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Building Generative AI-Powered Apps

Author : Aarushi Kansal
Publisher : Apress
Page : 0 pages
File Size : 24,55 MB
Release : 2024-04-16
Category : Computers
ISBN :

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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

Generative AI for Web Development

Author : Tom Auger
Publisher : Apress
Page : 0 pages
File Size : 20,35 MB
Release : 2025-02-10
Category : Computers
ISBN :

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Explore the world of Generative AI and understand why it matters. This book is divided into two parts, introducing tools such as ChatGPT, DALL-E, and will show you how to use them to build AI-powered web apps. The first part of the book describes Generative AI and covers the essential models and APIs from OpenAI. Legal, ethical, and security considerations are discussed to help you decide whether it is an appropriate tool for your projects. You’ll then review ChatGPT and see how to use it effectively for generating code. This is followed by a review of best practices, and tips and techniques for getting around the limitations of ChatGPT and other OpenAI APIs. The second part of the book provides practical guide to building a series of web apps with Next.js that showcase how to use the OpenAI APIs. For example, you’ll learn how to build a Story/Poetry generator, a language learning app, and a blog site with a custom Chatbot widget. The code for the web apps is generated using ChatGPT. When done with this book, you’ll have a clear understanding of Generative AI and be well on your way to building web applications powered by OpenAI APIs and Next.js. What You Will Learn Assess the legal, ethical, and security concerns with using Generative AI in web applications Review the latest APIs provided by OpenAI for generating text and image Use ChatGPT to generate code for web projects, as well as tips and tricks to working around the limitations. Who This Book Is For Experienced web developers and software engineers who know their way around HTML, CSS, and JavaScript, but have limited or no experience using Generative AI to build web applications.

Building LLM Powered Applications

Author : Valentina Alto
Publisher : Packt Publishing Ltd
Page : 343 pages
File Size : 16,94 MB
Release : 2024-05-22
Category : Computers
ISBN : 1835462634

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Get hands-on with GPT 3.5, GPT 4, LangChain, Llama 2, Falcon LLM and more, to build LLM-powered sophisticated AI applications Key Features Embed LLMs into real-world applications Use LangChain to orchestrate LLMs and their components within applications Grasp basic and advanced techniques of prompt engineering Book DescriptionBuilding LLM Powered Applications delves into the fundamental concepts, cutting-edge technologies, and practical applications that LLMs offer, ultimately paving the way for the emergence of large foundation models (LFMs) that extend the boundaries of AI capabilities. The book begins with an in-depth introduction to LLMs. We then explore various mainstream architectural frameworks, including both proprietary models (GPT 3.5/4) and open-source models (Falcon LLM), and analyze their unique strengths and differences. Moving ahead, with a focus on the Python-based, lightweight framework called LangChain, we guide you through the process of creating intelligent agents capable of retrieving information from unstructured data and engaging with structured data using LLMs and powerful toolkits. Furthermore, the book ventures into the realm of LFMs, which transcend language modeling to encompass various AI tasks and modalities, such as vision and audio. Whether you are a seasoned AI expert or a newcomer to the field, this book is your roadmap to unlock the full potential of LLMs and forge a new era of intelligent machines.What you will learn Explore the core components of LLM architecture, including encoder-decoder blocks and embeddings Understand the unique features of LLMs like GPT-3.5/4, Llama 2, and Falcon LLM Use AI orchestrators like LangChain, with Streamlit for the frontend Get familiar with LLM components such as memory, prompts, and tools Learn how to use non-parametric knowledge and vector databases Understand the implications of LFMs for AI research and industry applications Customize your LLMs with fine tuning Learn about the ethical implications of LLM-powered applications Who this book is for Software engineers and data scientists who want hands-on guidance for applying LLMs to build applications. The book will also appeal to technical leaders, students, and researchers interested in applied LLM topics. We don’t assume previous experience with LLM specifically. But readers should have core ML/software engineering fundamentals to understand and apply the content.

