Llm Powered Application

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Building Llm Powered Applications

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Author : Valentina Alto
language : en
Publisher: Packt Publishing Ltd
Release Date : 2024-05-22

Building Llm Powered Applications written by Valentina Alto and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-05-22 with Computers categories.

Get hands-on with GPT 3.5, GPT 4, LangChain, Llama 2, Falcon LLM and more, to build LLM-powered sophisticated AI applications Get With Your Book: PDF Copy, AI Assistant, and Next-Gen Reader Free 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.

Llm Powered Application

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Author : Lou Jackson
language : en
Publisher: Independently Published
Release Date : 2024-06-23

Llm Powered Application written by Lou Jackson and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-06-23 with Computers categories.

LLM-Powered Applications: Building the Future with Language Large Language Models (LLMs) are revolutionizing the way we interact with machines. These AI models, trained on massive amounts of text data, can understand and generate human-like language, opening doors to a new era of intelligent applications. Written by an expert in the field of AI and language processing, this book provides a balanced and informative view of LLMs. You'll gain a solid understanding of their capabilities, limitations, and the ethical considerations surrounding their development. This comprehensive guide dives deep into the world of LLM-powered applications. You'll explore how LLMs are transforming various industries, from software development and content creation to education and customer service. What's Inside: 1. Demystifying LLMs: Understand how these complex models work and their potential to revolutionize various fields. 2. Practical Applications: Discover inspiring ideas and real-world use cases for LLM technology across diverse industries. 3. Building with LLMs: Learn the essential tools, libraries, and techniques to develop your own LLM-powered applications 4. The Future Landscape: Explore the exciting possibilities and potential challenges that lie ahead for LLM development. This book is ideal for anyone interested in the future of technology and language. Whether you're a developer, entrepreneur, business leader, or simply curious about AI, this guide will equip you with the knowledge to harness the power of LLMs. Don't get left behind in the LLM revolution. This book empowers you to be at the forefront of this technological wave, shaping the future of how we interact with language and information. Become an LLM pioneer! Grab your copy of "LLM-Powered Applications" today and unlock the potential of this transformative technology!

Building Ai Intensive Python Applications

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Author : Rachelle Palmer
language : en
Publisher: Packt Publishing Ltd
Release Date : 2024-09-06

Building Ai Intensive Python Applications written by Rachelle Palmer and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-09-06 with Computers categories.

Master retrieval-augmented generation architecture and fine-tune your AI stack, along with discovering real-world use cases and best practices to create powerful AI apps Key Features Get to grips with the fundamentals of LLMs, vector databases, and Python frameworks Implement effective retrieval-augmented generation strategies with MongoDB Atlas Optimize AI models for performance and accuracy with model compression and deployment optimization Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionThe era of generative AI is upon us, and this book serves as a roadmap to harness its full potential. With its help, you’ll learn the core components of the AI stack: large language models (LLMs), vector databases, and Python frameworks, and see how these technologies work together to create intelligent applications. The chapters will help you discover best practices for data preparation, model selection, and fine-tuning, and teach you advanced techniques such as retrieval-augmented generation (RAG) to overcome common challenges, such as hallucinations and data leakage. You’ll get a solid understanding of vector databases, implement effective vector search strategies, refine models for accuracy, and optimize performance to achieve impactful results. You’ll also identify and address AI failures to ensure your applications deliver reliable and valuable results. By evaluating and improving the output of LLMs, you’ll be able to enhance their performance and relevance. By the end of this book, you’ll be well-equipped to build sophisticated AI applications that deliver real-world value.What you will learn Understand the architecture and components of the generative AI stack Explore the role of vector databases in enhancing AI applications Master Python frameworks for AI development Implement Vector Search in AI applications Find out how to effectively evaluate LLM output Overcome common failures and challenges in AI development Who this book is for This book is for software engineers and developers looking to build intelligent applications using generative AI. While the book is suitable for beginners, a basic understanding of Python programming is required to make the most of it.

Developing Apps With Gpt 4 And Chatgpt

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Author : Olivier Caelen
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2024-07-10

Developing Apps With Gpt 4 And Chatgpt written by Olivier Caelen and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-07-10 with Computers categories.

