دانلود کتاب ساخت عامل‌های هوش مصنوعی برای عملیات شبکه – طراحی گردش‌های کاری NetOps مبتنی بر LLM با پایتون، اولاما، MCP و فراخوانی ابزار

Network operations has always been a context-heavy job. A single incident can involve alerts, command-line output, routing state, interface status, topology notes, change records, and handoffs between teams. The challenge is not just collecting information. It is knowing what to check next, how to keep the evidence clear, and how to avoid turning an investigation into guesswork. AI agents are becoming interesting for network teams because they can help gather context, reason over evidence, and support troubleshooting workflows. But they also introduce new risks if they are given too much freedom, trusted without validation, or connected to tools without clear controls. This book takes a careful, engineering-led view of AI in network operations. The goal is not to replace network engineers or automate blindly. The goal is to show how AI-assisted workflows can support engineers while keeping validation, visibility, and control at the center. Building AI Agents for Network Operations starts with local large language model workflows and gradually builds toward a controlled troubleshooting agent. You will work with prompts, structured output, memory, tool calling, MCP, and production-readiness patterns. Each part of the journey is designed to help you understand not only what the agent does, but also how the surrounding application keeps it safe and useful. By the end of this book, you should have a clear path for designing, testing, and reviewing AIassisted network workflows that can move from a local lab toward controlled operational evaluation. This book is for network engineers, NetOps engineers, NOC engineers, SREs, DevOps engineers, network automation professionals, and platform engineers who want to understand how AI agents can support network troubleshooting and operations. If you work with CLI output, routing issues, incident triage, automation scripts, or operational tooling, this book will help you connect AI concepts to familiar network workflows. Basic networking knowledge and comfort with the command line will help you get the most from the examples. Beginner-level Python knowledge is useful, but the labs are designed to explain the important application patterns as they are introduced.