LLM Powered Application
LLM Powered Application

Author: Lou Jackson

Publisher: Independently Published

Published: 2024-06-23

Total Pages: 0

ISBN-13:

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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 LLM Powered Applications
Building LLM Powered Applications

Author: Valentina Alto

Publisher: Packt Publishing Ltd

Published: 2024-05-22

Total Pages: 343

ISBN-13: 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.

Building LLM Applications with Python: A Practical Guide
Building LLM Applications with Python: A Practical Guide

Author: Anand Vemula

Publisher: Anand Vemula

Published:

Total Pages: 42

ISBN-13:

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This book equips you to harness the remarkable capabilities of Large Language Models (LLMs) using Python. Part I unveils the world of LLMs. You'll delve into their inner workings, explore different LLM types, and discover their exciting applications in various fields. Part II dives into the practical side of things. We'll guide you through setting up your Python environment and interacting with LLMs. Learn to craft effective prompts to get the most out of LLMs and understand the different response formats they can generate. Part III gets you building! We'll explore how to leverage LLMs for creative text generation, from poems and scripts to code snippets. Craft effective question-answering systems and build engaging chatbots – the possibilities are endless! Part IV empowers you to maintain and improve your LLM creations. We'll delve into debugging techniques to identify and resolve issues. Learn to track performance and implement optimizations to ensure your LLM applications run smoothly. This book doesn't shy away from the bigger picture. The final chapter explores the ethical considerations of LLMs, addressing bias and promoting responsible use of this powerful technology. By the end of this journey, you'll be equipped to unlock the potential of LLMs with Python and contribute to a future brimming with exciting possibilities.

The Langchain And Llm Evolution
The Langchain And Llm Evolution

Author: Ronald C Sheffield

Publisher: Independently Published

Published: 2023-10-24

Total Pages: 0

ISBN-13:

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Generative AI-powered programming language, LangChain, is an innovative platform that empowers developers to build applications fueled by large language models (LLMs) such as GPT-3 and GPT-4. With its user-friendly interface for writing prompts and generating content, it opens the door to creative possibilities in the realm of technology. Brief Overview This book serves as your comprehensive guide to LangChain and LLMs, catering to developers of all skill levels. It takes you on a journey from the fundamentals to advanced concepts, offering a step-by-step approach to creating contents/write ups harnessing the power of LLMs. Picture a world where you can breathe life into writings using the magic of human language. Thanks to LangChain and LLMs, that world is now a reality. LangChain is your potent ally in crafting applications that generate text, translate languages, provide answers, and more. This book is your portal to mastering LangChain and LLMs, equipping you with the knowledge and skills needed to embark on your own journey of creating LLM-powered applications. What you will learn? The book delves into an array of topics, including: - Unveiling the essence of LangChain and its mechanics - Deciphering the inner workings of LLMs - Leveraging LangChain to generate text, translate languages, and tackle questions - Crafting LLM-powered text applications using LangChain - Adhering to best practices in working with LangChain and LLMs Who this book is meant for ? Whether you're a novice or a seasoned developer, if you aspire to use LangChain and LLMs to craft LLM-powered applications, this book is designed with you in mind. Position yourself as a trailblazer in the future of application development by mastering LangChain and LLMs today! Embark on your journey with LangChain and LLMs today, and begin forging the future of application development!

Building Large Language Model(LLM) Applications
Building Large Language Model(LLM) Applications

Author: Anand Vemula

Publisher: Independently Published

Published: 2024-05-24

Total Pages: 0

ISBN-13:

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"Building LLM Apps" is a comprehensive guide that equips readers with the knowledge and practical skills needed to develop applications utilizing large language models (LLMs). The book covers various aspects of LLM application development, starting from understanding the fundamentals of LLMs to deploying scalable and efficient solutions. Beginning with an introduction to LLMs and their importance in modern applications, the book explores the history, key concepts, and popular architectures like GPT and BERT. Readers learn how to set up their development environment, including hardware and software requirements, installing necessary tools and libraries, and leveraging cloud services for efficient development and deployment. Data preparation is essential for training LLMs, and the book provides insights into gathering and cleaning data, annotating and labeling data, and handling imbalanced data to ensure high-quality training datasets. Training large language models involves understanding training basics, best practices, distributed training techniques, and fine-tuning pre-trained models for specific tasks. Developing LLM applications requires designing user interfaces, integrating LLMs into existing systems, and building interactive features such as chatbots, text generation, sentiment analysis, named entity recognition, and machine translation. Advanced LLM techniques like prompt engineering, transfer learning, multi-task learning, and zero-shot learning are explored to enhance model capabilities. Deployment and scalability strategies are discussed to ensure smooth deployment of LLM applications while managing costs effectively. Security and ethics in LLM apps are addressed, covering bias detection, fairness, privacy, security, and ethical considerations to build responsible AI solutions. Real-world case studies illustrate the practical applications of LLMs in various domains, including customer service, healthcare, and finance. Troubleshooting and optimization techniques help readers address common issues and optimize model performance. Looking towards the future, the book highlights emerging trends and developments in LLM technology, emphasizing the importance of staying updated with advancements and adhering to ethical AI practices. "Building LLM Apps" serves as a comprehensive resource for developers, data scientists, and business professionals seeking to harness the power of large language models in their applications.

