LEADER 03970nam 22005895 450 001 9911031674903321 005 20251016173431.0 010 $a979-88-6881-718-2 024 7 $a10.1007/979-8-8688-1718-2 035 $a(CKB)41520995800041 035 $a(MiAaPQ)EBC32323516 035 $a(Au-PeEL)EBL32323516 035 $a(CaSebORM)9798868817182 035 $a(OCoLC)1543044629 035 $a(OCoLC-P)1543044629 035 $a(DE-He213)979-8-8688-1718-2 035 $a(EXLCZ)9941520995800041 100 $a20251001d2025 u| 0 101 0 $aeng 135 $aur||||||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aMastering LangChain $eA Comprehensive Guide to Building Generative AI Applications /$fby Sanath Raj B Narayan, Nitin Agarwal 205 $a1st ed. 2025. 210 1$aBerkeley, CA :$cApress :$cImprint: Apress,$d2025. 215 $a1 online resource (181 pages) 225 1 $aProfessional and Applied Computing Series 311 08$a979-88-6881-717-5 327 $aChapter 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. 330 $aThis book provides a comprehensive exploration of LangChain, empowering you to effectively harness large language models (LLMs) for Gen AI applications. It focuses on practical implementation and techniques, making it a valuable resource for learning LangChain. The book starts with foundational topics such as environment setup and building basic chains, then delves into key components such as prompt templates, tool integration, and memory management. You will also explore practical topics such as output parsing, embedding models, and developing chatbots and retrieval-augmented generation (RAG) systems. Additional chapters focus on integrating LangChain with other AI tools and deploying applications while emphasizing best practices for AI ethics and performance. By the time you finish this book, you?ll have the know-how to confidently build Generative AI solutions using LangChain. Whether you're exploring practical applications or curious about the latest trends, this guide gives you the tools and insights to solve real-world AI problems. You?ll be ready to design smart, data-driven applications?and rethink how you approach Generative AI. What You Will Learn Understand the core ideas, architecture, and essential features of the LangChain framework Create advanced LLM-driven workflows and applications that address real-world challenges Develop robust Retrieval-Augmented Generation (RAG) systems using LangChain, vector databases, and proven best practices for retrieving and generating high-quality responses. 410 0$aProfessional and Applied Computing Series 606 $aArtificial intelligence 606 $aComputer programming 606 $aChatbots 606 $aApplication program interfaces (Computer software) 606 $aPython (Computer program language) 615 0$aArtificial intelligence. 615 0$aComputer programming. 615 0$aChatbots. 615 0$aApplication program interfaces (Computer software) 615 0$aPython (Computer program language) 676 $a004.6 700 $aNarayan$b Sanath Raj B$01850194 701 $aAgarwal$b Nitin$01361236 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9911031674903321 996 $aMastering LangChain$94443132 997 $aUNINA