Building Generative Ai Applications With Open Source Libraries
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Building Generative AI Applications with Open-source Libraries
Author: Srikannan Balakrishnan
language: en
Publisher: BPB Publications
Release Date: 2025-03-27
Generative AI is revolutionizing how we interact with technology, empowering us to create everything from compelling text to intricate code. This book is your practical guide to harnessing the power of open-source libraries, enabling you to build cutting-edge generative AI applications without needing extensive prior experience. In this book, you will journey from foundational concepts like natural language processing and transformers to the practical implementation of large language models. Learn to customize foundational models for specific industries, master text embeddings, and vector databases for efficient information retrieval, and build robust applications using LangChain. Explore open-source models like Llama and Falcon and leverage Hugging Face for seamless implementation. Discover how to deploy scalable AI solutions in the cloud while also understanding crucial aspects of data privacy and ethical AI usage. By the end of this book, you will be equipped with technical skills and practical knowledge, enabling you to confidently develop and deploy your own generative AI applications, leveraging the power of open-source tools to innovate and create. WHAT YOU WILL LEARN ● Building AI applications using LangChain and integrating RAG. ● Implementing large language models like Llama and Falcon. ● Utilizing Hugging Face for efficient model deployment. ● Developing scalable AI applications in cloud environments. ● Addressing ethical considerations and data privacy in AI. ● Practical application of vector databases for information retrieval. WHO THIS BOOK IS FOR This book is for aspiring tech professionals, students, and creative minds seeking to build generative AI applications. While a basic understanding of programming and an interest in AI are beneficial, no prior generative AI expertise is required. TABLE OF CONTENTS 1. Getting Started with Generative AI 2. Overview of Foundational Models 3. Text Processing and Embeddings Fundamentals 4. Understanding Vector Databases 5. Exploring LangChain for Generative AI 6. Implementation of LLMs 7. Implementation Using Hugging Face 8. Developments in Generative AI 9. Deployment of Applications 10. Generative AI for Good
Building Generative AI-Powered Apps
Generative AI has gone beyond the responsibility of researchers and data scientists and is being used by production engineers. However, there is a lot of confusion where to get started when building an end-to-end app with generative AI. This book consolidates core models, frameworks, and tools into a single source of knowledge. By providing hands-on examples, the book takes you through the generative AI ecosystem to build applications for production. The book starts with a brief and accessible introduction to transformer models before delving into some of the most popular large language models and diffusions models (image generation). These models are the foundations of both AI and your potential new apps. You will then go through various tools available to work with these models, starting with Langchain, a framework to develop foundational models, which is the next building block you should grasp after understanding generative AI models. The next chapters cover databases, caching, monitoring, etc., which are the topics necessary to build larger-scale applications. Real-world examples using these models and tools are included. By the end of this book, you should be able to build end-to-end apps that are powered by generative AI. You also should be able to apply the tools and techniques taught in this book to your use cases and business. What You Will Learn What is Generative AI? What is ChatGPT and GPT4? What are language models and diffusions models? How do we deploy LangChain and HuggingFace? Who This Book Is For Software engineers with a few years of experience building applications in any language or infrastructure
Building Conversational Generative AI Apps with Langchain and GPT
TAGLINE Transform Text into Intelligent Conversations with LangChain and GPT. KEY FEATURES ● Build AI Chatbots with LangChain, Python and GPT models through hands-on guidance. ● Master Advanced Techniques like RAG, document embedding, and LLM fine-tuning. ● Deploy and Scale conversational AI systems for real-world applications. DESCRIPTION Conversational AI Apps are revolutionizing the way we interact with technology, enabling businesses and developers to create smarter, more intuitive applications that engage users in natural, meaningful ways. Building Conversational Generative AI Apps with LangChain and GPT is your ultimate guide to mastering AI-driven conversational systems. Starting with core concepts of generative AI and LLMs, you'll learn to build intelligent chatbots and virtual assistants, while exploring techniques like fine-tuning LLMs, retrieval-augmented generation (RAG), and document embedding. As you progress, you'll dive deeper into advanced topics such as vector databases and multimodal capabilities, enabling you to create highly accurate, context-aware AI agents. The book's step-by-step tutorials ensure that you develop practical skills in deploying and optimizing scalable conversational AI solutions. By the end, you'll be equipped to build AI apps that enhance customer engagement, automate workflows, and scale seamlessly. Unlock the potential of Building Conversational Generative AI Apps with LangChain and GPT and create next-gen AI applications today! WHAT WILL YOU LEARN ● Build and deploy AI-driven chatbots using LangChain and GPT models. ● Implement advanced techniques like retrieval-augmented generation (RAG) for smarter responses. ● Fine-tune LLMs for domain-specific conversational AI applications. ● Leverage vector databases for efficient knowledge retrieval and enhanced chatbot performance. ● Explore multimodal capabilities and document embedding for better context-aware responses. ● Optimize and scale conversational AI systems for large-scale deployments. WHO IS THIS BOOK FOR? This book is for developers, data scientists, and AI enthusiasts eager to build conversational applications using LangChain and GPT models. While a basic understanding of Python and machine learning concepts is beneficial, the book offers step-by-step guidance, making it accessible to both beginners and experienced practitioners. TABLE OF CONTENTS 1. Introduction to Conversational Generative AI 2. Natural Language Processing (NLP) Fundamentals 3. The Building Blocks of Rule-Based Chatbots 4. Statistical Language Models for Text Generation 5. Neural Network Architectures for Conversation 6. The Transformer Architecture Revolution 7. Unveiling ChatGPT and Architectures 8. Langchain Framework for Building Conversational AI 9. Exploring the LLM Landscape beyond GPT 10. The Transformative Impact of Conversational AI 11. Challenges and Opportunities in LLM Development Index