This book provides an ideal guide for Python developers who want to learn how to build applications with large language models. Authors Olivier Caelen and Marie-Alice Blete cover the main features and benefits of GPT-4 and GPT-3.5 models and explain how they work. You'll also get a step-by-step guide for developing applications using the OpenAI Python library, including text generation, Q&A, and smart assistants. Written in clear and concise language, Developing Apps with GPT-4 and ChatGPT includes easy-to-follow examples to help you understand and apply the concepts to your projects. Python code examples are available in a GitHub repository, and the book includes a glossary of key terms. Ready to harness the power of large language models in your applications? This book is a must. You'll learn: Fundamentals and benefits of GPT-4 and GPT-3.5 models, including the main features and how they work How to integrate these models into Python-based applications, leveraging natural language processing capabilities and overcoming specific LLM-related challenges Examples of applications demonstrating the OpenAI API in Python for tasks including text generation, question answering, content summarization, classification, and more Advanced LLM topics such as prompt engineering, fine-tuning models for specific tasks, RAG, plug-ins, LangChain, LlamaIndex, GPTs, and assistants Olivier Caelen is a machine learning researcher at Worldline and teaches machine learning courses at the University of Brussels. Marie-Alice Blete, a software architect and data engineer in Worldline's R&D department, is interested in performance and latency issues associated with AI solutions.

Generative Ai Application Integration Patterns

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Author : Juan Pablo Bustos
language : en
Publisher: Packt Publishing Ltd
Release Date : 2024-09-05

Generative Ai Application Integration Patterns written by Juan Pablo Bustos and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-09-05 with Computers categories.

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

Demystifying Large Language Models

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Author : James Chen
language : en
Publisher: James Chen
Release Date : 2024-04-25

Demystifying Large Language Models written by James Chen and has been published by James Chen this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-04-25 with Computers categories.

This book is a comprehensive guide aiming to demystify the world of transformers -- the architecture that powers Large Language Models (LLMs) like GPT and BERT. From PyTorch basics and mathematical foundations to implementing a Transformer from scratch, you'll gain a deep understanding of the inner workings of these models. That's just the beginning. Get ready to dive into the realm of pre-training your own Transformer from scratch, unlocking the power of transfer learning to fine-tune LLMs for your specific use cases, exploring advanced techniques like PEFT (Prompting for Efficient Fine-Tuning) and LoRA (Low-Rank Adaptation) for fine-tuning, as well as RLHF (Reinforcement Learning with Human Feedback) for detoxifying LLMs to make them aligned with human values and ethical norms. Step into the deployment of LLMs, delivering these state-of-the-art language models into the real-world, whether integrating them into cloud platforms or optimizing them for edge devices, this section ensures you're equipped with the know-how to bring your AI solutions to life. Whether you're a seasoned AI practitioner, a data scientist, or a curious developer eager to advance your knowledge on the powerful LLMs, this book is your ultimate guide to mastering these cutting-edge models. By translating convoluted concepts into understandable explanations and offering a practical hands-on approach, this treasure trove of knowledge is invaluable to both aspiring beginners and seasoned professionals. Table of Contents 1. INTRODUCTION 1.1 What is AI, ML, DL, Generative AI and Large Language Model 1.2 Lifecycle of Large Language Models 1.3 Whom This Book Is For 1.4 How This Book Is Organized 1.5 Source Code and Resources 2. PYTORCH BASICS AND MATH FUNDAMENTALS 2.1 Tensor and Vector 2.2 Tensor and Matrix 2.3 Dot Product 2.4 Softmax 2.5 Cross Entropy 2.6 GPU Support 2.7 Linear Transformation 2.8 Embedding 2.9 Neural Network 2.10 Bigram and N-gram Models 2.11 Greedy, Random Sampling and Beam 2.12 Rank of Matrices 2.13 Singular Value Decomposition (SVD) 2.14 Conclusion 3. TRANSFORMER 3.1 Dataset and Tokenization 3.2 Embedding 3.3 Positional Encoding 3.4 Layer Normalization 3.5 Feed Forward 3.6 Scaled Dot-Product Attention 3.7 Mask 3.8 Multi-Head Attention 3.9 Encoder Layer and Encoder 3.10 Decoder Layer and Decoder 3.11 Transformer 3.12 Training 3.13 Inference 3.14 Conclusion 4. PRE-TRAINING 4.1 Machine Translation 4.2 Dataset and Tokenization 4.3 Load Data in Batch 4.4 Pre-Training nn.Transformer Model 4.5 Inference 4.6 Popular Large Language Models 4.7 Computational Resources 4.8 Prompt Engineering and In-context Learning (ICL) 4.9 Prompt Engineering on FLAN-T5 4.10 Pipelines 4.11 Conclusion 5. FINE-TUNING 5.1 Fine-Tuning 5.2 Parameter Efficient Fine-tuning (PEFT) 5.3 Low-Rank Adaptation (LoRA) 5.4 Adapter 5.5 Prompt Tuning 5.6 Evaluation 5.7 Reinforcement Learning 5.8 Reinforcement Learning Human Feedback (RLHF) 5.9 Implementation of RLHF 5.10 Conclusion 6. DEPLOYMENT OF LLMS 6.1 Challenges and Considerations 6.2 Pre-Deployment Optimization 6.3 Security and Privacy 6.4 Deployment Architectures 6.5 Scalability and Load Balancing 6.6 Compliance and Ethics Review 6.7 Model Versioning and Updates 6.8 LLM-Powered Applications 6.9 Vector Database 6.10 LangChain 6.11 Chatbot, Example of LLM-Powered Application 6.12 WebUI, Example of LLM-Power Application 6.13 Future Trends and Challenges 6.14 Conclusion REFERENCES ABOUT THE AUTHOR