Generative AI Apps with LangChain and Python

Author : Rabi Jay
Publisher : Apress
Page : 0 pages
File Size : 22,86 MB
Release : 2024-12-12
Category : Computers
ISBN :

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Future-proof your programming career through practical projects designed to grasp the intricacies of LangChain’s components, from core chains to advanced conversational agents. This hands-on book provides Python developers with the necessary skills to develop real-world Large Language Model (LLM)-based Generative AI applications quickly, regardless of their experience level. Projects throughout the book offer practical LLM solutions for common business issues, such as information overload, internal knowledge access, and enhanced customer communication. Meanwhile, you’ll learn how to optimize workflows, enhance embedding efficiency, select between vector stores, and other optimizations relevant to experienced AI users. The emphasis on real-world applications and practical examples will enable you to customize your own projects to address pain points across various industries. Developing LangChain-based Generative AI LLM Apps with Python employs a focused toolkit (LangChain, Pinecone, and Streamlit LLM integration) to practically showcase how Python developers can leverage existing skills to build Generative AI solutions. By addressing tangible challenges, you’ll learn-by-be doing, enhancing your career possibilities in today’s rapidly evolving landscape. What You Will Learn Understand different types of LLMs and how to select the right ones for responsible AI. Structure effective prompts. Master LangChain concepts, such as chains, models, memory, and agents. Apply embeddings effectively for search, content comparison, and understanding similarity. Setup and integrate Pinecone vector database for indexing, structuring data, and search. Build Q & A applications for multiple doc formats. Develop multi-step AI workflow apps using LangChain agents. Who This Book Is For Python programmers who aim to develop a basic understanding of AI concepts and move from LLM theory to practical Generative AI application development using LangChain; those seeking a structured guide to enhance their careers by learning to create robust, real-world LLM-powered Generative AI applications; data scientists, analysts, and experienced developers new to LLMs.

Generative AI-Powered Assistant for Developers

Author : Behram Irani
Publisher : Packt Publishing Ltd
Page : 416 pages
File Size : 20,68 MB
Release : 2024-08-30
Category : Computers
ISBN : 1835081207

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Leverage Amazon Q Developer to boost productivity and maximize efficiency by accelerating software development life cycle tasks Key Features First book on the market to thoroughly explore all of Amazon Q Developer’s features Gain an understanding of Amazon Q Developer's capabilities across the software development life cycle through real-world examples Build apps with Amazon Q Developer by auto-generating code in various languages within supported IDEs Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionMany developers face the challenge of managing repetitive tasks and maintaining productivity. This book will help you tackle both these challenges with Amazon Q Developer, a generative AI-powered assistant designed to optimize coding and streamline workflows. This book takes you through the setup and customization of Amazon Q Developer, demonstrating how to leverage its capabilities for auto-code generation, code explanation, and transformation across multiple IDEs and programming languages. You'll learn to use Amazon Q Developer to enhance coding experiences, generate accurate code references, and ensure security by scanning for vulnerabilities. The book also shows you how to use Amazon Q Developer for AWS-related tasks, including solution building, applying architecture best practices, and troubleshooting errors. Each chapter provides practical insights and step-by-step guidance to help you fully integrate this powerful tool into your development process. You’ll get to grips with effortless code implementation, explanation, transformation, and documentation, helping you create applications faster and improve your development experience. By the end of this book, you’ll have mastered Amazon Q Developer to accelerate your software development lifecycle, improve code quality, and build applications faster and more efficiently.What you will learn Understand the importance of generative AI-powered assistants in developers' daily work Enable Amazon Q Developer for IDEs and with AWS services to leverage code suggestions Customize Amazon Q Developer to align with organizational coding standards Utilize Amazon Q Developer for code explanation, transformation, and feature development Understand code references and scan for code security issues using Amazon Q Developer Accelerate building solutions and troubleshooting errors on AWS Who this book is for This book is for coders, software developers, application builders, data engineers, and technical resources using AWS services looking to leverage Amazon Q Developer's features to enhance productivity and accelerate business outcomes. Basic coding skills are needed to understand the concepts covered in this book.

