{
  "type": "edition",
  "site": {
    "name": "Kołczan Książek",
    "language": "pl-PL",
    "url": "https://www.kolczanksiazek.pl"
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  "formats": "Każda podstrona ma dwie wersje z tymi samymi danymi: JSON (adres strony + .json) i markdown (adres strony + .md). Do każdego `url` w tym dokumencie można dopisać .json albo .md.",
  "title": "RAG with Python Cookbook. Practical Recipes from Data Preprocessing to LLM Agents",
  "subtitle": null,
  "url": "https://www.kolczanksiazek.pl/dominik-polzer/rag-with-python-cookbook-practical-recipes-from-data-preprocessing-to-llm-agents/9798341600539",
  "publisher": "O'Reilly Media (Z chęcią przeczytam książkę w języku polskim)",
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  "isbn": "979-83-4160-053-9",
  "pages": 378,
  "published": null,
  "language": "pl_PL",
  "cover": "https://quivercdn.com/covers/oreilly-media-z-checia-przeczytam-ksiazke-w-jezyku-polskim/dominik-polzer/rag-with-python-cookbook-practical-recipes-from-data-preprocessing-to-llm-agents_979-83-4160-053-9.jpg?v=2026-05-12%2000%3A52%3A36",
  "json": "https://www.kolczanksiazek.pl/dominik-polzer/rag-with-python-cookbook-practical-recipes-from-data-preprocessing-to-llm-agents/9798341600539.json",
  "markdown": "https://www.kolczanksiazek.pl/dominik-polzer/rag-with-python-cookbook-practical-recipes-from-data-preprocessing-to-llm-agents/9798341600539.md",
  "binding": "Softcover",
  "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 techniques Understand advanced workflows like semantic-aware chunking and multi-query prompting Build custom solutions such as chatbots and autonomous agents for specific data challenges Continuously evaluate and optimize systems for accuracy, relevance, and performance",
  "book": {
    "title": "RAG with Python Cookbook. Practical Recipes from Data Preprocessing to LLM Agents",
    "slug": "rag-with-python-cookbook-practical-recipes-from-data-preprocessing-to-llm-agents",
    "url": "https://www.kolczanksiazek.pl/dominik-polzer/rag-with-python-cookbook-practical-recipes-from-data-preprocessing-to-llm-agents"
  },
  "authors": [
    {
      "name": "Dominik Polzer",
      "slug": "dominik-polzer",
      "url": "https://www.kolczanksiazek.pl/dominik-polzer"
    }
  ]
}