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[null,"1.","Record Nr.",null,"UNINA9911031674903321"]
[null,null,"Autore",null,"Narayan Sanath Raj B"]
[null,null,"Titolo",null,"Mastering LangChain : A Comprehensive Guide to Building Generative AI Applications / / by Sanath Raj B Narayan, Nitin Agarwal"]
[null,null,"Pubbl/distr/stampa",null,"Berkeley, CA : , : Apress : , : Imprint : Apress, , 2025"]
[null,null,"ISBN",null,"979-88-6881-718-2"]
[null,null,"Edizione",null,"[1st ed. 2025.]"]
[null,null,"Descrizione fisica",null,"1 online resource (181 pages)"]
[null,null,"Collana",null,"Professional and Applied Computing Series"]
[null,null,"Disciplina",null,"004.6"]
[null,null,"Soggetti",null,"Artificial intelligence"]
[{"$nulls":4},"Computer programming"]
[{"$nulls":4},"Chatbots"]
[{"$nulls":4},"Application program interfaces (Computer software)"]
[{"$nulls":4},"Python (Computer program language)"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,"Nota di contenuto",null,"Chapter 1: Introduction to LangChain -- Chapter 2: Core Components of LangChain -- Chapter 3: Advanced Components and Integrations -- Chapter 4: Building Chatbots -- Chapter 5: Building Retrieval-Augmented Generation (RAG) Systems -- Chapter 6: LangServe, LangSmith, and LangGraph: Deploying, Optimizing, and Designing Language Model Workflows -- Chapter 7: LangChain and NLP -- Chapter 8: Building AI Agents with LangGraph -- Chapter 9: LangChain Framework Integration -- Chapter 10: Deploying LangChain Applications -- Chapter 11: Best Practices and Practical Aspects."]
[null,null,null,"Sommario/riassunto","This book provides a comprehensive exploration of LangChain, empowering you to effectively harness large language models (LLMs) for Gen AI applications. It focuses on practical implementation and techniques, making it a valuable resource for learning LangChain. The book starts with foundational topics such as environment setup and building basic chains, then delves into key components such as prompt templates, tool integration, and memory management. You will also explore practical topics such as output parsing, embedding models, and developing chatbots and retrieval-augmented generation (RAG) systems. Additional chapters focus on integrating LangChain with other AI tools and deploying applications while emphasizing best practices for AI ethics and performance. By the time you finish this book, you’ll have the know-how to confidently build Generative AI solutions using "]
[{"$nulls":4},"LangChain. Whether you're exploring practical applications or curious about the latest trends, this guide gives you the tools and insights to solve real-world AI problems. You’ll be ready to design smart, data-driven applications—and rethink how you approach Generative AI. What You Will Learn Understand the core ideas, architecture, and essential features of the LangChain framework Create advanced LLM-driven workflows and applications that address real-world challenges Develop robust Retrieval-Augmented Generation (RAG) systems using LangChain, vector databases, and proven best practices for retrieving and generating high-quality responses."]