Fully Automated Network Documentation using Python and AI - Part 2

This episode is the audio from a YouTube video. Some segments reference on-screen demos. Watch the full video at https://youtu.be/LA3_eIaBM1E

Manually copy-pasting show command output into a browser chat works fine for a lab, but it falls apart the moment you need to run it against a whole site, on a schedule, or hand it off to a teammate.

This episode walks through a fully automated network documentation pipeline built on Python, Netmiko, and the Claude API. One YAML inventory, one command, and you get back a finished runbook plus an optional draw.io diagram in minutes.

What you’ll learn

• How to set up a YAML inventory file that drives the entire pipeline
• How to get an Anthropic API key, store it safely in ~/.bashrc, and understand the real cost
• How the one-command pipeline collects, redacts, assembles, calls the API, and restores real values
• How to generate a draw.io network diagram with a single flag (no extra API call)
• How to switch between Claude, OpenAI, and Gemini and override the default model
• How to handle scaling honestly once you have more than 20 devices

Chapters

• 00:00 Intro
• 01:08 From 5 Scripts to 1 Command
• 02:28 Inventory YAML File
• 04:01 API Keys, Cost, and Setup
• 06:23 Credentials and Secrets Warning
• 06:42 Running the Pipeline Live
• 07:37 Inside the Generated Runbook
• 09:24 Optional Network Diagram Flag
• 10:17 Switching AI Providers and Models
• 11:10 Token Limits and How to Scale
• 12:14 GitHub, Blog, and What’s Next
• 12:47 Recap

Resources

• GitHub (script, inventory example, README): https://github.com/GTalksTech/netops-toolkit/tree/main/scripts/netmiko/api-automation-pipeline
• Blog post companion: https://gtalkstech.com/blog/api-automation-pipeline/
• Anthropic API console (to create your key): https://console.anthropic.com
• Netmiko (Kirk Byers): https://github.com/ktbyers/netmiko

Heads up on this one: it’s a screen-share build, so there is real terminal work you can’t see here. The reasoning and the findings all stand on their own in audio. If you want to replicate the lab, the video version is worth the watch.

Support the show: https://ko-fi.com/gtalkstech