solaris33

# -*- coding: utf-8 -*-

# 절대 임포트 설정
from __future__ import absolute_import
from __future__ import print_function

# 필요한 라이브러리들을 임포트
import collections
import math
import os

kyo504

package com.your.package.name;

import android.widget.Toast;
import android.app.Activity;

import com.facebook.react.bridge.NativeModule;
import com.facebook.react.bridge.ReactApplicationContext;
import com.facebook.react.bridge.ReactContext;
import com.facebook.react.bridge.ReactContextBaseJavaModule;
import com.facebook.react.bridge.ReactMethod;

rokugasenpai

ツイキャス

• 要rtmpdump

• 生
  石川典行の配信を例に取る。
  http://twitcasting.tv/streamserver.php?mode=view&appid=TCViewerFlash&rtmp=1&target=icchy8591
  レスポンス　例　edge101.moi.st/publisher/214392821-f554a8fe319b8e13.stream?is_publisher=0:1935:GET :icchy8591:214392821
  rtmpdump -r "rtmp://edge101.moi.st/publisher/214392821-f554a8fe319b8e13.stream" -y "publisher/214392821-f554a8fe319b8e13.stream?is_publisher=0" -y icchy8591 -o output.flv
  コメント　初回　例　http://twitcasting.tv/noriyukicas/userajax.php?c=listupdate&m=212328387
  mは放送ID

harrydrippin

# -*- coding: utf-8 -*-
# 수치해석, 김상철 교수님
# 1. Incremental Search, Bisection, False Position,
#    Newton-Raphson, Secant Method 정리
# 20163179 홍승환

import numpy as np
import math
from scipy.optimize import fsolve

puilp0502

[Unit]
Description=uWSGI Emperor service

[Service]
RuntimeDirectory=uwsgi
RuntimeDirectoryMode=755
User=emperor
Group=www-data
ExecStart=/usr/local/bin/uwsgi --emperor /etc/uwsgi/sites
Restart=always

puilp0502

[uwsgi]

# Django-related settings
# the base directory (full path)
chdir           = /home/ubuntu/(project-dir)
# Django's wsgi file
module          = (project-name).wsgi:application
# the virtualenv (full path)
home            = /home/ubuntu/.venv/(venv-name)/

puilp0502

#!/bin/bash

# uWSGI & nginx installation script
# Created at 2017-06-27 by Frank Yang (https://github.com/puilp0502)
# Tested on Ubuntu Server 16.04 LTS

# Check if user is root
if [[ $UID -ne '0' ]]; then
	echo "This script needs to be run as root; exiting..."
	exit 0

allieus

from django.conf import settings
settings.configure(USE_I18N=False)

from django import forms
from rest_framework import serializers


class PostForm(forms.Form):
    email = forms.EmailField()

vanpelt

from app import db
from sqlalchemy import func
from sqlalchemy.dialects.mysql import insert

def upsert(model, insert_dict):
    """model can be a db.Model or a table(), insert_dict should contain a primary or unique key."""
    inserted = insert(model).values(**insert_dict)
    upserted = inserted.on_duplicate_key_update(
        id=func.LAST_INSERT_ID(model.id), **{k: inserted.inserted[k]
                               for k, v in insert_dict.items()})

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.