book

AI Networking Cookbook

Name: AI Networking Cookbook
Author: Eric Chou
ISBN: 9781805807995

by Eric Chou

January 2026

Intermediate to advanced

346 pages

5h 40m

English

Packt Publishing

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Preface
Who this book is forWhat this book coversTo get the most out of this bookGet in touchJoin Eric Live for Build Intelligent Networks with AIFree Benefits with Your BookHow to Unlock
The AI LLM Landscape and Key Parameters
Technical requirementsFree Benefits with Your Book1.1 Setting up an OpenAI environmentGetting readyHow to do it…How it works…There’s more…1.2 Experiment with OpenAI LLM models and model parametersGetting readyHow to do it…How it works…There’s more…1.3 Experimenting with OpenAI System messageGetting readyHow to do it…How it works…There’s more…1.4 Experimenting with OpenAI prompt engineering in chatGetting readyHow to do it…How it works…There’s more…1.5 Python scripts with OpenAIGetting readyHow to do it…How it works…There’s more…1.6 Local AI model OllamaGetting readyHow to do it…How it works…There’s more…1.7 Python scripts with OllamaGetting readyHow to do it… How it works…There’s more…SummaryGet This Book’s PDF Version and Exclusive Extras
OpenAI Recipes for Network Engineers
Technical requirements2.1 Using curl for OpenAI API communicationGetting readyHow to do it…How it works…There’s more…2.2 Using Postman with the OpenAI APIGetting readyHow to do it…How it works…There’s more…2.3 Fine-tuning OpenAI responsesGetting readyHow to do it…How it works…There’s more…2.4 Generating network topology with OpenAIGetting readyHow to do it…How it works…There’s more…2.5 Generating methods of procedure (MOPs) with OpenAIGetting readyHow to do it…How it works…There’s more…SummaryGet This Book’s PDF Version and Exclusive Extras
Prompt Engineering for Reliable Outputs
Technical requirements3.1 Giving directions to AI modelsGetting readyHow to do it… How it works… There’s more…See also3.2 Specifying return formatsGetting readyHow to do it…How it works… There’s more…3.3 Giving examplesGetting readyHow to do it… How it works… There’s more…3.4 Providing feedback Getting readyHow to do it… How it works… There’s more…See also3.5 Building prompts gradually Getting readyHow to do it… How it works… There’s more…The network engineer’s advantageSummaryGet This Book’s PDF Version and Exclusive Extras
Local AI LLM Playground in Network Engineering
Technical requirements4.1 Downloading Code Ollama modelsGetting readyHow to do it…How it works…There’s more…See also4.2 Fine-tuning LLM resourcesGetting readyHow to do it…How it works…There’s more…4.3 Generating network code examples with Code LlamaGetting readyHow to do it…How it works…There’s more…See also4.4 Using the Llama 2 Uncensored model for advanced code generationGetting readyHow to do it…How it works…There’s more…4.5 Tweaking models with custom network dataGetting readyHow to do it…How it works…There’s more…4.6 Using a local LLM for network documentation generationGetting readyHow to do it…How it works…There’s more…SummaryGet This Book’s PDF Version and Exclusive Extras
LangChain for Networking Tasks
What is LangChain all about?Technical requirements5.1 Installing and setting up LangChainGetting readyHow to do it…How it works…There’s more…5.2 Creating a network configuration analyzerGetting readyHow to do it…How it works…There’s more…5.3 Using prompt templates for reusabilityGetting readyHow to do it…How it works…There’s more…See also5.4 Combining models with simple chainsGetting readyHow to do it…How it works…There’s more…See also5.5 Using agents with LangChainGetting readyHow to do it…How it works…There’s more…SummaryGet This Book’s PDF Version and Exclusive Extras
Building an AI LLM Network Application Frontend with Streamlit
Technical requirements6.1 Installing and setting up StreamlitGetting readyHow to do it…How it works…There’s more…See also6.2 Creating your first visualizationGetting readyHow to do it…How it works…There’s more…See also6.3 Creating input fieldsGetting readyHow to do it…How it works…There’s more…See also6.4 Creating a navigation menuGetting readyHow to do it…How it works…There’s more…6.5 Organizing projects with foldersGetting readyHow to do it…How it works…There’s more…See alsoSummaryGet This Book’s PDF Version and Exclusive Extras
Building AI LLM Application Backends
Technical requirements7.1 Simple network AI APIsGetting readyHow to do it… How it works… There’s more…See also7.2 Adding device contextGetting readyHow to do it… How it works… There’s more…See also7.3 Adding database storageGetting readyHow to do it… How it works… There’s more…See also7.4 Simple web interfaceGetting readyHow to do it… How it works… There’s more…See also7.5 Docker deploymentGetting readyHow to do it… How it works… There’s more…SummaryGet This Book’s PDF Version and Exclusive Extras
Building a Network Co-Pilot
Technical requirements8.1 Model selection and evaluationGetting readyHow to do it…How it works…There’s more…See also8.2 Building the core AI engineGetting readyHow to do it…How it works…There’s more…See also8.3 Network knowledge integrationGetting readyHow to do it…How it works…There’s more…See alsoSummaryGet This Book’s PDF Version and Exclusive Extras
Network Monitoring and Performance Use Cases with MCP
MCP overviewMCP conceptsTechnical requirements9.1 AI-powered network health analysisGetting readyHow to do it…How it works…There’s more…See also9.2 Predictive network performance analysisGetting readyHow to do it…How it works…There’s more…See also9.3 Intelligent network optimization and auto-remediationGetting readyHow to do it…How it works…There’s more…SummaryGet This Book’s PDF Version and Exclusive Extras

