rjeczalik

How to find forks of a deleted repository?

1. Go to https://cachedview.com/

2. Navigate to the deleted repo, e.g. https://webcache.googleusercontent.com/search?q=cache:https://github.com/apcera/termtables

3. Copy latest known commit sha1 signature

4. Go to https://github.com/search

JacobYZ

From Zero to OpenClaw on Proxmox LXC (Debian 13): A Real-World Build Log

I wanted a self-hosted OpenClaw deployment on Proxmox, reachable on my LAN, with:

• Gemini API key support
• Gemini CLI OAuth (Google AI Pro)
• Telegram bot integration
• Brave Search API integration
• Browser tool support in an LXC
• OpenRouter free model option (without Gemini CLI install)

krisbolton

How to fix a USB drive showing up as two drives (fragmented into multiple partitions) on Windows:

1. Hold the Windows key and press X, select PowerShell (Admin), select Yes to the pop-up. You can also use Command Prompt.
2. In the Powershell interface type diskpart to enter the disk partition tool.
3. Type list disk to see all disks listed.
4. Select the USB drive by typing select disk [NUMBER]. Be careful to select the correct drive.
5. Type clean. An error will occur if you have the drive folder open, close the window and repeat the command if this happens.
6. Type create partition primary.
7. Type format fs=ntfs quick to format the drive (you can also choose to set fs=fat32).
8. Type active.

karpathy

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.

YuriyGuts

#!/usr/bin/env python3
"""
Expose Ollama models to LM Studio by symlinking its model files.
NOTE: On Windows, you need to run this script with administrator privileges.
"""

import json
import os
from pathlib import Path

qoomon

Conventional Commit Messages

See how a minor change to your commit message style can make a difference.

git commit -m"<type>(<optional scope>): <description>" \
  -m"<optional body>" \
  -m"<optional footer>"

Mansitoh

{
  "minecraft:banner_pattern": {
    "minecraft:base": {
      "asset_id": "minecraft:base",
      "translation_key": "block.minecraft.banner.base"
    },
    "minecraft:border": {
      "asset_id": "minecraft:border",
      "translation_key": "block.minecraft.banner.border"
    },

devhammed

<?php

namespace App\Jobs;

use App\Models\Post;
use App\Models\Like;
use App\Models\User;
use App\Notifications\AggregatedLikeNotification;
use App\Notifications\SingleLikeNotification;
use Illuminate\Contracts\Queue\ShouldQueue;

Kartones

PSQL

Magic words:

psql -U postgres

Some interesting flags (to see all, use -h or --help depending on your psql version):

• -E: will describe the underlaying queries of the \ commands (cool for learning!)
• -l: psql will list all databases and then exit (useful if the user you connect with doesn't has a default database, like at AWS RDS)