LEADER 03594nam 22004575 450 001 9911007365603321 005 20250522130241.0 010 $a979-88-6881-134-0 024 7 $a10.1007/979-8-8688-1134-0 035 $a(CKB)38891434900041 035 $a(CaSebORM)9798868811340 035 $a(OCoLC)1521194441 035 $a(OCoLC-P)1521194441 035 $a(DE-He213)979-8-8688-1134-0 035 $a(MiAaPQ)EBC32127058 035 $a(Au-PeEL)EBL32127058 035 $a(EXLCZ)9938891434900041 100 $a20250522d2025 u| 0 101 0 $aeng 135 $aur||||||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aBuilding Generative AI Agents $eUsing LangGraph, AutoGen, and CrewAI /$fby Tom Taulli, Gaurav Deshmukh 205 $a1st ed. 2025. 210 1$aBerkeley, CA :$cApress :$cImprint: Apress,$d2025. 215 $a1 online resource (ix, 275 pages) $cillustrations 311 08$a979-88-6881-133-3 327 $aChapter 1: Introduction to Generative AI Agents -- Chapter 2: Generative AI Foundations -- Chapter 3: Types of Agents -- Chapter 4: Open AI GPT Agents and the Assistants API -- Chapter 5: Development Agents -- Chapter 6: Crew AI -- Chapter 7: AutoGen -- Chapter 8: LangChain -- Chapter 9: LangGraph -- Chapter 10: Haystack -- Chapter 11: Takeaways. 330 $aThe 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. These agents already exhibit capabilities such as running test suites, searching the web for documentation, writing software, answering questions based on vast organized information, and performing intricate web-based tasks across multiple domains. They can autonomously investigate cybersecurity incidents and address complex customer support needs. By integrating skills, knowledge bases, planning frameworks, memory, and feedback loops, these systems can handle many tasks and improve over time. Building Generative AI Agents serves as a high-quality guide for developers to understand when and where AI agents can be useful, their advantages and disadvantages, and practical advice on designing, building, deploying, and monitoring them. 606 $aArtificial intelligence 615 0$aArtificial intelligence. 676 $a006.3 700 $aTaulli$b Tom$0541980 702 $aDeshmukh$b Gaurav 801 0$bOCoLC-P 801 1$bOCoLC-P 906 $aBOOK 912 $a9911007365603321 996 $aBuilding Generative AI Agents$94389733 997 $aUNINA