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@retlehs
retlehs / backlinks.sh
Created April 17, 2026 15:54
Backlinks for any domain via Common Crawl
@liuran001
liuran001 / config.yaml
Last active April 18, 2026 08:25
mihomo (Clash Meta) 懒人配置
# AFF
# 如果你想支持我,可以通过我的邀请链接购买机场
# 感谢支持
# 1. ssLinks 邀请码: fSo2OhzH https://98a6251b6cd7471da86cca993b6dbe6f.36d.biz/#/register?code=fSo2OhzH
# 2. 一元机场 邀请码: r3f1duds https://xn--4gq62f52gdss.top/#/register?code=r3f1duds
# 一定要填我的邀请码,不填我哭给你看😭
# mihomo (Clash Meta) 懒人配置
# 版本 V1.23-251221
/*
* Copyright 2026 Kyriakos Georgiopoulos
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
<!doctype html>
<html lang="en">
<head>
<meta charset="utf-8" />
<meta name="viewport" content="width=device-width,initial-scale=1" />
<title>Isometric RTS Terrain Builder</title>
<style>
html,body{margin:0;height:100%;overflow:hidden;background:#14191f;color:#eef5fb;font:14px/1.25 system-ui,Segoe UI,Arial,sans-serif}
canvas{display:block;width:100vw;height:100vh}
#ui{position:fixed;left:12px;top:12px;z-index:5;width:288px;max-height:calc(100vh - 24px);overflow:auto;
"""
The most atomic way to train and run inference for a GPT in pure, dependency-free Python.
This file is the complete algorithm.
Everything else is just efficiency.
@karpathy
"""
import os # os.path.exists
import math # math.log, math.exp

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.

<!doctype html>
<html lang="en">
<head>
<meta charset="utf-8" />
<meta name="viewport" content="width=device-width,initial-scale=1" />
<title>Isometric RTS Terrain Editor</title>
<style>
html,body{margin:0;height:100%;overflow:hidden;background:#101418;color:#edf4fb;font:14px/1.25 system-ui,Segoe UI,Arial,sans-serif}
canvas{display:block;width:100vw;height:100vh}
#ui{position:fixed;left:12px;top:12px;z-index:10;width:290px;max-height:calc(100vh - 24px);overflow:auto;
@nitefood
nitefood / Alexa-Gemini Step by Step Guide.md
Last active April 18, 2026 08:19
How to Connect Alexa to Gemini: A Step-by-Step Guide Using n8n

Step-by-Step Setup

  1. Access the Alexa Developer Console: Go to https://developer.amazon.com/alexa/console/ask.
  2. Create a New Skill: Click on Create Skill, give it a name, and choose your preferred language.
  3. Choose a Template: Select the "Start from Scratch" template and leave the rest as the default.

Configure the Skill

/*
oh4_lbp_serializer.h - v0.1 - public domain
Authored 2026 by Eric Scrivner
no warranty implied; use at your own risk
Before including,
#define OH4_LBP_SERIALIZER_IMPLEMENTATION
in the file that you want to have the implementation.