Building Generative Ai Services With Fastapi
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Building Generative Ai Services With Fastapi
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Author : Ali Parandeh
language : en
Publisher: O'Reilly Media
Release Date : 2025-05-31
Building Generative Ai Services With Fastapi written by Ali Parandeh and has been published by O'Reilly Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-05-31 with Computers categories.
Ready to build applications using generative AI? This practical book outlines the process necessary to design and build production grade AI services with a FastAPI web server that communicate seamlessly with databases, payment systems, and external APIs. You'll learn how to develop autonomous generative AI agents that stream outputs in real-time and interact with other models. Web developers, data scientists, and DevOps engineers will learn to implement end-to-end production-ready services that leverage generative AI. You'll learn design patterns to manage software complexity, implement FastAPI lifespan for AI model integration, handle long-running generative tasks, perform content filtering, cache outputs, implement retrieval augmented generation (RAG) with a vector database, implement usage/cost monitoring and tracking, protect services with your own authentication and authorization mechanisms, and effectively control stream outputs directly from GenAI models. You'll explore efficient testing methods for AI outputs, validation against databases, and deployment patterns using Docker for robust microservices in the cloud. Build generative services that interact with databases, external APIs, and more Learn how to load AI models into a FastAPI lifecycle memory Monitor and log model requests and responses within services Use authentication and authorization patterns hooked with generative models Handle and cache long-running inference tasks Stream model outputs via streaming events and WebSockets into browsers or files Automate the retraining process of generative models by exposing event-driven endpoints Ali Parandeh is a Chartered Engineer with the UK Engineering Council and a Microsoft and Google certified developer, data engineer, and data scientist.
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.
Fastapi For Generative Ai
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Author : Drake Duncan
language : en
Publisher: Independently Published
Release Date : 2025-06-08
Fastapi For Generative Ai written by Drake Duncan and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-06-08 with Computers categories.
FastAPI for Generative AI: Build and Deploy Scalable AI Applications with Python Unlock the power of FastAPI, Python, and Generative AI to build real-world, scalable applications that deliver blazing-fast performance and intelligent results. Whether you're integrating LLMs, diffusion models, or deploying AI APIs to production, this comprehensive guide walks you through every step with clear code, best practices, and hands-on projects. This is the definitive guide for developers, machine learning engineers, and backend architects building AI-powered web services using FastAPI. What You'll Learn Build RESTful and WebSocket-based APIs optimized for AI models Serve text-generation and image-generation models using FastAPI and Python Handle asynchronous processing, background tasks, and streaming outputs Secure endpoints with OAuth2, JWT tokens, and role-based access control (RBAC) Use Docker, GitHub Actions, and Render/Fly.io for full CI/CD deployments Integrate with Hugging Face Transformers, Diffusers, and modern AI libraries Develop a complete multi-model chat and image web app with frontend integration 1. Build Scalable AI APIs with FastAPI and Python Learn how to structure high-performance endpoints for machine learning workloads using FastAPI's async architecture. 2. Serve Generative Models Like GPT and Stable Diffusion Deploy language and image models using Hugging Face libraries, optimized for real-world inference. 3. Stream Responses with WebSockets and Server-Sent Events Deliver token-by-token LLM responses and real-time image generation feedback using FastAPI's async capabilities. 4. Secure Production-Grade AI Endpoints Implement authentication, rate limiting, and logging for mission-critical AI applications. 5. Deploy Your AI App with Docker, CI/CD, and Cloud Platforms Use containerization and GitHub Actions to launch to Render, Fly.io, or AWS. 6. Integrate Frontend Interfaces Using Streamlit or React Connect user-friendly frontends to your AI backend for real-time interaction and demo-ready delivery. 7. Real-World Project: Generative AI Chat + Image App Follow a complete walkthrough of building a multi-modal generative AI app, from architecture to deployment. Who This Book Is For Backend developers building intelligent APIs AI engineers deploying LLMs or diffusion models in production Python developers exploring modern web frameworks MLOps professionals scaling generative AI systems Teams building AI SaaS platforms, agentic tools, or custom inference endpoints Unlike generic AI or FastAPI books, FastAPI for Generative AI focuses specifically on real-time generative workloads, delivering both depth and practicality. You'll not only learn how to serve models-you'll learn how to build robust, deployable products around them.
Generative Ai With Langchain
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Author : Ben Auffarth
language : en
Publisher: Packt Publishing Ltd
Release Date : 2023-12-22
Generative Ai With Langchain written by Ben Auffarth 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 2023-12-22 with Computers categories.
