LangChain Frameworks: Engineering Advanced Language Models: Harnessing Prompt Engineering, Memory, External Tools, Chatbots, Security, and Scalable La
暫譯: LangChain 框架：工程進階語言模型：利用提示工程、記憶、外部工具、聊天機器人、安全性及可擴展性
Ashbourne, Liam
- 出版商: Independently Published
- 出版日期: 2025-08-25
- 售價: $970
- 貴賓價: 9.5 折 $922
- 語言: 英文
- 頁數: 234
- 裝訂: Quality Paper - also called trade paper
- ISBN: 9798262248940
- ISBN-13: 9798262248940
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相關分類:
LangChain
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相關主題
商品描述
LangChain Frameworks: Engineering Advanced Language Models, the second volume in the Comprehensive AI and Software Innovation Series by Liam Ashbourne, provides a comprehensive guide to mastering LangChain, a powerful framework for building sophisticated language model applications. Spanning 15 meticulously crafted chapters, this book offers developers, data scientists, and AI practitioners an in-depth exploration of LangChain's capabilities, focusing on prompt engineering, memory management, and external tool integration to create scalable, context-aware, and secure AI solutions.
Readers will learn the fundamentals of language models, starting with an introduction to LangChain and its role in modern AI development. The book dives into prompt engineering basics and advanced techniques for chaining prompts effectively, enabling the creation of dynamic and responsive AI interactions. A dedicated chapter on memory in language models equips readers with strategies to maintain contextual continuity, enhancing the performance of context-aware applications. The integration of external tools is thoroughly covered, teaching readers how to augment LangChain with APIs, databases, and other resources for robust functionality.
Practical applications are emphasized, with chapters on LangChain for chatbots and LangChain in e-commerce, providing real-world examples of building intelligent, user-centric systems. Readers will master data augmentation techniques to enrich model inputs and fine-tuning language models to optimize performance for specific tasks. The book also addresses critical technical considerations, including security in language chains, scaling LangChain applications, and debugging LangChain workflows, ensuring readers can build reliable and efficient systems.
Concluding with a forward-looking perspective, the book explores the future of language model frameworks, offering insights into emerging trends and innovations. Through a blend of theoretical foundations, practical tutorials, and case studies, readers will gain the expertise to engineer advanced, secure, and scalable language model applications, positioning them at the forefront of AI-driven software development.
Readers will learn the fundamentals of language models, starting with an introduction to LangChain and its role in modern AI development. The book dives into prompt engineering basics and advanced techniques for chaining prompts effectively, enabling the creation of dynamic and responsive AI interactions. A dedicated chapter on memory in language models equips readers with strategies to maintain contextual continuity, enhancing the performance of context-aware applications. The integration of external tools is thoroughly covered, teaching readers how to augment LangChain with APIs, databases, and other resources for robust functionality.
Practical applications are emphasized, with chapters on LangChain for chatbots and LangChain in e-commerce, providing real-world examples of building intelligent, user-centric systems. Readers will master data augmentation techniques to enrich model inputs and fine-tuning language models to optimize performance for specific tasks. The book also addresses critical technical considerations, including security in language chains, scaling LangChain applications, and debugging LangChain workflows, ensuring readers can build reliable and efficient systems.
Concluding with a forward-looking perspective, the book explores the future of language model frameworks, offering insights into emerging trends and innovations. Through a blend of theoretical foundations, practical tutorials, and case studies, readers will gain the expertise to engineer advanced, secure, and scalable language model applications, positioning them at the forefront of AI-driven software development.
