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Python LangChain and LangGraph in Action: Crafting Next-Gen RAG Applications with GPT Agents
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- FormatePub
- ISBN8231144594
- EAN9798231144594
- Date de parution12/06/2025
- Protection num.pas de protection
- Infos supplémentairesepub
- ÉditeurWalzone Press
Résumé
"Python LangChain and LangGraph in Action: Crafting Next-Gen RAG Applications with GPT Agents" is a comprehensive, hands-on guide for developers and AI enthusiasts eager to master the latest tools in Retrieval-Augmented Generation (RAG) and generative AI. This book demystifies the powerful LangChain and LangGraph frameworks, showing how to build intelligent, stateful, and scalable AI agents with Python.
Readers will explore core concepts such as multi-agent orchestration, memory management, human-in-the-loop controls, and advanced prompt engineering. The book offers step-by-step tutorials to design, implement, and deploy real-world AI applications, including chatbots, multi-agent systems, and data-driven workflows. It also covers integration with external APIs, vector databases, and cloud platforms, ensuring practical skills for production-ready solutions.
With detailed case studies and future trends, this book bridges theory and practice, empowering readers to create robust, adaptable AI systems that leverage GPT models effectively. Whether you are a beginner or looking to deepen your expertise, this guide provides the latest methodologies and best practices to build next-generation AI applications confidently.
Readers will explore core concepts such as multi-agent orchestration, memory management, human-in-the-loop controls, and advanced prompt engineering. The book offers step-by-step tutorials to design, implement, and deploy real-world AI applications, including chatbots, multi-agent systems, and data-driven workflows. It also covers integration with external APIs, vector databases, and cloud platforms, ensuring practical skills for production-ready solutions.
With detailed case studies and future trends, this book bridges theory and practice, empowering readers to create robust, adaptable AI systems that leverage GPT models effectively. Whether you are a beginner or looking to deepen your expertise, this guide provides the latest methodologies and best practices to build next-generation AI applications confidently.
"Python LangChain and LangGraph in Action: Crafting Next-Gen RAG Applications with GPT Agents" is a comprehensive, hands-on guide for developers and AI enthusiasts eager to master the latest tools in Retrieval-Augmented Generation (RAG) and generative AI. This book demystifies the powerful LangChain and LangGraph frameworks, showing how to build intelligent, stateful, and scalable AI agents with Python.
Readers will explore core concepts such as multi-agent orchestration, memory management, human-in-the-loop controls, and advanced prompt engineering. The book offers step-by-step tutorials to design, implement, and deploy real-world AI applications, including chatbots, multi-agent systems, and data-driven workflows. It also covers integration with external APIs, vector databases, and cloud platforms, ensuring practical skills for production-ready solutions.
With detailed case studies and future trends, this book bridges theory and practice, empowering readers to create robust, adaptable AI systems that leverage GPT models effectively. Whether you are a beginner or looking to deepen your expertise, this guide provides the latest methodologies and best practices to build next-generation AI applications confidently.
Readers will explore core concepts such as multi-agent orchestration, memory management, human-in-the-loop controls, and advanced prompt engineering. The book offers step-by-step tutorials to design, implement, and deploy real-world AI applications, including chatbots, multi-agent systems, and data-driven workflows. It also covers integration with external APIs, vector databases, and cloud platforms, ensuring practical skills for production-ready solutions.
With detailed case studies and future trends, this book bridges theory and practice, empowering readers to create robust, adaptable AI systems that leverage GPT models effectively. Whether you are a beginner or looking to deepen your expertise, this guide provides the latest methodologies and best practices to build next-generation AI applications confidently.