Vector Databases For Generative Ai Applications
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Vector Databases For Generative Ai Applications
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Author : Anand Vemula
language : en
Publisher: Independently Published
Release Date : 2024-05-03
Vector Databases For Generative Ai Applications written by Anand Vemula and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-05-03 with Computers categories.
"Vector Databases for Generative AI Applications" explores the intersection of two cutting-edge fields: vector databases and generative artificial intelligence (AI). The book provides a comprehensive overview of how vector databases, a specialized form of database optimized for vector similarity search, can enhance various generative AI applications. The first part of the book introduces the fundamentals of vector databases, including key concepts such as vector indexing, similarity search algorithms, and performance optimizations. Readers are guided through the architecture and functionality of vector databases, with a focus on how they differ from traditional relational databases and their suitability for handling high-dimensional data. In the second part, the book delves into the application of vector databases in generative AI. It explores how vector databases can be leveraged to store and retrieve large collections of high-dimensional vectors, which are prevalent in generative AI tasks such as natural language processing, computer vision, and recommender systems. Through real-world examples and case studies, the book demonstrates how vector databases can accelerate the training and inference processes of generative AI models by efficiently managing vector representations of data points. Moreover, the book addresses the challenges and considerations involved in integrating vector databases with generative AI frameworks and platforms. It discusses topics such as data preprocessing, indexing strategies, distributed computing, and scalability, providing practical guidance for architects and developers looking to deploy vector databases in their generative AI pipelines. Throughout the book, the authors highlight the synergies between vector databases and generative AI, showcasing how the combination of these technologies can enable breakthroughs in applications such as content generation, personalized recommendations, and data synthesis. By offering both theoretical insights and hands-on implementation techniques, "Vector Databases for Generative AI Applications" serves as a valuable resource for researchers, practitioners, and enthusiasts seeking to harness the power of vector databases to drive innovation in generative AI.
Vector Databases For Generative Ai Applications
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Author : Anand Vemula
language : en
Publisher: Anand Vemula
Release Date :
Vector Databases For Generative Ai Applications written by Anand Vemula and has been published by Anand Vemula this book supported file pdf, txt, epub, kindle and other format this book has been release on with Computers categories.
"Vector Databases for Generative AI Applications" explores the intersection of two cutting-edge fields: vector databases and generative artificial intelligence (AI). The book provides a comprehensive overview of how vector databases, a specialized form of database optimized for vector similarity search, can enhance various generative AI applications. The first part of the book introduces the fundamentals of vector databases, including key concepts such as vector indexing, similarity search algorithms, and performance optimizations. Readers are guided through the architecture and functionality of vector databases, with a focus on how they differ from traditional relational databases and their suitability for handling high-dimensional data. In the second part, the book delves into the application of vector databases in generative AI. It explores how vector databases can be leveraged to store and retrieve large collections of high-dimensional vectors, which are prevalent in generative AI tasks such as natural language processing, computer vision, and recommender systems. Through real-world examples and case studies, the book demonstrates how vector databases can accelerate the training and inference processes of generative AI models by efficiently managing vector representations of data points. Moreover, the book addresses the challenges and considerations involved in integrating vector databases with generative AI frameworks and platforms. It discusses topics such as data preprocessing, indexing strategies, distributed computing, and scalability, providing practical guidance for architects and developers looking to deploy vector databases in their generative AI pipelines. Throughout the book, the authors highlight the synergies between vector databases and generative AI, showcasing how the combination of these technologies can enable breakthroughs in applications such as content generation, personalized recommendations, and data synthesis. By offering both theoretical insights and hands-on implementation techniques, "Vector Databases for Generative AI Applications" serves as a valuable resource for researchers, practitioners, and enthusiasts seeking to harness the power of vector databases to drive innovation in generative AI.
Building Generative Ai Applications With Open Source Libraries
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Author : Srikannan Balakrishnan
language : en
Publisher: BPB Publications
Release Date : 2025-03-27
Building Generative Ai Applications With Open Source Libraries written by Srikannan Balakrishnan and has been published by BPB Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-03-27 with Computers categories.
