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  <titleInfo>
    <title>Building generative AI agents</title>
    <subTitle>using LangGraph, AutoGen, and CrewAI</subTitle>
  </titleInfo>
  <name type="personal">
    <namePart>Taulli, Tom</namePart>
    <role>
      <roleTerm authority="marcrelator" type="text">creator</roleTerm>
    </role>
  </name>
  <name type="personal">
    <namePart>Deshmukh, Gaurav</namePart>
  </name>
  <typeOfResource>text</typeOfResource>
  <originInfo>
    <place>
      <placeTerm type="text">New York</placeTerm>
    </place>
    <publisher>Apress</publisher>
    <dateIssued>2025</dateIssued>
    <issuance>monographic</issuance>
  </originInfo>
  <language>
    <languageTerm authority="iso639-2b" type="code">eng</languageTerm>
  </language>
  <physicalDescription>
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    <extent>ix, 275 p.</extent>
  </physicalDescription>
  <abstract>The dawn of AI agents is upon us. Tech visionaries like Bill Gates, Andrew Ng, and Vinod Khosla have highlighted the monumental potential of this powerful technology. This book will provide the knowledge and tools necessary to build generative AI agents using the most popular frameworks, such as AutoGen, LangChain, LangGraph, CrewAI, and Haystack. Recent breakthroughs in large language models have opened up unprecedented possibilities. After years of gradual progress in machine learning and deep learning, we are now witnessing novel approaches capable of understanding, reasoning, and generating content in ways that promise to revolutionize nearly every industry. This platform shift is as significant as the advent of mainframes, PCs, cloud computing, mobile technology, and social media. It's why the world's largest technology companies - like Microsoft, Apple, Google, and Meta - are making enormous investments in this category. While chatbots like ChatGPT, Claude, and Gemini have demonstrated remarkable potential, the years ahead will see the rise of generative AI agents capable of executing complex tasks on behalf of users.</abstract>
  <note type="statement of responsibility">Tom Taulli and Gaurav Deshmukh</note>
  <note>Index present</note>
  <note>Eng</note>
  <subject>
    <topic>Artificial intelligence</topic>
  </subject>
  <subject>
    <topic>Generative AI</topic>
  </subject>
  <subject>
    <topic>Machine learning</topic>
  </subject>
  <classification authority="ddc">006.3 TAU-B</classification>
  <identifier type="isbn">9798868811333</identifier>
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    <recordCreationDate encoding="marc">260807</recordCreationDate>
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