willurd

Each of these commands will run an ad hoc http static server in your current (or specified) directory, available at http://localhost:8000. Use this power wisely.

Discussion on reddit.

Python 2.x

$ python -m SimpleHTTPServer 8000

1va7

OpenClaw 多 Agent 架构配置指南

把这份指南发给你的 OpenClaw，它会引导你选择最适合的多 Agent 架构。

---

使用说明

当用户把这份文档发给你时，请按照以下流程引导他们选择合适的多 Agent 架构配置。

ossa-ma

AI Writing Tropes to Avoid

Add this file to your AI assistant's system prompt or context to help it avoid common AI writing patterns. Source: tropes.fyi by ossama.is

---

Word Choice

"Quietly" and Other Magic Adverbs

sungminnoh

UX 정의: UI + 스토리텔링

작성일: 2026-03-21
작성자: 노성민

---

1️⃣ 개념 정의

UX(User Experience)란 사용자가 시스템, 애플리케이션, 또는 대시보드를 이용하면서 느끼는 전체적인 경험을 의미합니다.

MuhammadSaim

RAR registration data
WinRAR
Unlimited Company License
UID=4b914fb772c8376bf571
6412212250f5711ad072cf351cfa39e2851192daf8a362681bbb1d
cd48da1d14d995f0bbf960fce6cb5ffde62890079861be57638717
7131ced835ed65cc743d9777f2ea71a8e32c7e593cf66794343565
b41bcf56929486b8bcdac33d50ecf773996052598f1f556defffbd
982fbe71e93df6b6346c37a3890f3c7edc65d7f5455470d13d1190
6e6fb824bcf25f155547b5fc41901ad58c0992f570be1cf5608ba9

kpn-advanced-analytics

As today’s companies strive to become more data driven, reliable analytics and data science has become an essential part of staying competitive and keeping costs under control. Because of this most mid to large companies have created their own analytics or data science teams, or roles, that focus on producing, maintaining and scoring models. These models are essentially pieces of code that use raw data to produce insights or strategies that other teams and management rely on. Because most analytics and data scientist teams create and tune these models by hand, this work is more of a R&D field rather than a bookkeeping one. For this reason, like most R&D products, the models need to be made ready to be run in a stable, reliable and auditable fashion as fast as possible.

What is Model Factory?

Model factory is a framework that helps analytics and data science teams go from a development model to a stable, reliable and auditable production model faster and with less guess work. A model factory is not one so

ryerh

注意：本文内容适用于 Tmux 2.3 及以上的版本，但是绝大部分的特性低版本也都适用，鼠标支持、VI 模式、插件管理在低版本可能会与本文不兼容。

Tmux 快捷键 & 速查表 & 简明教程

启动新会话：

tmux [new -s 会话名 -n 窗口名]

恢复会话：

AlexanderHott

# For an explanation and more advanced setup, see this video from mCding https://www.youtube.com/watch?v=9L77QExPmI0

import logging

logging.config.dictConfig(
    {
        "version": 1,
        "disable_existing_loggers": False,
        "formatters": {
            "simple": {

velvet-shark

OpenClaw after 50 days: all prompts

Companion prompts for the video: OpenClaw after 50 days: 20 real workflows (honest review)

These are the actual prompts I use for each use case shown in the video. Copy-paste them into your agent and adjust for your setup. Most will work as-is or the agent will ask you clarifying questions.

Each prompt describes the intent clearly enough that the agent can figure out the implementation details. You don't need to hand-hold it through every step.

My setup: OpenClaw running on a VPS, Discord as primary interface (separate channels per workflow), Obsidian for notes (markdown-first), Coolify for self-hosted services.

karpathy

"""
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