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


Book Description

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.




Mastering LLM Applications with LangChain and Hugging Face


Book Description

DESCRIPTION The book is all about the basics of NLP, generative AI, and their specific component LLM. In this book, we have provided conceptual knowledge about different terminologies and concepts of NLP and NLG with practical hands-on. This comprehensive book offers a deep dive into the world of NLP and LLMs. Starting with the fundamentals of Python programming and code editors, the book gradually introduces NLP concepts, including text preprocessing, word embeddings, and transformer architectures. You will explore the architecture and capabilities of popular models like GPT-3 and BERT. The book also covers practical aspects of LLM usage for RAG applications using frameworks like LangChain and Hugging Face and deploying them in real world applications. With a focus on both theoretical knowledge and hands-on experience, this book is ideal for anyone looking to master the art of NLP and LLMs. The book also contains AWS Cloud deployment, which will help readers step into the world of cloud computing. As the book contains both theoretical and practical approaches, it will help the readers to gain confidence in the deployment of LLMs for any use cases, as well as get acquainted with the required generative AI knowledge to crack the interviews. KEY FEATURES ● Covers Python basics, NLP concepts, and terminologies, including LLM and RAG concepts. ● Provides exposure to LangChain, Hugging Face ecosystem, and chatbot creation using custom data. ● Guides on integrating chatbots with real-time applications and deploying them on AWS Cloud. WHAT YOU WILL LEARN ● Basics of Python, which contains Python concepts, installation, and code editors. ● Foundation of NLP and generative AI concepts and different terminologies being used in NLP and generative AI domain. ● LLMs and their importance in the cutting edge of AI. ● Creating chatbots using custom data using open source LLMs without spending a single penny. ● Integration of chatbots with real-world applications like Telegram. WHO THIS BOOK IS FOR This book is ideal for beginners and freshers entering the AI or ML field, as well as those at an intermediate level looking to deepen their understanding of generative AI, LLMs, and cloud deployment. TABLE OF CONTENTS 1. Introduction to Python and Code Editors 2. Installation of Python, Required Packages, and Code Editors 3. Ways to Run Python Scripts 4. Introduction to NLP and its Concepts 5. Introduction to Large Language Models 6. Introduction of LangChain, Usage and Importance 7. Introduction of Hugging Face, its Usage and Importance 8. Creating Chatbots Using Custom Data with LangChain and Hugging Face Hub 9. Hyperparameter Tuning and Fine Tuning Pre-Trained Models 10. Integrating LLMs into Real-World Applications–Case Studies 11. Deploying LLMs in Cloud Environments for Scalability 12. Future Directions: Advances in LLMs and Beyond Appendix A: Useful Tips for Efficient LLM Experimentation Appendix B: Resources and References




Generative AI with LangChain


Book Description

2024 Edition – Get to grips with the LangChain framework to develop production-ready applications, including agents and personal assistants. The 2024 edition features updated code examples and an improved GitHub repository. Purchase of the print or Kindle book includes a free PDF eBook. Key Features Learn how to leverage LangChain to work around LLMs’ inherent weaknesses Delve into LLMs with LangChain and explore their fundamentals, ethical dimensions, and application challenges Get better at using ChatGPT and GPT models, from heuristics and training to scalable deployment, empowering you to transform ideas into reality Book DescriptionChatGPT and the GPT models by OpenAI have brought about a revolution not only in how we write and research but also in how we can process information. This book discusses the functioning, capabilities, and limitations of LLMs underlying chat systems, including ChatGPT and Gemini. It demonstrates, in a series of practical examples, how to use the LangChain framework to build production-ready and responsive LLM applications for tasks ranging from customer support to software development assistance and data analysis – illustrating the expansive utility of LLMs in real-world applications. Unlock the full potential of LLMs within your projects as you navigate through guidance on fine-tuning, prompt engineering, and best practices for deployment and monitoring in production environments. Whether you're building creative writing tools, developing sophisticated chatbots, or crafting cutting-edge software development aids, this book will be your roadmap to mastering the transformative power of generative AI with confidence and creativity.What you will learn Create LLM apps with LangChain, like question-answering systems and chatbots Understand transformer models and attention mechanisms Automate data analysis and visualization using pandas and Python Grasp prompt engineering to improve performance Fine-tune LLMs and get to know the tools to unleash their power Deploy LLMs as a service with LangChain and apply evaluation strategies Privately interact with documents using open-source LLMs to prevent data leaks Who this book is for The book is for developers, researchers, and anyone interested in learning more about LangChain. Whether you are a beginner or an experienced developer, this book will serve as a valuable resource if you want to get the most out of LLMs using LangChain. Basic knowledge of Python is a prerequisite, while prior exposure to machine learning will help you follow along more easily.




