{"product_id":"generative-ai-apps-with-langchain-and-python-a-project-based-approach-to-building-real-world-llm-apps-paperback","title":"Generative AI Apps with Langchain and Python: A Project-Based Approach to Building Real-World LLM Apps - Paperback","description":"\u003cdiv\u003e\u003cp style=\"text-align: right;\"\u003e\u003ca href=\"https:\/\/reportcopyrightinfringement.com\/\" target=\"_blank\" rel=\"nofollow\"\u003e\u003cb\u003eReport copyright infringement\u003c\/b\u003e\u003c\/a\u003e\u003c\/p\u003e\u003c\/div\u003e\u003cp\u003eby \u003cb\u003eRabi Jay\u003c\/b\u003e (Author)\u003c\/p\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003eFuture-proof your programming career through practical projects designed to grasp the intricacies of LangChain's components, from core chains to advanced conversational agents. This hands-on book provides Python developers with the necessary skills to develop real-world Large Language Model (LLM)-based Generative AI applications quickly, regardless of their experience level.\u003c\/p\u003e \u003cp\u003eProjects throughout the book offer practical LLM solutions for common business issues, such as information overload, internal knowledge access, and enhanced customer communication. Meanwhile, you'll learn how to optimize workflows, enhance embedding efficiency, select between vector stores, and other optimizations relevant to experienced AI users. The emphasis on real-world applications and practical examples will enable you to customize your own projects to address pain points across various industries.\u003c\/p\u003e \u003cp\u003e\u003cem\u003eDeveloping LangChain-based Generative AI LLM Apps with Python\u003c\/em\u003e employs a focused toolkit (LangChain, Pinecone, and Streamlit LLM integration) to practically showcase how Python developers can leverage existing skills to build Generative AI solutions. By addressing tangible challenges, you'll learn-by-be doing, enhancing your career possibilities in today's rapidly evolving landscape.\u003c\/p\u003e \u003cp\u003e\u003cstrong\u003eWhat You Will Learn \u003c\/strong\u003e\u003c\/p\u003e \u003cul\u003e \u003cli\u003eUnderstand different types of LLMs and how to select the right ones for responsible AI.\u003c\/li\u003e \u003cli\u003eStructure effective prompts.\u003c\/li\u003e \u003cli\u003eMaster LangChain concepts, such as chains, models, memory, and agents.\u003c\/li\u003e \u003cli\u003eApply embeddings effectively for search, content comparison, and understanding similarity.\u003c\/li\u003e \u003cli\u003eSetup and integrate Pinecone vector database for indexing, structuring data, and search.\u003c\/li\u003e \u003cli\u003eBuild Q \u0026amp; A applications for multiple doc formats.\u003c\/li\u003e \u003cli\u003eDevelop multi-step AI workflow apps using LangChain agents.\u003c\/li\u003e \u003c\/ul\u003e \u003cp\u003e\u003cstrong\u003eWho This Book Is For\u003c\/strong\u003e\u003c\/p\u003e \u003cp\u003ePython programmers who aim to develop a basic understanding of AI concepts and move from LLM theory to practical Generative AI application development using LangChain; those seeking a structured guide to enhance their careers by learning to create robust, real-world LLM-powered Generative AI applications; data scientists, analysts, and experienced developers new to LLMs.\u003c\/p\u003e \u003cp\u003e \u003c\/p\u003e\u003ch3\u003eBack Jacket\u003c\/h3\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003eFuture-proof your programming career through practical projects designed to grasp the intricacies of LangChain's components, from core chains to advanced conversational agents. This hands-on book provides Python developers with the necessary skills to develop real-world Large Language Model (LLM)-based Generative AI applications quickly, regardless of their experience level.\u003c\/p\u003e \u003cp\u003eProjects throughout the book offer practical LLM solutions for common business issues, such as information overload, internal knowledge access, and enhanced customer communication. Meanwhile, you'll learn how to optimize workflows, enhance embedding efficiency, select between vector stores, and other optimizations relevant to experienced AI users. The emphasis on real-world applications and practical examples will enable you to customize your own projects to address pain points across various industries.\u003c\/p\u003e \u003cp\u003e\u003cem\u003eDeveloping LangChain-based Generative AI LLM Apps with Python\u003c\/em\u003e employs a focused toolkit (LangChain, Pinecone, and Streamlit LLM integration) to practically showcase how Python developers can leverage existing skills to build Generative AI solutions. By addressing tangible challenges, you'll learn-by-be doing, enhancing your career possibilities in today's rapidly evolving landscape.\u003c\/p\u003e \u003cp\u003eYou will: \u003c\/p\u003e \u003cul\u003e \u003cli\u003eUnderstand different types of LLMs and how to select the right ones for responsible AI.\u003c\/li\u003e \u003cli\u003eStructure effective prompts.\u003c\/li\u003e \u003cli\u003eMaster LangChain concepts, such as chains, models, memory, and agents.\u003c\/li\u003e \u003cli\u003eApply embeddings effectively for search, content comparison, and understanding similarity.\u003c\/li\u003e \u003cli\u003eSetup and integrate Pinecone vector database for indexing, structuring data, and search.\u003c\/li\u003e \u003cli\u003eBuild Q \u0026amp; A applications for multiple doc formats.\u003c\/li\u003e \u003cli\u003eDevelop multi-step AI workflow apps using LangChain agents.\u003c\/li\u003e \u003c\/ul\u003e\u003ch3\u003eAuthor Biography\u003c\/h3\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003eRabi Jay\u003c\/strong\u003e has over 15 years of experience driving digital transformation with a unique blend of technical depth and business acumen. His background as a Java and SAP ABAP developer provides insights into the enterprise systems LLMs often needed to integrate with. As a leader in Deloitte's Digital \/ Cloud Native practice, he has gained cross-industry experience applying AI solutions, positioning him to identify where LLMs offer the greatest potential for business impact.\u003c\/p\u003e \u003cp\u003eHe is passionate about making complex technology accessible, leading him to authoring books on SAP NetWeaver Portal Technology and \"Enterprise AI in the Cloud\" along with regular contributions to industry publications. His role as a technical reviewer for Large Language Model Based Solutions, Modern Python Development Using ChatGPT, and as Vice President at HCL America, focused on digital transformation, demonstrate his active engagement in the LLM field. Additionally, he runs a LinkedIn newsletter (\"Enterprise AI Transformation\") and free LinkedIn course (\"Generative AI for Business Innovation\").\u003c\/p\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003eNumber of Pages:\u003c\/strong\u003e 513\u003c\/div\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003eDimensions:\u003c\/strong\u003e 1.08 x 9.21 x 6.14 IN\u003c\/div\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003eIllustrated:\u003c\/strong\u003e Yes\u003c\/div\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003ePublication Date:\u003c\/strong\u003e January 12, 2025\u003c\/div\u003e\n            ","brand":"BooksCloud","offers":[{"title":"Default Title","offer_id":44846332903526,"sku":"9798868808814","price":79.99,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0599\/7255\/0758\/files\/N9Ou_GP8ZV9798868808814.webp?v=1772683520","url":"https:\/\/infinitylightwa.com\/products\/generative-ai-apps-with-langchain-and-python-a-project-based-approach-to-building-real-world-llm-apps-paperback","provider":"Infinity Light","version":"1.0","type":"link"}