{ "item_title" : "Rag with Python Cookbook", "item_author" : [" Dominik Polzer "], "item_description" : "As businesses race to unlock the full potential of large language models (LLMs), a critical challenge has emerged: How do you connect these tools to real-time, external data to solve real-world problems? Retrieval-augmented generation (RAG) is the answer. By combining LLMs with information retrieval, RAG empowers you to build everything from intelligent chatbots to autonomous, task-solving agents.Packed with over 70 practical recipes, this go-to guide tackles a wide range of GenAI applications through structured hands-on learning. Author Dominik Polzer provides the tools you need to design, implement, and optimize RAG systems for your unique use cases. Whether you're working with simple data retrieval or designing cutting-edge autonomous agents, this cookbook will help you stay ahead of the curve.Learn core RAG components including embedding, retrieval, and generation techniquesUnderstand advanced workflows like semantic-aware chunking and multi-query promptingBuild custom solutions such as chatbots and autonomous agents for specific data challengesContinuously evaluate and optimize systems for accuracy, relevance, and performance", "item_img_path" : "https://covers1.booksamillion.com/covers/bam/9/79/834/160/9798341600560_b.jpg", "price_data" : { "retail_price" : "79.99", "online_price" : "79.99", "our_price" : "79.99", "club_price" : "79.99", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }

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