2024 Edition – Get to grips with the LangChain framework to develop production-ready applications, including agents and personal assistants. The 2024 edition features updated code examples and an improved GitHub repository. Get With Your Book: PDF Copy, AI Assistant, and Next-Gen Reader Free Key Features Learn how to leverage LangChain to work around LLMs’ inherent weaknesses Delve into LLMs with LangChain and explore their fundamentals, ethical dimensions, and application challenges Get better at using ChatGPT and GPT models, from heuristics and training to scalable deployment, empowering you to transform ideas into reality Book DescriptionChatGPT and the GPT models by OpenAI have brought about a revolution not only in how we write and research but also in how we can process information. This book discusses the functioning, capabilities, and limitations of LLMs underlying chat systems, including ChatGPT and Gemini. It demonstrates, in a series of practical examples, how to use the LangChain framework to build production-ready and responsive LLM applications for tasks ranging from customer support to software development assistance and data analysis – illustrating the expansive utility of LLMs in real-world applications. Unlock the full potential of LLMs within your projects as you navigate through guidance on fine-tuning, prompt engineering, and best practices for deployment and monitoring in production environments. Whether you're building creative writing tools, developing sophisticated chatbots, or crafting cutting-edge software development aids, this book will be your roadmap to mastering the transformative power of generative AI with confidence and creativity.What you will learn Create LLM apps with LangChain, like question-answering systems and chatbots Understand transformer models and attention mechanisms Automate data analysis and visualization using pandas and Python Grasp prompt engineering to improve performance Fine-tune LLMs and get to know the tools to unleash their power Deploy LLMs as a service with LangChain and apply evaluation strategies Privately interact with documents using open-source LLMs to prevent data leaks Who this book is for The book is for developers, researchers, and anyone interested in learning more about LangChain. Whether you are a beginner or an experienced developer, this book will serve as a valuable resource if you want to get the most out of LLMs using LangChain. Basic knowledge of Python is a prerequisite, while prior exposure to machine learning will help you follow along more easily.
Generative Ai Foundations In Python
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Author : Carlos Rodriguez
language : en
Publisher: Packt Publishing Ltd
Release Date : 2024-07-26
Generative Ai Foundations In Python written by Carlos Rodriguez 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 2024-07-26 with Computers categories.
Begin your generative AI journey with Python as you explore large language models, understand responsible generative AI practices, and apply your knowledge to real-world applications through guided tutorials Key Features Gain expertise in prompt engineering, LLM fine-tuning, and domain adaptation Use transformers-based LLMs and diffusion models to implement AI applications Discover strategies to optimize model performance, address ethical considerations, and build trust in AI systems Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionThe intricacies and breadth of generative AI (GenAI) and large language models can sometimes eclipse their practical application. It is pivotal to understand the foundational concepts needed to implement generative AI. This guide explains the core concepts behind -of-the-art generative models by combining theory and hands-on application. Generative AI Foundations in Python begins by laying a foundational understanding, presenting the fundamentals of generative LLMs and their historical evolution, while also setting the stage for deeper exploration. You’ll also understand how to apply generative LLMs in real-world applications. The book cuts through the complexity and offers actionable guidance on deploying and fine-tuning pre-trained language models with Python. Later, you’ll delve into topics such as task-specific fine-tuning, domain adaptation, prompt engineering, quantitative evaluation, and responsible AI, focusing on how to effectively and responsibly use generative LLMs. By the end of this book, you’ll be well-versed in applying generative AI capabilities to real-world problems, confidently navigating its enormous potential ethically and responsibly.What you will learn Discover the fundamentals of GenAI and its foundations in NLP Dissect foundational generative architectures including GANs, transformers, and diffusion models Find out how to fine-tune LLMs for specific NLP tasks Understand transfer learning and fine-tuning to facilitate domain adaptation, including fields such as finance Explore prompt engineering, including in-context learning, templatization, and rationalization through chain-of-thought and RAG Implement responsible practices with generative LLMs to minimize bias, toxicity, and other harmful outputs Who this book is for This book is for developers, data scientists, and machine learning engineers embarking on projects driven by generative AI. A general understanding of machine learning and deep learning, as well as some proficiency with Python, is expected.
Build Financial Software With Generative Ai From Scratch
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Author : Chris Kardell
language : en
Publisher: Simon and Schuster
Release Date : 2025-06-24
Build Financial Software With Generative Ai From Scratch written by Chris Kardell and has been published by Simon and Schuster this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-06-24 with Computers categories.
