The Langgraph Langchain Developer S Guide
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Master Langgraph
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Author : Hawke Nexon
language : en
Publisher: Independently Published
Release Date : 2025-05-12
Master Langgraph written by Hawke Nexon and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-05-12 with Computers categories.
Master LangGraph: A Developer's Guide to AI Workflows and Agents with LangChain Build scalable, intelligent, and production-ready AI applications using the next-generation graph-based framework for Python. The future of AI development is graph-based - are you ready to lead the charge? LangGraph is revolutionizing how developers design and orchestrate intelligent workflows using Large Language Models (LLMs). Whether you're building collaborative agents, research assistants, or automated enterprise systems, this book provides the roadmap to mastering LangGraph with Python and LangChain. Inside this hands-on guide, you'll learn how to: Think in graphs: Model AI workflows and multi-agent systems using LangGraph's node, edge, and state architecture. Go beyond pipelines: Explore the power of conditionals, loops, memory, and tool use in dynamic, decision-based agents. Build real-world apps: From research assistants to product ideators, walk through full projects with production-ready patterns. Design intelligent agents: Implement LangChain tools, custom functions, memory modules, and OpenAI function calling. Scale and deploy with confidence: Learn how to integrate FastAPI, Streamlit, Docker, CI/CD pipelines, and observability tools. Ensure safety and ethics: Build secure, explainable, and aligned agent systems with guardrails and auditability. Stay ahead of the curve: Discover emerging trends, distributed agents, and the LangGraph open-source roadmap. Who this book is for: Developers working with Python, LLMs, and LangChain AI engineers building multi-agent systems and automation workflows Technical founders and researchers looking to prototype scalable AI apps Educators, students, and hackathon participants exploring next-gen AI tools Bonus Resources Include: Companion GitHub repository with full code examples Developer challenges, project templates, and workshop curriculum Glossary, API references, and prompt engineering templates If you're serious about building intelligent, adaptive, and scalable AI systems - this is the one book you can't afford to miss.
Agentic Ai A Practical Guide To Build Agent Based Ai Systems That Think And Act
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Author : Tejas Patthi
language : en
Publisher: Tejas Patthi
Release Date : 2025-06-30
Agentic Ai A Practical Guide To Build Agent Based Ai Systems That Think And Act written by Tejas Patthi and has been published by Tejas Patthi this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-06-30 with Computers categories.
Build real-world AI systems that do more than just respond. They think, plan, and act with purpose. Agentic AI is a comprehensive, hands-on guide to building autonomous AI agents using Python, large language models (LLMs), LangGraph, CrewAI, FAISS, and other modern tools. Whether you are an AI developer, a machine learning engineer, or a tech enthusiast, this book will help you move beyond simple chatbots and prompt-based models into the advanced world of intelligent, agent-based systems that function independently and handle real tasks. In this step-by-step guide, you’ll learn how to build LLM-powered autonomous agents capable of reasoning, tool use, memory recall, and multi-step task execution. From integrating with real-world APIs to deploying production-ready agent workflows, you'll gain the skills to create powerful and reliable agentic AI systems using today's top frameworks and best practices. 🔍 What You Will Learn: How to build autonomous AI agents that work independently without constant human input How to create agents with long-term memory using vector databases like FAISS and Chroma How to orchestrate multi-agent systems using frameworks like LangGraph and CrewAI How to integrate AI with external tools, APIs, and web services How to use Python to script smart agent behaviors and decision-making logic How to deploy agentic systems in cloud environments or containers with live monitoring How to implement agent safety, performance testing, and real-time feedback loops 💡 Why This Book Is Different: This is not just another theoretical AI book. Agentic AI is a project-based, code-driven manual that gives you everything you need to: Build tool-using AI assistants, copilots, and multi-agent task managers Use LangChain, LangGraph, CrewAI, and LLM toolchains effectively Combine LLMs with real-time data, plugins, memory, and feedback systems Design and deploy goal-driven AI agents with full autonomy and context awareness Stay ahead in the fast-evolving field of agent-based AI and LLM integration 🧠 Tools and Technologies Covered: Python 3.x LangGraph & LangChain CrewAI & OpenAgents ChromaDB & FAISS for memory OpenAI, Claude, Gemini, HuggingFace APIs FastAPI, Docker, REST APIs, and Webhooks Autonomous task chaining, multi-agent routing, and smart tool use 📦 Who Should Read This Book? AI Engineers ready to move beyond static models Python Developers exploring LLMs and autonomous systems Tech founders building smart assistants and AI copilots Data Scientists interested in real-world AI deployment Prompt engineers ready to level up into full-stack AI workflows
Generative Ai With Langchain
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Author : Ben Auffarth
language : en
Publisher: Packt Publishing Ltd
Release Date : 2025-05-23
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 2025-05-23 with Computers categories.
