Automate Conversations With Langchain
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Automate Conversations with LangChain
Author: Edward Coldiron
language: en
Publisher: Independently Published
Release Date: 2025-02-23
Automate Conversations with LangChain: Build Intelligent Chatbots and Virtual Assistants Conversational AI is transforming the way businesses and developers interact with users. Automate Conversations with LangChain is a practical guide that takes you through building intelligent chatbots and virtual assistants using LangChain, a powerful framework for developing AI-driven applications. Whether you're creating a customer support bot, a virtual assistant for productivity, or a specialized chatbot for a unique use case, this book equips you with the knowledge and hands-on skills to bring your ideas to life. By the end of this book, you'll have a deep understanding of how to design, develop, and deploy robust conversational AI solutions that are context-aware, efficient, and scalable. This book provides a step-by-step approach to building intelligent chatbots and virtual assistants using LangChain. It covers key topics such as prompt engineering, retrieval-augmented generation (RAG), memory management, API integrations, and advanced techniques like multi-turn dialogues and self-healing chatbots. Through practical examples and real-world use cases, you'll learn how to enhance chatbot performance, optimize responses, and scale your solutions for enterprise applications. Key Features of This Book Learn the fundamentals of LangChain and its role in AI-driven chatbots. Implement memory and context retention to improve conversation flow. Use retrieval-augmented generation (RAG) for better response accuracy. Integrate APIs, external tools, and databases to enhance chatbot capabilities. Optimize chatbot behavior using prompt engineering and fine-tuning techniques. Handle multi-turn conversations, decision trees, and fallback mechanisms. Deploy, scale, and monitor chatbots for real-world applications. This book is ideal for: Developers looking to build and deploy intelligent chatbots using LangChain. AI and ML enthusiasts eager to explore the practical applications of conversational AI. Business professionals and product managers interested in automating customer interactions. Data scientists who want to integrate LLM-powered chatbots into their workflows. Ready to build smarter chatbots? Automate Conversations with LangChain provides everything you need to design, implement, and scale AI-powered conversational agents. Whether you're a beginner or an experienced developer, this hands-on guide will help you unlock the full potential of LangChain. Start your journey today and revolutionize the way you interact with AI!
ChatGPT for Conversational AI and Chatbots
Author: Adrian Thompson
language: en
Publisher: Packt Publishing Ltd
Release Date: 2024-07-30
Explore ChatGPT technologies to create state-of-the-art chatbots and voice assistants, and prepare to lead the AI revolution Key Features Learn how to leverage ChatGPT to create innovative conversational AI solutions for your organization Harness LangChain and delve into step-by-step LLM application development for conversational AI Gain insights into security, privacy, and the future landscape of large language models and conversational AI Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionChatGPT for Conversational AI and Chatbots is a definitive resource for exploring conversational AI, ChatGPT, and large language models. This book introduces the fundamentals of ChatGPT and conversational AI automation. You’ll explore the application of ChatGPT in conversation design, the use of ChatGPT as a tool to create conversational experiences, and a range of other practical applications. As you progress, you’ll delve into LangChain, a dynamic framework for LLMs, covering topics such as prompt engineering, chatbot memory, using vector stores, and validating responses. Additionally, you’ll learn about creating and using LLM-enabling tools, monitoring and fine tuning, LangChain UI tools such as LangFlow, and the LangChain ecosystem. You’ll also cover popular use cases, such as using ChatGPT in conjunction with your own data. Later, the book focuses on creating a ChatGPT-powered chatbot that can comprehend and respond to queries directly from your unique data sources. The book then guides you through building chatbot UIs with ChatGPT API and some of the tools and best practices available. By the end of this book, you’ll be able to confidently leverage ChatGPT technologies to build conversational AI solutions.What you will learn Gain a solid understanding of ChatGPT and its capabilities and limitations Understand how to use ChatGPT for conversation design Discover how to use advanced LangChain techniques, such as prompting, memory, agents, chains, vector stores, and tools Create a ChatGPT chatbot that can answer questions about your own data Develop a chatbot powered by ChatGPT API Explore the future of conversational AI, LLMs, and ChatGPT alternatives Who this book is for This book is for tech-savvy readers, conversational AI practitioners, engineers, product owners, business analysts, and entrepreneurs wanting to integrate ChatGPT into conversational experiences and explore the possibilities of this game-changing technology. Anyone curious about using internal data with ChatGPT and looking to stay up to date with the developments in large language models will also find this book helpful. Some expertise in coding and standard web design concepts would be useful, along with familiarity with conversational AI terminology, though not essential.
Textual Intelligence
The book is a must-have resource for anyone looking to understand the complexities of generative AI, offering comprehensive insights into LLMs, effective training strategies, and practical applications. Textual Intelligence: Large Language Models and Their Real-World Applications provides an overview of generative AI and its multifaceted applications, as well as the significance and potential of Large Language Models (LLMs), including GPT and LLaMA. It addresses the generative AI project lifecycle, challenges in existing data architectures, proposed use case planning and scope definition, model deployment, and application integration. Training LLMs, data requirements for effective LLM training, pre-training and fine-tuning processes, and navigating computational resources and infrastructure are also discussed. The volume delves into in-context learning and prompt engineering, offering strategies for crafting effective prompts, techniques for controlling model behavior and output quality, and best practices for prompt engineering. Textual Intelligence: Large Language Models and Their Real-World Applications also discusses cost optimization strategies for LLM training, aligning models to human values, optimizing model architectures, the power of transfer learning and fine-tuning, instruction fine-tuning for precision, and parameter-efficient fine-tuning (PEFT) with adapters such as LoRA, QLoRA, and soft prompts, making it an essential guide for both beginners and industry veterans. Readers will find this book: Explores the real-world potential of large language models; Introduces industry-changing AI solutions; Provides advanced insights on AI and its models. Audience Industry professionals, academics, graduate students, and researchers seeking real-world solutions using generative AI.