Goals: Add links that are reasonable and good explanations of how stuff works. No hype and no vendor content if possible. Practical first-hand accounts of models in prod eagerly sought.
| # ----------------------------------------------------------------------------- | |
| # AI-powered Git Commit Function | |
| # Copy paste this gist into your ~/.bashrc or ~/.zshrc to gain the `gcm` command. It: | |
| # 1) gets the current staged changed diff | |
| # 2) sends them to an LLM to write the git commit message | |
| # 3) allows you to easily accept, edit, regenerate, cancel | |
| # But - just read and edit the code however you like | |
| # the `llm` CLI util is awesome, can get it here: https://llm.datasette.io/en/stable/ | |
| gcm() { |
Here's how I configured a GitHub Action so that a new version issued by GitHub's release interface will build a Dockerfile, tag it with the version number and upload it to Google Artifact Registry.
Before you attempt the steps below, you need the following:
| #!/usr/bin/env python3 | |
| # -*- coding: utf-8 -*- | |
| import os | |
| import sys | |
| import argparse | |
| import datetime | |
| def main(): | |
| console_prefix = "$ " |
This is a set up for projects which want to check in only their source files, but have their gh-pages branch automatically updated with some compiled output every time they push.
A file below this one contains the steps for doing this with Travis CI. However, these days I recommend GitHub Actions, for the following reasons:
| #!/bin/sh | |
| TABLE_SCHEMA=$1 | |
| TABLE_NAME=$2 | |
| mytime=`date '+%y%m%d%H%M'` | |
| hostname=`hostname | tr 'A-Z' 'a-z'` | |
| file_prefix="trimax$TABLE_NAME$mytime$TABLE_SCHEMA" | |
| bucket_name=$file_prefix | |
| splitat="4000000000" | |
| bulkfiles=200 |