Go beyond foundational LangChain documentation with detailed coverage of LangGraph interfaces, design patterns for building AI agents, and scalable architectures used in production—ideal for Python developers building GenAI applications Key Features Bridge the gap between prototype and production with robust LangGraph agent architectures Apply enterprise-grade practices for testing, observability, and monitoring Build specialized agents for software development and data analysis Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionThis second edition tackles the biggest challenge facing companies in AI today: moving from prototypes to production. Fully updated to reflect the latest developments in the LangChain ecosystem, it captures how modern AI systems are developed, deployed, and scaled in enterprise environments. This edition places a strong focus on multi-agent architectures, robust LangGraph workflows, and advanced retrieval-augmented generation (RAG) pipelines. You'll explore design patterns for building agentic systems, with practical implementations of multi-agent setups for complex tasks. The book guides you through reasoning techniques such as Tree-of -Thoughts, structured generation, and agent handoffs—complete with error handling examples. Expanded chapters on testing, evaluation, and deployment address the demands of modern LLM applications, showing you how to design secure, compliant AI systems with built-in safeguards and responsible development principles. This edition also expands RAG coverage with guidance on hybrid search, re-ranking, and fact-checking pipelines to enhance output accuracy. Whether you're extending existing workflows or architecting multi-agent systems from scratch, this book provides the technical depth and practical instruction needed to design LLM applications ready for success in production environments.What you will learn Design and implement multi-agent systems using LangGraph Implement testing strategies that identify issues before deployment Deploy observability and monitoring solutions for production environments Build agentic RAG systems with re-ranking capabilities Architect scalable, production-ready AI agents using LangGraph and MCP Work with the latest LLMs and providers like Google Gemini, Anthropic, Mistral, DeepSeek, and OpenAI's o3-mini Design secure, compliant AI systems aligned with modern ethical practices Who this book is for This book is for developers, researchers, and anyone looking to learn more about LangChain and LangGraph. With a strong emphasis on enterprise deployment patterns, it’s especially valuable for teams implementing LLM solutions at scale. While the first edition focused on individual developers, this updated edition expands its reach to support engineering teams and decision-makers working on enterprise-scale LLM strategies. A basic understanding of Python is required, and familiarity with machine learning will help you get the most out of this book.
Learning Langchain
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Author : Mayo Oshin
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2025-02-13
Learning Langchain written by Mayo Oshin 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 2025-02-13 with Business & Economics categories.
If you're looking to build production-ready AI applications that can reason and retrieve external data for context-awareness, you'll need to master LangChain—a popular development framework and platform for building, running, and managing agentic applications. LangChain is used by several leading companies, including Zapier, Replit, Databricks, and many more. This guide is an indispensable resource for developers who understand Python or JavaScript but are beginners eager to harness the power of AI. Authors Mayo Oshin and Nuno Campos demystify the use of LangChain through practical insights and in-depth tutorials. Starting with basic concepts, this book shows you step-by-step how to build a production-ready AI agent that uses your data. Harness the power of retrieval-augmented generation (RAG) to enhance the accuracy of LLMs using external up-to-date data Develop and deploy AI applications that interact intelligently and contextually with users Make use of the powerful agent architecture with LangGraph Integrate and manage third-party APIs and tools to extend the functionality of your AI applications Monitor, test, and evaluate your AI applications to improve performance Understand the foundations of LLM app development and how they can be used with LangChain
The Langgraph Langchain Handbook
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Author : William Deckman
language : en
Publisher: Independently Published
Release Date : 2025
The Langgraph Langchain Handbook written by William Deckman 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 with Computers categories.
Unlock the full potential of Natural Language Processing (NLP) with "The LangGraph LangChain Handbook: A Developer's Guide to Tackling NLP Challenges to Create Powerful and Cutting-Edge AI Solutions." This comprehensive guide empowers developers, data scientists, and AI enthusiasts to harness the combined strengths of LangGraph and LangChain frameworks, enabling the creation of sophisticated and intelligent AI applications. Dive into the essentials of LangChain for Retrieval-Augmented Generation (RAG) beginners and advance to mastering Large Language Model (LLM) application development. This handbook provides step-by-step instructions on building autonomous AI agents, managing multi-agent systems, and designing advanced AI workflows. Learn how to develop generative AI solutions on Google Cloud with LangChain, integrating seamlessly with modern cloud infrastructures to deliver scalable and efficient applications. Featuring detailed project blueprints and a dedicated projects lab section, "The LangGraph LangChain Handbook" bridges the gap between theory and practice. Engage with real-world projects such as building intelligent AI agents with LangGraph, utilizing LangChain for robust LLM applications, and integrating CrewAI for enhanced AI development. Explore hands-on examples like LangGraph RAG in JavaScript and delve into the intricacies of architecture-based design for multi-agent systems. Whether you are a beginner embarking on your first AI project or an experienced developer seeking to expand your expertise, this handbook offers valuable insights and practical tools to overcome complex NLP challenges. From understanding the fundamentals of multi-agent reinforcement learning to implementing advanced AI agent systems, you will gain the knowledge and skills needed to create powerful and cutting-edge AI solutions. Embrace the future of AI development with "The LangGraph LangChain Handbook" and transform your approach to building intelligent, scalable, and innovative NLP applications. Equip yourself with the expertise to lead in the rapidly evolving landscape of artificial intelligence and make a significant impact in your projects and career. Get your copy today and start building the next generation of AI solutions!