AgentScope A Guide to Building Multi-Agent LLM Applications
AgentScope A Guide to Building Multi-Agent LLM Applications

Author: StoryBuddiesPlay

Publisher: StoryBuddiesPlay

Published: 2024-05-14

Total Pages: 99

ISBN-13:

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Unleash the power of collaboration with AgentScope, a comprehensive platform designed to streamline the development of multi-agent Large Language Model (LLM) applications. This in-depth guide equips you with everything you need to know to leverage AgentScope's functionalities and build intelligent, scalable AI systems. Embrace the Future of AI: Multi-Agent Collaboration Made Easy AgentScope empowers you to construct a team of specialized LLMs, each with its own strengths and expertise. Imagine a system where one agent analyzes customer reviews for sentiment, another identifies key themes, and a third generates a comprehensive report – all working together seamlessly. This is the power of multi-agent LLMs, and AgentScope simplifies the process of bringing it to life. Dive Deep into AgentScope: From Agent Definition to Orchestrated Workflows This comprehensive guide takes you on a journey through the functionalities of AgentScope. Learn how to define and configure your agents, specifying their roles, LLM models, and communication protocols. Explore how to orchestrate tasks, ensuring a smooth workflow where subtasks are completed in the correct order and dependencies are managed effectively. Conquer Challenges: Error Handling, Security, and Explainability The guide doesn't shy away from the real-world considerations of multi-agent systems. Address potential errors and exceptions with AgentScope's robust error handling mechanisms. Safeguard your LLM application with built-in security features like authentication and data encryption. Foster trust and transparency by incorporating Explainable AI (XAI) techniques to understand the decision-making processes within your multi-agent system. Scale to New Heights: Optimizing Performance for Large Tasks As your LLM application tackles more complex tasks and works with ever-growing datasets, AgentScope provides the tools you need to maintain optimal performance. Discover strategies for resource allocation, communication optimization, and utilizing scalable LLM architectures. Employ monitoring and analytics to identify bottlenecks and ensure your multi-agent system continues to function efficiently. A Glimpse into the Future: Pioneering Applications with AgentScope Look ahead and explore the exciting potential of multi-agent LLM systems. Imagine AI-powered scientific discovery, personalized education, intelligent content creation, and advanced conversational AI for businesses – these are just a few possibilities on the horizon. AgentScope equips you to be a part of this revolution, empowering you to build groundbreaking applications that leverage the power of collaborative intelligence. Start Building Today: Unleash the Potential of Multi-Agent LLMs with AgentScope This guide provides a roadmap for your journey into the world of multi-agent LLM development with AgentScope. With its user-friendly interface, comprehensive documentation, and expansive capabilities, AgentScope makes complex AI development accessible. So, what are you waiting for? Start building the future of AI today!

Optimizing LLM Applications
Optimizing LLM Applications

Author: George Anvil

Publisher: Independently Published

Published: 2023-09-06

Total Pages: 0

ISBN-13:

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Master the Secrets to Optimizing LLM Applications for Speed and Efficiency LLMs are the brains of AI-powered products. They can understand language, power chatbots, and translate languages. But in the real world, they can be slow and inefficient. This book shows you how to make LLMs perform better. Learn how to make LLMs perform with lightning speed and unbeatable efficiency Discover the latest techniques and strategies for parallelization, memory management, hardware acceleration, and more Gain hands-on experience with real-world use cases, from chatbots to language translation Who is this book for? Developers and data scientists who want to optimize LLM applications Anyone who wants to learn how to make LLMs perform faster and more efficiently What's inside? An introduction to the basics of LLMs A comprehensive overview of the latest optimization techniques Real-world use cases of LLM optimization Hands-on exercises to help you learn by doing Why should you buy this book? This is the most comprehensive guide to optimizing LLM applications available. It covers everything you need to know to get started with LLM optimization, from the basics to advanced topics. The book is packed with practical examples and exercises that will help you learn by doing. The author is an expert in the field of LLM optimization and has a proven track record of teaching others. Order your copy today and start optimizing your LLM applications

Generative AI Application Integration Patterns
Generative AI Application Integration Patterns

Author: Juan Pablo Bustos

Publisher: Packt Publishing Ltd

Published: 2024-09-05

Total Pages: 219

ISBN-13: 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

Developing Apps with GPT-4 and ChatGPT
Developing Apps with GPT-4 and ChatGPT

Author: Olivier Caelen

Publisher: "O'Reilly Media, Inc."

Published: 2024-07-10

Total Pages: 273

ISBN-13: 1098168070

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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.