Build working and regulation-compliant financial software—from scratch! The software used by banks, trading firms, and other financial services has special requirements at every level, from securing the UI to making sure backend services comply with a host of regulations. Build Financial Software with Generative AI (From Scratch) shows you how to deliver full stack financial services software—and how generative AI can make you even more productive. In Build Financial Software with Generative AI (From Scratch) you will: • Explore the core concepts of FinTech • Speed development with generative AI tools • Develop and deploy containerized services • Create and document APIs • Effectively visualize your data In Build Financial Software with Generative AI (From Scratch) you’ll build working software for processing Automated Clearing House (ACH) files, a cornerstone technology of banking that moves trillions of dollars every year. You’ll work with generative AI technology throughout the full stack application, including researching the tech for your application, spinning up a bare bone starting project, answering domain questions, clarifying functionality, and troubleshooting. Along the way, you’ll learn what sets FinTech projects apart from normal web apps. Purchase of the print book includes a free eBook in PDF and ePub formats from Manning Publications. About the technology The financial industry is awash with regulatory and compliance challenges, complex technical requirements, and stringent security demands. There’s a huge demand for developers who can create financial services software and this book will get you started. You’ll build your own FinTech app from the ground up—with a big productivity boost from Generative AI! About the book Build Financial Software with Generative AI (From Scratch) guides you through modernizing a full-stack Automated Clearing House (ACH) application, layer-by-layer. You’ll start with a quick review of FinTech basics and an introduction to GenAI tools. Then, you’ll develop a data visualization dashboard with React, containerize components with Docker, create and refine APIs, implement backend processing, and even design a custom database. Throughout, you’ll see how AI tools aid with coding, testing, research, security, documentation, and even Agile practices. What's inside • Learn the core concepts of FinTech development • Create and document APIs using Generative AI • Build an awesome data visualization dashboard About the reader Examples are in Python. No experience with generative AI or financial services required. About the author Christopher Kardell and Mark Brouwer have both spent more than 20 years working in the Fintech industry. Table of Contents Part 1 1 Exploring FinTech and generative AI 2 Parsing payments Part 2 3 Getting started with Docker 4 APIs: The piping between our components 5 Storing our ACH files 6 Taking the next step with Next.js 7 Our minimum viable product Part 3 8 Exceptions 9 Searching and auditing 10 Company information 11 International ACH transactions and OFAC scanning 12 Where to go from here
Generative Ai For Everyone
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Author : Karthikeyan Sabesan
language : en
Publisher: BPB Publications
Release Date : 2025-01-25
Generative Ai For Everyone written by Karthikeyan Sabesan and has been published by BPB Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-01-25 with Computers categories.
DESCRIPTION Generative AI is revolutionizing the way we interact with technology. Imagine creating hyper-realistic images, composing original music pieces, or generating creative text formats, all with the help of AI. This book provides a comprehensive exploration of generative AI and its transformative impact across various industries. This book begins with the basics of AI, explaining ML and design patterns to build a solid foundation. It delves deeply into generative AI and then progresses through machine learning, deep learning, and essential architectures such as CNNs, GANs, Diffusion, RNNs, LSTMs, and Transformers. It covers practical applications, from regression and classification to advanced use cases such as image generation, editing, document search, content summarization, and question answering. Readers will also learn to build prototypes like a Document Q&A bot, research assistant, and prompt playground, while mastering techniques such as continued pre-training, fine-tuning, model merging, retrieval-augmented generation, and agentic AI. By the end of this book, you will transform from a curious beginner to a confident, generative AI user. You will possess the knowledge and skills to explore its capabilities for creative expression, problem-solving, and even business innovation. You will be able to confidently navigate the world of generative AI, turning your ideas into reality. KEY FEATURES ● Explore the entire spectrum of generative AI, from fundamental AI concepts to advanced LLM applications. ● Includes practical examples, code snippets, and real-world case studies to enhance learning and understanding. ● Learn how to use generative AI for business applications, including ethical considerations. WHAT YOU WILL LEARN ● Explore concepts of AI, ML, deep learning, and generative AI. ● Learn about computer vision and generative image AI supported by coding examples. ● Discover NLP Techniques, Transformer architecture components and generative text AI supported by coding examples. ● Understand prompt engineering and LLM frameworks while building prototypes. ● Examine the role of LLM operations throughout the entire LLM lifecycle. ● Investigate the potential impact of generative AI on enterprises and develop business strategies. WHO THIS BOOK IS FOR This book is ideal for anyone curious about generative AI, regardless of their prior technical expertise. Whether you are a business professional, a student, an artist, or simply someone fascinated by the future of technology, this book will provide you with a clear and accessible understanding of this groundbreaking field. TABLE OF CONTENTS 1. AI Fundamentals 2. GenAI Foundation 3. GenAI for Images 4. Transforming Images with GenAI 5. GenAI for Text 6. ChatGPT 7. Large Language Model Frameworks 8. Large Language Model Operations 9. Generative AI for the Enterprise 10. Advances and Sustainability in Generative AI
Microservice Apis
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Author : Jose Haro Peralta
language : en
Publisher: Simon and Schuster
Release Date : 2023-03-07
Microservice Apis written by Jose Haro Peralta and has been published by Simon and Schuster this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-03-07 with Computers categories.