Generative AI with Amazon Bedrock


Book Description

Become proficient in Amazon Bedrock by taking a hands-on approach to building and scaling generative AI solutions that are robust, secure, and compliant with ethical standards Key Features Learn the foundations of Amazon Bedrock from experienced AWS Machine Learning Specialist Architects Master the core techniques to develop and deploy several AI applications at scale Go beyond writing good prompting techniques and secure scalable frameworks by using advanced tips and tricks Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionThe concept of generative artificial intelligence has garnered widespread interest, with industries looking to leverage it to innovate and solve business problems. Amazon Bedrock, along with LangChain, simplifies the building and scaling of generative AI applications without needing to manage the infrastructure. Generative AI with Amazon Bedrock takes a practical approach to enabling you to accelerate the development and integration of several generative AI use cases in a seamless manner. You’ll explore techniques such as prompt engineering, retrieval augmentation, fine-tuning generative models, and orchestrating tasks using agents. The chapters take you through real-world scenarios and use cases such as text generation and summarization, image and code generation, and the creation of virtual assistants. The latter part of the book shows you how to effectively monitor and ensure security and privacy in Amazon Bedrock. By the end of this book, you’ll have gained a solid understanding of building and scaling generative AI apps using Amazon Bedrock, along with various architecture patterns and security best practices that will help you solve business problems and drive innovation in your organization.What you will learn Explore the generative AI landscape and foundation models in Amazon Bedrock Fine-tune generative models to improve their performance Explore several architecture patterns for different business use cases Gain insights into ethical AI practices, model governance, and risk mitigation strategies Enhance your skills in employing agents to develop intelligence and orchestrate tasks Monitor and understand metrics and Amazon Bedrock model response Explore various industrial use cases and architectures to solve real-world business problems using RAG Stay on top of architectural best practices and industry standards Who this book is for This book is for generalist application engineers, solution engineers and architects, technical managers, ML advocates, data engineers, and data scientists looking to either innovate within their organization or solve business use cases using generative AI. A basic understanding of AWS APIs and core AWS services for machine learning is expected.




Mastering Large Language Models


Book Description

Do not just talk AI, build it: Your guide to LLM application development KEY FEATURES ● Explore NLP basics and LLM fundamentals, including essentials, challenges, and model types. ● Learn data handling and pre-processing techniques for efficient data management. ● Understand neural networks overview, including NN basics, RNNs, CNNs, and transformers. ● Strategies and examples for harnessing LLMs. DESCRIPTION Transform your business landscape with the formidable prowess of large language models (LLMs). The book provides you with practical insights, guiding you through conceiving, designing, and implementing impactful LLM-driven applications. This book explores NLP fundamentals like applications, evolution, components and language models. It teaches data pre-processing, neural networks , and specific architectures like RNNs, CNNs, and transformers. It tackles training challenges, advanced techniques such as GANs, meta-learning, and introduces top LLM models like GPT-3 and BERT. It also covers prompt engineering. Finally, it showcases LLM applications and emphasizes responsible development and deployment. With this book as your compass, you will navigate the ever-evolving landscape of LLM technology, staying ahead of the curve with the latest advancements and industry best practices. WHAT YOU WILL LEARN ● Grasp fundamentals of natural language processing (NLP) applications. ● Explore advanced architectures like transformers and their applications. ● Master techniques for training large language models effectively. ● Implement advanced strategies, such as meta-learning and self-supervised learning. ● Learn practical steps to build custom language model applications. WHO THIS BOOK IS FOR This book is tailored for those aiming to master large language models, including seasoned researchers, data scientists, developers, and practitioners in natural language processing (NLP). TABLE OF CONTENTS 1. Fundamentals of Natural Language Processing 2. Introduction to Language Models 3. Data Collection and Pre-processing for Language Modeling 4. Neural Networks in Language Modeling 5. Neural Network Architectures for Language Modeling 6. Transformer-based Models for Language Modeling 7. Training Large Language Models 8. Advanced Techniques for Language Modeling 9. Top Large Language Models 10. Building First LLM App 11. Applications of LLMs 12. Ethical Considerations 13. Prompt Engineering 14. Future of LLMs and Its Impact




ChatGPT for Conversational AI and Chatbots


Book Description

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.




Programming Large Language Models with Azure Open AI


Book Description

Use LLMs to build better business software applications Autonomously communicate with users and optimize business tasks with applications built to make the interaction between humans and computers smooth and natural. Artificial Intelligence expert Francesco Esposito illustrates several scenarios for which a LLM is effective: crafting sophisticated business solutions, shortening the gap between humans and software-equipped machines, and building powerful reasoning engines. Insight into prompting and conversational programming—with specific techniques for patterns and frameworks—unlock how natural language can also lead to a new, advanced approach to coding. Concrete end-to-end demonstrations (featuring Python and ASP.NET Core) showcase versatile patterns of interaction between existing processes, APIs, data, and human input. Artificial Intelligence expert Francesco Esposito helps you: Understand the history of large language models and conversational programming Apply prompting as a new way of coding Learn core prompting techniques and fundamental use-cases Engineer advanced prompts, including connecting LLMs to data and function calling to build reasoning engines Use natural language in code to define workflows and orchestrate existing APIs Master external LLM frameworks Evaluate responsible AI security, privacy, and accuracy concerns Explore the AI regulatory landscape Build and implement a personal assistant Apply a retrieval augmented generation (RAG) pattern to formulate responses based on a knowledge base Construct a conversational user interface For IT Professionals and Consultants For software professionals, architects, lead developers, programmers, and Machine Learning enthusiasts For anyone else interested in natural language processing or real-world applications of human-like language in software