The Langgraph Langchain Developer S Guide
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Author : Edward R DeForest
language : en
Publisher: Independently Published
Release Date : 2024-12-13
The Langgraph Langchain Developer S Guide written by Edward R DeForest and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-12-13 with Computers categories.
Unlock the power of AI and take your projects to the next level with "LangGraph & LangChain: Mastering Next-Generation AI Development"-the ultimate guide to building intelligent systems using cutting-edge NLP technologies. Designed for developers, entrepreneurs, and AI enthusiasts, this book simplifies the complexities of LangChain and LangGraph, providing hands-on insights and practical examples to transform how you create and deploy AI-powered applications. Whether you're crafting Generative AI models, developing real-time chatbots, or managing knowledge graphs, this book offers everything you need to harness the capabilities of LangGraph and LangChain. From learning prompt engineering to mastering LLM integration, each chapter builds your expertise, empowering you to design systems that adapt, scale, and deliver exceptional performance. Explore key topics such as: LangGraph for Beginners: Start with the fundamentals of knowledge graphs and learn how to structure and query data effectively. LangChain in Your Pocket: Discover the versatility of LangChain for conversational AI, generative applications, and beyond. Generative AI on Google Cloud: Learn how to deploy LangChain-powered AI systems on scalable cloud infrastructure. Hands-On Mastery: Follow step-by-step guides to build real-world applications, from prompt-driven tools to advanced multimodal systems. This crash course is packed with expert insights, personal anecdotes, and actionable strategies to keep you ahead in the competitive field of AI. Whether you're a beginner with "CrewAI LangGraph for Beginners" or an experienced developer diving into "Generative AI with LangChain", this book adapts to your needs. Transform your career with a learning experience tailored to the modern AI ecosystem. Grab your copy now and start mastering LangChain, LangGraph, and the technologies shaping the future of AI development!
Generative Ai On Google Cloud With Langchain
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Author : Leonid Kuligin
language : en
Publisher: Packt Publishing Ltd
Release Date : 2024-12-20
Generative Ai On Google Cloud With Langchain written by Leonid Kuligin 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 2024-12-20 with Computers categories.
Turn challenges into opportunities by mastering advanced techniques for text generation, summarization, and question answering using LangChain and Google Cloud tools Key Features Solve real-world business problems with hands-on examples of GenAI applications on Google Cloud Learn repeatable design patterns for Gen AI on Google Cloud with a focus on architecture and AI ethics Build and implement GenAI agents and workflows, such as RAG and NL2SQL, using LangChain and Vertex AI Purchase of the print or Kindle book includes a free PDF eBook Book Description The rapid transformation and enterprise adoption of GenAI has created an urgent demand for developers to quickly build and deploy AI applications that deliver real value. Written by three distinguished Google AI engineers and LangChain contributors who have shaped Google Cloud’s integration with LangChain and implemented AI solutions for Fortune 500 companies, this book bridges the gap between concept and implementation, exploring LangChain and Google Cloud’s enterprise-ready tools for scalable AI solutions. You'll start by exploring the fundamentals of large language models (LLMs) and how LangChain simplifies the development of AI workflows by connecting LLMs with external data and services. This book guides you through using essential tools like the Gemini and PaLM 2 APIs, Vertex AI, and Vertex AI Search to create sophisticated, production-ready GenAI applications. You'll also overcome the context limitations of LLMs by mastering advanced techniques like Retrieval-Augmented Generation (RAG) and external memory layers. Through practical patterns and real-world examples, you’ll gain everything you need to harness Google Cloud’s AI ecosystem, reducing the time to market while ensuring enterprise scalability. You’ll have the expertise to build robust GenAI applications that can be tailored to solve real-world business challenges. What you will learn Build enterprise-ready applications with LangChain and Google Cloud Navigate and select the right Google Cloud generative AI tools Apply modern design patterns for generative AI applications Plan and execute proof-of-concepts for enterprise AI solutions Gain hands-on experience with LangChain's and Google Cloud's AI products Implement advanced techniques for text generation and summarization Leverage Vertex AI Search and other tools for scalable AI solutions Who this book is for If you’re an application developer or ML engineer eager to dive into GenAI, this book is for you. Whether you're new to LangChain or Google Cloud, you'll learn how to use these tools to build scalable AI solutions. This book is ideal for developers familiar with Python and machine learning basics looking to apply their skills in GenAI. Professionals who want to explore Google Cloud's powerful suite of enterprise-grade GenAI products and their implementation will also find this book useful.
