
註釋

Dive into the world of advanced AI with "Python LangChain for RAG Beginners"

✔ Learn how to code Agentic RAG Powered Chatbot Systems.

✔ Empower your Agents with Tools 

✔ Learn how to Create your Own Agents

This comprehensive guide takes you on a journey through LangChain, an innovative framework designed to harness the power of Generative Pre-trained Transformers (GPTs) and other large language models (LLMs) for creating sophisticated AI-driven applications.

Starting from the basics, this book provides a detailed understanding of how to effectively use LangChain to build, customize, and deploy AI applications that can think, learn, and interact seamlessly. You will explore the core concepts of LangChain, including prompt engineering, memory management, and Retrieval Augmented Generation (RAG). Each chapter is packed with practical examples and code snippets that demonstrate real-world applications and use cases.

Key highlights include:


Getting Started with LangChain: Learn the foundational principles and set up your environment.

Advanced Prompt Engineering: Craft effective prompts to enhance AI interactions.

Memory Management: Implement various memory types to maintain context and continuity in conversations.

Retrieval Augmented Generation (RAG): Integrate external knowledge bases to expand your AI's capabilities.

Building Intelligent Agents: Create agents that can autonomously perform tasks and make decisions.

Practical Use Cases: Explore building a chat agent with web UI that allows you chatting with documents, web retrieval, vector databases for long term memory and much more !

Whether you are an AI enthusiast, a developer looking to integrate AI into your projects, or a professional aiming to stay ahead in the AI-driven world, " Python LangChain for RAG Beginners" provides the tools and knowledge to elevate your AI skills. Embrace the future of AI and transform your ideas into powerful, intelligent applications with LangChain.