Florent Roques florentroques

brew install ffmpeg $(brew options ffmpeg | grep -vE '\s' | grep -- '--with-' | tr '\n' ' ')

Encoding Video

Installing

Install FFmpeg with homebrew. You'll need to install it with a couple flags for webm and the AAC audio codec.

brew install ffmpeg --with-libvpx --with-libvorbis --with-fdk-aac --with-opus

install ffmpeg with all options on MacOS

brew install ffmpeg $(brew options ffmpeg | grep -vE '\s' | grep -- '--with-' | tr '\n' ' ')

source:https://gist.github.com/Piasy/b5dfd5c048eb69d1b91719988c0325d8#gistcomment-2571754

mov to mp4

ffmpeg -y -i video.mov -c:v libx264 -crf 23 -profile:v baseline \
-c:a aac -strict experimental video.mp4

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.

	import React, { Component } from 'react';
	import { Text, FlatList, View, StyleSheet, Button } from 'react-native';
	import { Constants } from 'expo';

	const TouchableTextConst = props => {
	console.log(`TouchableTextConst${props.id} rendered, callback (re)created :(`);
	const textPressed = () => {
	props.onPressItem(props.id);
	};

	# 1. Install Python
	# Linux: apt-get install python3 (python should already be installed)
	# MacOS: brew install python3 (check homebrew if you do not have it yet)
	# Windows: download Python from Microsoft Store (you can try with chocolatey package manager also)
	# 2. Install PIP, Python package manager
	# Linux: apt-get install pip3
	# MacOS: brew install pip3 (should be installed with Python3 normally, run it in any case)
	# Windows:
	# 3. Install script dependencies
	# pip3 install pygsheets pandas

	"""
	Convert YouTube subtitles(vtt) to human readable text.

	Download only subtitles from YouTube with youtube-dl:
	youtube-dl --skip-download --convert-subs vtt <video_url>

	Note that default subtitle format provided by YouTube is ass, which is hard
	to process with simple regex. Luckily youtube-dl can convert ass to vtt, which
	is easier to process.