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
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
Building Conversational Generative Ai Apps With Langchain And Gpt
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Author : Mugesh S
language : en
Publisher: Orange Education Pvt Ltd
Release Date : 2025-06-04
Building Conversational Generative Ai Apps With Langchain And Gpt written by Mugesh S and has been published by Orange Education Pvt Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-06-04 with Computers categories.
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
Generative Ai For Software Engineers The Journey Begins
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Author : Naresh Dulam
language : en
Publisher: Libertatem Media Private Limited
Release Date : 2023-07-23
Generative Ai For Software Engineers The Journey Begins written by Naresh Dulam and has been published by Libertatem Media Private Limited this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-07-23 with Computers categories.
This book assists software engineers as they explore the realm of Artificial Intelligence (AI), providing essential tools and techniques for creating new AI-powered applications or adding AI functionalities to their current projects. Significant advancements in AI and machine learning (ML) frameworks have allowed software engineers to easily integrate intelligent capabilities into their products or projects in the last ten years. The introduction of ChatGPT in late 2022 brought Generative AI into the spotlight. Although abundant information is available online, software engineers need help finding a clear entry point like 101 to learn fundamentals. This guide simplifies the core concepts, gradually addressing more advanced topics to enable you to create practical, production-ready AI solutions with concrete code examples. Note: This book simplifies complex concepts by applying abstractions for software engineers to grasp the basics of Generative AI.
Building Generative Ai Services With Fastapi
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Author : Alireza Parandeh
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2025-04-15
Building Generative Ai Services With Fastapi written by Alireza Parandeh 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 2025-04-15 with Computers categories.
Ready to build production-grade applications with generative AI? This practical guide takes you through designing and deploying AI services using the FastAPI web framework. Learn how to integrate models that process text, images, audio, and video while seamlessly interacting with databases, filesystems, websites, and APIs. Whether you're a web developer, data scientist, or DevOps engineer, this book equips you with the tools to build scalable, real-time AI applications. Author Alireza Parandeh provides clear explanations and hands-on examples covering authentication, concurrency, caching, and retrieval-augmented generation (RAG) with vector databases. You'll also explore best practices for testing AI outputs, optimizing performance, and securing microservices. With containerized deployment using Docker, you'll be ready to launch AI-powered applications confidently in the cloud. Build generative AI services that interact with databases, filesystems, websites, and APIs Manage concurrency in AI workloads and handle long-running tasks Stream AI-generated outputs in real time via WebSocket and server-sent events Secure services with authentication, content filtering, throttling, and rate limiting Optimize AI performance with caching, batch processing, and fine-tuning techniques Visit the Book's Website.
Generative Ai On Aws
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Author : Chris Fregly
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2023-11-13
Generative Ai On Aws written by Chris Fregly 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 2023-11-13 with Computers categories.
Companies today are moving rapidly to integrate generative AI into their products and services. But there's a great deal of hype (and misunderstanding) about the impact and promise of this technology. With this book, Chris Fregly, Antje Barth, and Shelbee Eigenbrode from AWS help CTOs, ML practitioners, application developers, business analysts, data engineers, and data scientists find practical ways to use this exciting new technology. You'll learn the generative AI project life cycle including use case definition, model selection, model fine-tuning, retrieval-augmented generation, reinforcement learning from human feedback, and model quantization, optimization, and deployment. And you'll explore different types of models including large language models (LLMs) and multimodal models such as Stable Diffusion for generating images and Flamingo/IDEFICS for answering questions about images. Apply generative AI to your business use cases Determine which generative AI models are best suited to your task Perform prompt engineering and in-context learning Fine-tune generative AI models on your datasets with low-rank adaptation (LoRA) Align generative AI models to human values with reinforcement learning from human feedback (RLHF) Augment your model with retrieval-augmented generation (RAG) Explore libraries such as LangChain and ReAct to develop agents and actions Build generative AI applications with Amazon Bedrock
Building Generative Ai Agents
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Author : Tom Taulli
language : en
Publisher: Springer Nature
Release Date : 2025-06-15
Building Generative Ai Agents written by Tom Taulli and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-06-15 with Computers categories.