Generative AI from Beginner to Paid Professional, Part 2


Book Description

Unlock the Future of Generative AI and Skyrocket Your Career. This book is your comprehensive roadmap from grasping the fundamentals of AI to mastering the tools and techniques that will set you apart in today’s AI-driven world. Perfect for anyone serious about a career in AI, this book bridges the gap between knowledge and action, giving you the tools to earn, build, and innovate with generative AI technologies. Whether you’re building your first AI project or refining your professional skills, this is the guide you’ve been waiting for. Packed with hands-on projects and practical exercises, this book empowers you to build and launch your very own generative AI solutions. By the end, you’ll not only be equipped with in-demand AI skills but also be prepared to launch your AI projects in the real world. Welcome to Generative AI from Beginner to Paid Professional, Part 2: Master Prompt Design, Gemini Multimodal in Vertex AI Studio, LangChain, Launching & Deploying Generative AI Projects. In Part 2 of this transformative guide, you'll delve deep into powerful AI frameworks and cutting-edge technologies, including Gemini Multimodal, Vertex AI Studio, and LangChain, gaining the expertise needed to design custom AI solutions and deploy scalable AI projects. Whether you’re an aspiring professional or a seasoned developer, this book is your step-by-step companion to navigating the evolving landscape of generative AI. What You’ll Learn: 1. Master Prompt Design: Craft perfect prompts that make your AI work for you, no matter the use case. 2. Gemini Multimodal & Vertex AI Studio: Learn to integrate multimodal models into your AI pipeline, revolutionizing how you build intelligent systems that understand and generate both text and images. 3. LangChain for Real-World AI Projects: Leverage LangChain to create robust, API-powered workflows that bring your AI projects to life. 4. Launching & Deploying AI Projects: From conceptualization to deployment, turn your AI ideas into real-world applications with proven strategies.




AI-Assisted Programming


Book Description

Get practical advice on how to leverage AI development tools for all stages of code creation, including requirements, planning, design, coding, debugging, testing, and documentation. With this book, beginners and experienced developers alike will learn how to use a wide range of tools, from general-purpose LLMs (ChatGPT, Gemini, and Claude) to code-specific systems (GitHub Copilot, Tabnine, Cursor, and Amazon CodeWhisperer). You'll also learn about more specialized generative AI tools for tasks such as text-to-image creation. Author Tom Taulli provides a methodology for modular programming that aligns effectively with the way prompts create AI-generated code. This guide also describes the best ways of using general purpose LLMs to learn a programming language, explain code, or convert code from one language to another. This book examines: The core capabilities of AI-based development tools Pros, cons, and use cases of popular systems such as GitHub Copilot and Amazon CodeWhisperer Ways to use ChatGPT, Gemini, Claude, and other generic LLMs for coding Using AI development tools for the software development lifecycle, including requirements, planning, coding, debugging, and testing Prompt engineering for development Using AI-assisted programming for tedious tasks like creating regular expressions, starter code, object-oriented programming classes, and GitHub Actions How to use AI-based low-code and no-code tools, such as to create professional UIs




Software Testing


Book Description

This updated and reorganized fourth edition of Software Testing: A Craftsman's Approach applies the strong mathematics content of previous editions to a coherent treatment of Model-Based Testing for both code-based (structural) and specification-based (functional) testing. These techniques are extended from the usual unit testing discussions to full coverage of less understood levels integration and system testing. The Fourth Edition: Emphasizes technical inspections and is supplemented by an appendix with a full package of documents required for a sample Use Case technical inspection Introduces an innovative approach that merges the Event-Driven Petri Nets from the earlier editions with the "Swim Lane" concept from the Unified Modeling Language (UML) that permits model-based testing for four levels of interaction among constituents in a System of Systems Introduces model-based development and provides an explanation of how to conduct testing within model-based development environments Presents a new section on methods for testing software in an Agile programming environment Explores test-driven development, reexamines all-pairs testing, and explains the four contexts of software testing Thoroughly revised and updated, Software Testing: A Craftsman’s Approach, Fourth Edition is sure to become a standard reference for those who need to stay up to date with evolving technologies in software testing. Carrying on the tradition of previous editions, it will continue to serve as a valuable reference for software testers, developers, and engineers.