Enterprise AI in the Cloud

Author : Rabi Jay
Publisher : John Wiley & Sons
Page : 763 pages
File Size : 26,90 MB
Release : 2023-12-20
Category : Computers
ISBN : 1394213069

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Embrace emerging AI trends and integrate your operations with cutting-edge solutions Enterprise AI in the Cloud: A Practical Guide to Deploying End-to-End Machine Learning and ChatGPT Solutions is an indispensable resource for professionals and companies who want to bring new AI technologies like generative AI, ChatGPT, and machine learning (ML) into their suite of cloud-based solutions. If you want to set up AI platforms in the cloud quickly and confidently and drive your business forward with the power of AI, this book is the ultimate go-to guide. The author shows you how to start an enterprise-wide AI transformation effort, taking you all the way through to implementation, with clearly defined processes, numerous examples, and hands-on exercises. You’ll also discover best practices on optimizing cloud infrastructure for scalability and automation. Enterprise AI in the Cloud helps you gain a solid understanding of: AI-First Strategy: Adopt a comprehensive approach to implementing corporate AI systems in the cloud and at scale, using an AI-First strategy to drive innovation State-of-the-Art Use Cases: Learn from emerging AI/ML use cases, such as ChatGPT, VR/AR, blockchain, metaverse, hyper-automation, generative AI, transformer models, Keras, TensorFlow in the cloud, and quantum machine learning Platform Scalability and MLOps (ML Operations): Select the ideal cloud platform and adopt best practices on optimizing cloud infrastructure for scalability and automation AWS, Azure, Google ML: Understand the machine learning lifecycle, from framing problems to deploying models and beyond, leveraging the full power of Azure, AWS, and Google Cloud platforms AI-Driven Innovation Excellence: Get practical advice on identifying potential use cases, developing a winning AI strategy and portfolio, and driving an innovation culture Ethical and Trustworthy AI Mastery: Implement Responsible AI by avoiding common risks while maintaining transparency and ethics Scaling AI Enterprise-Wide: Scale your AI implementation using Strategic Change Management, AI Maturity Models, AI Center of Excellence, and AI Operating Model Whether you're a beginner or an experienced AI or MLOps engineer, business or technology leader, or an AI student or enthusiast, this comprehensive resource empowers you to confidently build and use AI models in production, bridging the gap between proof-of-concept projects and real-world AI deployments. With over 300 review questions, 50 hands-on exercises, templates, and hundreds of best practice tips to guide you through every step of the way, this book is a must-read for anyone seeking to accelerate AI transformation across their enterprise.

Automate It with Zapier and Generative AI

Author : Kelly Goss
Publisher : Packt Publishing Ltd
Page : 706 pages
File Size : 11,28 MB
Release : 2023-08-25
Category : Computers
ISBN : 1803246626

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Strategize and create automated business workflows with Zapier, including AI-integrated functionalities such as the ChatGPT plugin and the OpenAI integration, to minimize repetitive tasks without using code Key Features Discover the newest Zapier features including OpenAI integration and the ChatGPT plugin Explore expert tips and real-life examples to connect 6000+ business apps and automate tasks with Zapier Learn how to manage your account effectively and troubleshoot problems with your Zaps Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionOrganizations experience significant issues with productivity when dealing with manual and repetitive tasks. Automate it with Zapier and Generative AI, second edition has been extensively revised to help you analyze your processes and identify repetitive tasks that can be automated between 6000+ cloud-based business applications. This book includes all Zapier’s newest features such as AI functionality using the ChatGPT plugin, drafts, reordering and duplicating steps and paths, subfolders and version history, as well as built-in apps such as Looping, Sub-Zap, Interfaces, Tables, and Transfer. The chapters also contain examples covering various use cases sourced from the Zapier user community. You'll learn how to implement automation in your organization along with key principles and terminology, and take the first steps toward using Zapier. As you advance, you'll learn how to use Zapier’s native functionality and all 27 built-in apps such as Filter, Paths, Formatter, Digest, and Scheduler to enable you to build multi-step Zaps. You’ll also discover how to manage your Zapier account effectively, as well as how to troubleshoot technical problems with your workflows, and use the OpenAI integration to automate AI tasks. By the end of this book, you'll be able to automate your manual and repetitive tasks using Zapier.What you will learn Think outside the box to simplify business workflows and solve productivity problems Strategize how to optimally structure and build your workflow automation in Zapier to prevent errors and excessive task usage Explore the latest built-in apps including Transfer, Interfaces, Tables, Looping, Sub-Zap, and the ChatGPT plugin Discover how to use AI-integrated apps and features with automation Create complex multi-step Zaps using logic, formatting, and calculations Effectively manage your account and troubleshoot problems with your Zaps Who this book is forThis book is for business owners, operations managers, and teams in micro, small, or medium-sized businesses looking at automating repetitive tasks and increasing their productivity using Zapier and AI-integrated features. Service providers offering digital process improvement, systemization, and automation services to their clients such as solutions architects, process consultants, business analysts, virtual assistants, CRM consultants, OBMs, bookkeepers and accountants will find this book extremely useful. Suitable for new and experienced Zapier users.