Llm Design Patterns
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Author : Ken Huang
language : en
Publisher: Packt Publishing Ltd
Release Date : 2025-05-30
Llm Design Patterns written by Ken Huang 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 2025-05-30 with Computers categories.
Explore reusable design patterns, including data-centric approaches, model development, model fine-tuning, and RAG for LLM application development and advanced prompting techniques Key Features Learn comprehensive LLM development, including data prep, training pipelines, and optimization Explore advanced prompting techniques, such as chain-of-thought, tree-of-thought, RAG, and AI agents Implement evaluation metrics, interpretability, and bias detection for fair, reliable models Print or Kindle purchase includes a free PDF eBook Book DescriptionThis practical guide for AI professionals enables you to build on the power of design patterns to develop robust, scalable, and efficient large language models (LLMs). Written by a global AI expert and popular author driving standards and innovation in Generative AI, security, and strategy, this book covers the end-to-end lifecycle of LLM development and introduces reusable architectural and engineering solutions to common challenges in data handling, model training, evaluation, and deployment. You’ll learn to clean, augment, and annotate large-scale datasets, architect modular training pipelines, and optimize models using hyperparameter tuning, pruning, and quantization. The chapters help you explore regularization, checkpointing, fine-tuning, and advanced prompting methods, such as reason-and-act, as well as implement reflection, multi-step reasoning, and tool use for intelligent task completion. The book also highlights Retrieval-Augmented Generation (RAG), graph-based retrieval, interpretability, fairness, and RLHF, culminating in the creation of agentic LLM systems. By the end of this book, you’ll be equipped with the knowledge and tools to build next-generation LLMs that are adaptable, efficient, safe, and aligned with human values. What you will learn Implement efficient data prep techniques, including cleaning and augmentation Design scalable training pipelines with tuning, regularization, and checkpointing Optimize LLMs via pruning, quantization, and fine-tuning Evaluate models with metrics, cross-validation, and interpretability Understand fairness and detect bias in outputs Develop RLHF strategies to build secure, agentic AI systems Who this book is for This book is essential for AI engineers, architects, data scientists, and software engineers responsible for developing and deploying AI systems powered by large language models. A basic understanding of machine learning concepts and experience in Python programming is a must.
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Author :
language : en
Publisher: "O'Reilly Media, Inc."
Release Date :
written by 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 with categories.
Intro Guide To Concept Of Ai Agent
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Author : Barron Wilson
language : en
Publisher: Estalontech
Release Date : 2025-06-06
Intro Guide To Concept Of Ai Agent written by Barron Wilson and has been published by Estalontech this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-06-06 with Computers categories.
So you want to know what AI agents are all about? Great! Think of this as your friendly, easy-to-digest intro to one of the most exciting trends in tech today — no jargon, no complicated theories, just simple ideas and real-world examples. An AI Agent isn’t just a chatbot or a bot that follows strict rules. It’s more like a smart assistant that can understand your goals, make plans, use tools, and even adapt when things don’t go as expected. Imagine telling an AI: “Find me the best flight to London next week,” and it actually figures out how to do that using different websites, compares prices, checks for availability, and books it — all on its own. That’s the power of an AI agent. This guide breaks everything down into bite-sized pieces so anyone can understand. You’ll learn: What makes an AI agent different from regular bots How they work behind the scenes — think of them having a brain (powered by large language models), a toolkit (like APIs, apps, databases), memory, and a rulebook (your instructions). Real-life examples , like AI assistants handling customer service or helping coders debug software. How to start experimenting with automation using visual tools like n8n, Zapier, or Make — no coding required! Important safety tips — because building smart systems also means thinking about ethics, privacy, and responsibility. One of the coolest parts is seeing how multiple AI agents can work together like a team. Just like humans divide up tasks, AI agents can split up complex problems, help each other out, and get things done faster and smarter. The guide also gives you a peek into the future — where you can start building your own AI agents using development kits from big companies like Google. But here’s the key advice: start simple . Don’t jump into complex systems unless you really need to. Often, a clear instruction or a basic workflow is all you need. And if you're inspired and want to go further, the book recommends diving into "AI Agents Made Easy" — a hands-on guide to building your own digital helpers using no-code tools. In short, this pocket guide is perfect for beginners who want to understand AI agents, see how they can change the way we work, and take the first step toward building their own. Whether you're a business owner, student, or just plain curious, this is your doorway into the future of AI — and it's already here.