The dawn of AI agents is upon us. Tech visionaries like Bill Gates, Andrew Ng, and Vinod Khosla have highlighted the monumental potential of this powerful technology. This book will provide the knowledge and tools necessary to build generative AI agents using the most popular frameworks, such as AutoGen, LangChain, LangGraph, CrewAI, and Haystack. Recent breakthroughs in large language models have opened up unprecedented possibilities. After years of gradual progress in machine learning and deep learning, we are now witnessing novel approaches capable of understanding, reasoning, and generating content in ways that promise to revolutionize nearly every industry. This platform shift is as significant as the advent of mainframes, PCs, cloud computing, mobile technology, and social media. It’s why the world’s largest technology companies – like Microsoft, Apple, Google, and Meta – are making enormous investments in this category. While chatbots like ChatGPT, Claude, and Gemini have demonstrated remarkable potential, the years ahead will see the rise of generative AI agents capable of executing complex tasks on behalf of users. These agents already exhibit capabilities such as running test suites, searching the web for documentation, writing software, answering questions based on vast organized information, and performing intricate web-based tasks across multiple domains. They can autonomously investigate cybersecurity incidents and address complex customer support needs. By integrating skills, knowledge bases, planning frameworks, memory, and feedback loops, these systems can handle many tasks and improve over time. Building Generative AI Agents serves as a high-quality guide for developers to understand when and where AI agents can be useful, their advantages and disadvantages, and practical advice on designing, building, deploying, and monitoring them. What You Will Learn The foundational concepts, capabilities, and potential of AI agents. Recent innovations in large language models that have enabled the development of AI agents. How to build AI agents for launching a product, creating a financial plan, handling customer service, and using Retrieval Augmented Generation (RAG). Essential frameworks for building generative AI agents, including AutoGen, LangChain, LangGraph, CrewAI, and Haystack. Step-by-step guidance on designing, building, and deploying AI agents. Insights into the future of AI agents and their potential impact on various industries. Who This Book Is For Experienced software developers
Ai Unraveled Master Gpt X Gemini Generative Ai Llms Prompt Engineering A Simplified Guide For Everyday Users
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Author : Etienne Noumen
language : en
Publisher: Etienne Noumen
Release Date :
Ai Unraveled Master Gpt X Gemini Generative Ai Llms Prompt Engineering A Simplified Guide For Everyday Users written by Etienne Noumen and has been published by Etienne Noumen this book supported file pdf, txt, epub, kindle and other format this book has been release on with Computers categories.
Dive into the revolutionary world of Artificial Intelligence with 'AI Unraveled: Demystifying Frequently Asked Questions on Artificial Intelligence'. This comprehensive guide is your portal to understanding AI's most intricate concepts and cutting-edge developments. Whether you're a curious beginner or an AI enthusiast, this book is tailored to unveil the complexities of AI in a simple, accessible manner. What's Inside: Fundamental AI Concepts: Journey through the basics of AI, machine learning, deep learning, and neural networks. AI in Action: Explore how AI is reshaping industries and society, diving into its applications in computer vision, natural language processing, and beyond. Ethical AI: Tackle critical issues like AI ethics and bias, understanding the moral implications of AI advancements. Industry Insights: Gain insights into how AI is revolutionizing industries and impacting our daily lives. The Future of AI: Forecast the exciting possibilities and challenges that lie ahead in the AI landscape. Special Focus on Generative AI & LLMs: Latest AI Trends: Stay updated with the latest in AI, including ChatGPT, Google