Building Machine Learning Powered Applications

Author : Emmanuel Ameisen
Publisher : "O'Reilly Media, Inc."
Page : 267 pages
File Size : 14,17 MB
Release : 2020-01-21
Category : Computers
ISBN : 1492045063

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Learn the skills necessary to design, build, and deploy applications powered by machine learning (ML). Through the course of this hands-on book, you’ll build an example ML-driven application from initial idea to deployed product. Data scientists, software engineers, and product managers—including experienced practitioners and novices alike—will learn the tools, best practices, and challenges involved in building a real-world ML application step by step. Author Emmanuel Ameisen, an experienced data scientist who led an AI education program, demonstrates practical ML concepts using code snippets, illustrations, screenshots, and interviews with industry leaders. Part I teaches you how to plan an ML application and measure success. Part II explains how to build a working ML model. Part III demonstrates ways to improve the model until it fulfills your original vision. Part IV covers deployment and monitoring strategies. This book will help you: Define your product goal and set up a machine learning problem Build your first end-to-end pipeline quickly and acquire an initial dataset Train and evaluate your ML models and address performance bottlenecks Deploy and monitor your models in a production environment

Generative AI Application Integration Patterns

Author : Juan Pablo Bustos
Publisher : Packt Publishing Ltd
Page : 219 pages
File Size : 32,44 MB
Release : 2024-09-05
Category : Computers
ISBN : 1835887619

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Unleash the transformative potential of GenAI with this comprehensive guide that serves as an indispensable roadmap for integrating large language models into real-world applications. Gain invaluable insights into identifying compelling use cases, leveraging state-of-the-art models effectively, deploying these models into your applications at scale, and navigating ethical considerations. Key Features Get familiar with the most important tools and concepts used in real scenarios to design GenAI apps Interact with GenAI models to tailor model behavior to minimize hallucinations Get acquainted with a variety of strategies and an easy to follow 4 step frameworks for integrating GenAI into applications Book Description Explore the transformative potential of GenAI in the application development lifecycle. Through concrete examples, you will go through the process of ideation and integration, understanding the tradeoffs and the decision points when integrating GenAI. With recent advances in models like Google Gemini, Anthropic Claude, DALL-E and GPT-4o, this timely resource will help you harness these technologies through proven design patterns. We then delve into the practical applications of GenAI, identifying common use cases and applying design patterns to address real-world challenges. From summarization and metadata extraction to intent classification and question answering, each chapter offers practical examples and blueprints for leveraging GenAI across diverse domains and tasks. You will learn how to fine-tune models for specific applications, progressing from basic prompting to sophisticated strategies such as retrieval augmented generation (RAG) and chain of thought. Additionally, we provide end-to-end guidance on operationalizing models, including data prep, training, deployment, and monitoring. We also focus on responsible and ethical development techniques for transparency, auditing, and governance as crucial design patterns. What you will learn Concepts of GenAI: pre-training, fine-tuning, prompt engineering, and RAG Framework for integrating AI: entry points, prompt pre-processing, inference, post-processing, and presentation Patterns for batch and real-time integration Code samples for metadata extraction, summarization, intent classification, question-answering with RAG, and more Ethical use: bias mitigation, data privacy, and monitoring Deployment and hosting options for GenAI models Who this book is for This book is not an introduction to AI/ML or Python. It offers practical guides for designing, building, and deploying GenAI applications in production. While all readers are welcome, those who benefit most include: Developer engineers with foundational tech knowledge Software architects seeking best practices and design patterns Professionals using ML for data science, research, etc., who want a deeper understanding of Generative AI Technical product managers with a software development background This concise focus ensures practical, actionable insights for experienced professionals