Strategies, best practices, and patterns that will help you design resilient microservices architecture and streamline your API integrations. In Microservice APIs, you’ll discover: Service decomposition strategies for microservices Documentation-driven development for APIs Best practices for designing REST and GraphQL APIs Documenting REST APIs with the OpenAPI specification (formerly Swagger) Documenting GraphQL APIs using the Schema Definition Language Building microservices APIs with Flask, FastAPI, Ariadne, and other frameworks Service implementation patterns for loosely coupled services Property-based testing to validate your APIs, and using automated API testing frameworks like schemathesis and Dredd Adding authentication and authorization to your microservice APIs using OAuth and OpenID Connect (OIDC) Deploying and operating microservices in AWS with Docker and Kubernetes Microservice APIs teaches you practical techniques for designing robust microservices with APIs that are easy to understand, consume, and maintain. You’ll benefit from author José Haro Peralta’s years of experience experimenting with microservices architecture, dodging pitfalls and learning from mistakes he’s made. Inside you’ll find strategies for delivering successful API integrations, implementing services with clear boundaries, managing cloud deployments, and handling microservices security. Written in a framework-agnostic manner, its universal principles can easily be applied to your favorite stack and toolset. About the technology Clean, clear APIs are essential to the success of microservice applications. Well-designed APIs enable reliable integrations between services and help simplify maintenance, scaling, and redesigns. Th is book teaches you the patterns, protocols, and strategies you need to design, build, and deploy effective REST and GraphQL microservices APIs. About the book Microservice APIs gathers proven techniques for creating and building easy-to-consume APIs for microservices applications. Rich with proven advice and Python-based examples, this practical book focuses on implementation over philosophy. You’ll learn how to build robust microservice APIs, test and protect them, and deploy them to the cloud following principles and patterns that work in any language. What's inside Service decomposition strategies for microservices Best practices for designing and building REST and GraphQL APIs Service implementation patterns for loosely coupled components API authorization with OAuth and OIDC Deployments with AWS and Kubernetes About the reader For developers familiar with the basics of web development. Examples are in Python. About the author José Haro Peralta is a consultant, author, and instructor. He’s also the founder of microapis.io. Table of Contents PART 1 INTRODUCING MICROSERVICE APIS 1 What are microservice APIs? 2 A basic API implementation 3 Designing microservices PART 2 DESIGNING AND BUILDING REST APIS 4 Principles of REST API design 5 Documenting REST APIs with OpenAPI 6 Building REST APIs with Python 7 Service implementation patterns for microservices PART 3 DESIGNING AND BUILDING GRAPHQL APIS 8 Designing GraphQL APIs 9 Consuming GraphQL APIs 10 Building GraphQL APIs with Python PART 4 SECURING, TESTING, AND DEPLOYING MICROSERVICE APIS 11 API authorization and authentication 12 Testing and validating APIs 13 Dockerizing microservice APIs 14 Deploying microservice APIs with Kubernetes
Hands On Apis For Ai And Data Science
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Author : Ryan Day
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2025-03-04
Hands On Apis For Ai And Data Science written by Ryan Day 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 2025-03-04 with Computers categories.
Are you ready to grow your skills in AI and data science? A great place to start is learning to build and use APIs in real-world data and AI projects. API skills have become essential for AI and data science success, because they are used in a variety of ways in these fields. With this practical book, data scientists and software developers will gain hands-on experience developing and using APIs with the Python programming language and popular frameworks like FastAPI and StreamLit. As you complete the chapters in the book, you'll be creating portfolio projects that teach you how to: Design APIs that data scientists and AIs love Develop APIs using Python and FastAPI Deploy APIs using multiple cloud providers Create data science projects such as visualizations and models using APIs as a data source Access APIs using generative AI and LLMs
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.