Tips

Tip: Use the genai-prices Python library to calculate the estimated cost of calling LLM inference APIs. This avoids maintaining your own pricing table and lets you report token counts and cost for each request. Below is an example: # Install: uv add openai genai-prices from openai import OpenAI from

A common question we get from students using NetBox Branching is: How can I automatically remove stale branches from NetBox? Therefore, I thought I’d share the latest addition to NetBox Branching, introduced in v1.1.2. This release adds the auto_archive_days setting, allowing you to automatically archive

🐍 Python Tip! Tired of typing uv run every time? Install any Python CLI as a standalone uv tool and call it directly from anywhere, with no venv and no prefix. # Before: prefix every call with `uv run` uv run mytool --help uv run mytool serve # After: install once... uv tool

NetBox Tip! Prevent direct changes to the main branch when using the NetBox Changes plugin. Enable protect_main to ensure all changes are made through branches and follow an approval workflow. Here's an example configuration: # ./configuration.py PLUGINS_CONFIG = { "netbox_changes": { "protect_main": True,

MCP has gained a huge amount of popularity. And for good reason, it's easy to use and can allow you to really harness the benefits of LLMs. So here's a quick MCP tip! Dynamically create MCP servers with FastMCP by passing a REST API's

NetBox/Ansible Tip: The netbox.netbox.nb_inventory plugin pulls data from multiple NetBox API endpoints. Enable caching and disable unused extra lookups to reduce API calls and improve inventory load times. Here’s what you need to add to your NetBox inventory plugin file: # Cache inventory data cache: True

Use uvx to run development tools without adding them to your project dependencies. uvx runs each tool in an isolated, cached environment, keeping your pyproject.toml clean and focused on actual dependencies. Here's an example: # uvx (alias for uv run tool) # Format and lint code without modifying pyproject.

Use .filter() in Config Templates to query objects during lookups and conditional logic. This exposes the Django ORM QuerySet filter directly in your templates. Here's an example: {% for iface in device.interfaces.filter(enabled=True, name__startswith="ge-") %} interface {{ iface.name }} {% endfor %}

OpenAI Tip: If you need structured output from the LLM, use structured responses and define the expected format with JSON Schema. Here’s an example: from openai import OpenAI import os client = OpenAI(api_key=os.getenv("OPENAI_API_KEY")) # Define the exact shape you want back. schema