Building Conversational Generative Ai Apps With Langchain And Gpt


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Building Conversational Generative AI Apps with Langchain and GPT: Develop End-to-End LLM-powered Conversational AI Apps with Python, LangChain, GPT and Google Colab


Building Conversational Generative AI Apps with Langchain and GPT: Develop End-to-End LLM-powered Conversational AI Apps with Python, LangChain, GPT and Google Colab

Author: Mugesh S.

language: en

Publisher: Orange Education Pvt Limited

Release Date: 2025-06-04


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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. Book DescriptionConversational 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 you will 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.

Building Conversational Generative AI Apps with Langchain and GPT


Building Conversational Generative AI Apps with Langchain and GPT

Author: Mugesh S

language: en

Publisher: Orange Education Pvt Ltd

Release Date: 2025-06-04


DOWNLOAD





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 with LangChain


Generative AI with LangChain

Author: Ben Auffarth

language: en

Publisher: Packt Publishing Ltd

Release Date: 2023-12-22


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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.