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@XVilka
XVilka / TrueColour.md
Last active July 13, 2026 20:43
True Colour (16 million colours) support in various terminal applications and terminals

THIS GIST WAS MOVED TO TERMSTANDARD/COLORS REPOSITORY.

PLEASE ASK YOUR QUESTIONS OR ADD ANY SUGGESTIONS AS A REPOSITORY ISSUES OR PULL REQUESTS INSTEAD!

@kevin-smets
kevin-smets / iterm2-solarized.md
Last active August 9, 2026 11:54
iTerm2 + Oh My Zsh + Solarized color scheme + Source Code Pro Powerline + Font Awesome + [Powerlevel10k] - (macOS)

Default

Default

Powerlevel10k

Powerlevel10k

@natelandau
natelandau / .bash_profile
Last active June 21, 2026 16:18
Mac OSX Bash Profile
# ---------------------------------------------------------------------------
#
# Description: This file holds all my BASH configurations and aliases
#
# Sections:
# 1. Environment Configuration
# 2. Make Terminal Better (remapping defaults and adding functionality)
# 3. File and Folder Management
# 4. Searching
# 5. Process Management
@kazad
kazad / fourier.html
Created June 25, 2014 19:00
BetterExplained Fourier Example
<html>
<head>
<script src="//cdnjs.cloudflare.com/ajax/libs/underscore.js/1.4.2/underscore-min.js"></script>
<script src="//ajax.googleapis.com/ajax/libs/jquery/1.8.2/jquery.min.js"></script>
<script src="//cdnjs.cloudflare.com/ajax/libs/modernizr/2.6.2/modernizr.min.js"></script>
<script src="//ajax.cdnjs.com/ajax/libs/json2/20110223/json2.js"></script>
<!--
TODO:
@max-mapper
max-mapper / bibtex.png
Last active November 19, 2025 13:01
How to make a scientific looking PDF from markdown (with bibliography)
bibtex.png
@9b
9b / what_runs.py
Created August 26, 2017 03:51
Simple tool to use WhatRuns API to get technologies used on a page. Doesn't submit the page if it's not in the database.
import ast
import datetime
import json
import sys
import requests
import urllib
from tabulate import tabulate
url = "https://www.whatruns.com/api/v1/get_site_apps"
data = {"data": {"hostname": sys.argv[1], "url": sys.argv[1],
@gustavoacm
gustavoacm / ObjectStorage.ipynb
Created May 17, 2021 02:35
Pandas, how to read files and work with dataframes
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import React, { useState, useEffect, useRef, useContext } from 'react';
import VisibilitySensor from 'react-visibility-sensor';
import { el, resolve } from '@elemaudio/core';
import srvb from '@elemaudio/srvb';
import Chrome from '../components/Chrome';
import Article from '../components/Article';
import ResizingCanvas from '../components/ResizingCanvas';
import { RenderContext, RenderContextProvider } from './RenderContext';
{
"apiVersion": "dashboard.grafana.app/v2beta1",
"kind": "Dashboard",
"metadata": {
"name": "claude-code-metrics",
"generation": 12,
"creationTimestamp": "2025-12-10T13:33:56Z",
"labels": {},
"annotations": {}
},

LLM Wiki

A pattern for building personal knowledge bases using LLMs.

This is an idea file, it is designed to be copy pasted to your own LLM Agent (e.g. OpenAI Codex, Claude Code, OpenCode / Pi, or etc.). Its goal is to communicate the high level idea, but your agent will build out the specifics in collaboration with you.

The core idea

Most people's experience with LLMs and documents looks like RAG: you upload a collection of files, the LLM retrieves relevant chunks at query time, and generates an answer. This works, but the LLM is rediscovering knowledge from scratch on every question. There's no accumulation. Ask a subtle question that requires synthesizing five documents, and the LLM has to find and piece together the relevant fragments every time. Nothing is built up. NotebookLM, ChatGPT file uploads, and most RAG systems work this way.