Network Security through Vibe Coding
Technical requirements10.1 Setting up GitHub CopilotGetting readyHow to do it…How it works…There’s more…See also10.2 Setting up Claude CodeGetting readyHow to do it…How it works…There’s more…See also10.3 Conversational log analysis and threat detectionGetting readyHow to do it…How it works…There’s more…See also10.4 Rapid security script development for incident responseGetting readyHow to do it…How it works…There’s more…See alsoSummaryGet This Book’s PDF Version and Exclusive Extras
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Index

Overview

Transform your network operations with AI-powered automation, and learn code generation, prompt engineering, and practical recipes for building custom network tools using AI assistants and Python

Key Features

Leverage AI assistants like OpenAI and Claude to build network automation solutions
Use prompt engineering and AI tools to automate network setup, monitoring, and threat detection
Build AI-assisted network configuration, monitoring, and management workflows with multi-vendor APIs
Purchase of the print or Kindle book includes a free PDF eBook

Book Description

Transform your approach to network automation with the power of AI LLM assistants guided by hands-on recipes for building custom automation solutions quickly using artificial intelligence.

You’ll learn tools and techniques such as Vibe coding for conversational development, OpenAI API scripts, prompt engineering for better outputs, local LLM fine-tuning, combining models with LangChain, and Streamlit-based frontends development. The book progresses from simple Python scripts to advanced AI-assisted automation techniques, including multi-vendor API integration, showing you how AI can enhance network configuration, monitoring, security, and troubleshooting.

Each recipe presents realistic mock data, complete code examples, and step-by-step guidance, creating a safe environment for experimentation while building a solid foundation for future production use. Whether you want to automate routine configuration, implement AI-driven troubleshooting, or build compliance monitoring systems, this cookbook helps you connect your networking expertise with the capabilities of modern AI.

What you will learn

Understand the AI LLM landscape and key parameters for networking tasks
Create OpenAI-enabled scripts for daily network engineering workflows
Master prompt engineering techniques for improved AI outputs
Build local LLMs using Ollama for network applications
Chain language models with LangChain for complex network solutions
Develop AI application frontends using the Streamlit framework
Design robust backends for network AI applications
Build an end-to-end network copilot by integrating all the techniques you've learned

Who this book is for

The AI for Networking Cookbook is for experienced network engineers, network architects, and DevOps professionals who want to enhance their network automation capabilities using AI and LLM technologies. It is especially invaluable for networking professionals looking to integrate conversational AI development, prompt engineering, and modern AI tools like OpenAI APIs, LangChain, and local LLM models into their workflows. Familiarity with basic networking concepts, configurations, and Python is helpful, but no prior AI or advanced programming experience is required.

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