Gemini, GPT-x, Gemini, and more. Interactive Quizzes: Test your knowledge with engaging quizzes on Generative AI and Large Language Models (LLMs). Practical Guides: Master GPT-x with a simplified guide, delve into advanced prompt engineering, and explore the nuances of temperature settings in AI. Real-World Applications: Learn how to leverage AI in various sectors, from healthcare to cybersecurity, and even explore its potential in areas like aging research and brain implants. For the AI Enthusiast: Prompt Engineering: Uncover secrets to crafting effective prompts for ChatGPT/Google Gemini. AI Career Insights: Explore lucrative career paths in AI, including roles like AI Prompt Engineers. AI Investment Guide: Navigate the world of AI stocks and investment opportunities. For AI Developers: How to develop AI-powered apps effectively? Generative AI Technology Stack Overview – A Comprehensive Guide Your Guide to Navigating AI: Do-It-Yourself Tutorials: From building custom ChatGPT applications to running LLMs locally, this book offers step-by-step guides. AI for Everyday Use: Learn how AI can assist in weight loss, social media, and more. 'AI Unraveled' is more than just a book; it's a resource for anyone looking to grasp the complexities of AI and its impact on our world. Get ready to embark on an enlightening journey into the realm of Artificial Intelligence!" More Topics Covered: Artificial Intelligence, Machine Learning, Deep Learning, NLP, AI Ethics, Robotics, Cognitive Computing, ChatGPT, OpenAI, Google Gemini, Generative AI, LLMs, AI in Healthcare, AI Investments, and much more. GPT-x vs Gemini: Pros and Cons Mastering GPT-x: Simplified Guide For everyday Users Advance Prompt Engineering Techniques: [Single Prompt Technique, Zero-Shot and Few-Shot, Zero-Shot and Few-Shot, Generated Knowledge Prompting, EmotionPrompt, Chain of Density (CoD), Chain of Thought (CoT), Validation of LLMs Responses, Chain of Verification (CoVe), Agents - The Frontier of Prompt Engineering, Prompt Chaining vs Agents, Tree of Thought (ToT), ReAct (Reasoning + Act), ReWOO (Reasoning WithOut Observation), Reflexion and Self-Reflection, Guardrails, RAIL (Reliable AI Markup Language), Guardrails AI, NeMo Guardrails] Understanding Temperature in GPT-x: A Guide to AI Probability and Creativity Retrieval-Augmented Generation (RAG) model in the context of Large Language Models (LLMs) like GPT-x Prompt Ideas for ChatGPT/Google Gemini How to Run ChatGPT-like LLMs Locally on Your Computer in 3 Easy Steps ChatGPT Custom Instructions Settings for Power Users Examples of bad and good ChatGPT prompts Top 5 Beginner Mistakes in Prompt Engineering Use ChatGPT like a PRO Prompt template for learning any skill Prompt Engineering for ChatGPT The Future of LLMs in Search What is Explainable AI? Which industries are meant for XAI? ChatGPT Best Tips, Cheat Sheet LLMs Utilize Vector DB for Data Storage The Limitation Technique in Prompt Responses Use ChatGPT to learn new subjects Prompts to proofread anything How to Create a Specialized LLM That Understands Your Custom Data Topics: Artificial Intelligence Education Machine Learning Deep Learning Reinforcement Learning Neural networks Data science AI ethics Deepmind Robotics Natural language processing Intelligent agents Cognitive computing AI Apps AI impact AI Tech ChatGPT Open AI Safe AI Generative AI Discriminative AI Sam Altman Google Gemini NVDIA Large Language Models (LLMs) PALM GPT Explainable AI GPUs AI Stocks AI Podcast Q* AI Certification AI Quiz RAG Context Windows Tokens Ai Agents How to access the AI Unraveled: Djamgatech: https://djamgatech.com/product/ai-unraveled-demystifying-frequently-asked-questions-on-artificial-intelligence-paperback-print-book Google eBook: https://play.google.com/store/books/details?id=oySuEAAAQBAJ Apple eBook: https://books.apple.com/us/book/id6445730691 Etsy: https://www.etsy.com/ca/listing/1617575707/ai-unraveled-demystifying-frequently Audible at Amazon : https://www.audible.com/pd/B0BXMJ7FK5/?source_code=AUDFPWS0223189MWT-BK-ACX0-343437&ref=acx_bty_BK_ACX0_343437_rh_us (Use Promo code: 37YT3B5UYUYZW) Audiobook at Google: https://play.google.com/store/audiobooks/details?id=AQAAAEAihFTEZM