Digital Warfare

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Author : Nadia Zasanska
language : en
Publisher: transcript Verlag
Release Date : 2025-07-27

Digital Warfare written by Nadia Zasanska and has been published by transcript Verlag this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-07-27 with Political Science categories.

Digital media and technologies remain unpredictable when we approach them as actors in armed conflicts. Artificial intelligence, drones, information leaks, hacking, propaganda and fakes become part of war reality. The contributors to this volume prompt us to focus on the virtual fronts of the Russo-Ukrainian War, examining the agency of an individual, community and society in the digitalized war reality. This collection illustrates how digital spaces empower society to stay resilient, resist Russia’s aggression and defend democratic values in times of adversity and severe trials.

An Ollama Crash Course In Building Smart Solutions

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Author : Alicia B Carpenter
language : en
Publisher: Independently Published
Release Date : 2025-05-04

An Ollama Crash Course In Building Smart Solutions written by Alicia B Carpenter and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-05-04 with Technology & Engineering categories.

Unlock the Future of App Development with Local LLMs! Are you ready to take your app development skills to the next level? Imagine building AI-powered solutions that are fast, secure, and customizable, all without relying on the cloud. With Local LLMs (Large Language Models), you can create smart apps that process data directly on the user's device, offering enhanced data privacy, offline functionality, and lightning-fast performance. In "An Ollama Crash Course In Building Smart Solutions: Local LLM-Powered App Development", you'll discover the secrets to developing LLM-powered apps that stand out in the crowded world of app development. From the basics of machine learning for developers to advanced LLM model integration, this book will equip you with the knowledge to build cutting-edge AI applications that are tailored for today's privacy-conscious, performance-driven world. You'll learn how to leverage Ollama and its powerful local language models to create everything from customer service bots to smart productivity apps. Master LLM app design and understand the nuances of optimizing apps for offline AI functionality, ensuring that your solutions are not only secure but also capable of handling real-world use cases with ease. Whether you're an experienced developer or a beginner eager to dive into the world of machine learning for mobile apps, this book will guide you through the essential concepts, techniques, and tools needed to build the next generation of intelligent, privacy-first applications. Take Control of Your App Development Journey Today! Ready to start building local LLM-powered solutions that can change the way users interact with technology? Download your copy now and get started on creating smarter, faster, and more secure apps that stand out in the digital landscape. Don't wait-empower yourself with the knowledge to build AI applications that prioritize privacy, speed, and innovation. Get your copy now and transform the way you develop apps!

Photovoltaics For Commercial Solar Power Applications

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Author : David Adler
language : en
Publisher:
Release Date : 1986

Photovoltaics For Commercial Solar Power Applications written by David Adler and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1986 with Technology & Engineering categories.

Prompt Engineering For Llms

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Author : John Berryman
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2024-11-04

Prompt Engineering For Llms written by John Berryman and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-11-04 with Computers categories.

Large language models (LLMs) are revolutionizing the world, promising to automate tasks and solve complex problems. A new generation of software applications are using these models as building blocks to unlock new potential in almost every domain, but reliably accessing these capabilities requires new skills. This book will teach you the art and science of prompt engineering-the key to unlocking the true potential of LLMs. Industry experts John Berryman and Albert Ziegler share how to communicate effectively with AI, transforming your ideas into a language model-friendly format. By learning both the philosophical foundation and practical techniques, you'll be equipped with the knowledge and confidence to build the next generation of LLM-powered applications. Understand LLM architecture and learn how to best interact with itDesign a complete prompt-crafting strategy for an applicationGather, triage, and present context elements to make an efficient promptMaster specific prompt-crafting techniques like few-shot learning, chain-of-thought prompting, and RAG