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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.

"""
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
// This is a basic uniswap frontrunning MEV bot
// Made by Merunas follow me on youtube to see how to use it and edit it: https://www.youtube.com/channel/UCJInIwgW1duAEnMHHxDK7XQ
// 1. Setup ethers, required variables, contracts and start function
const { Wallet, ethers } = require('ethers')
const { FlashbotsBundleProvider, FlashbotsBundleResolution } = require('@flashbots/ethers-provider-bundle')
// 1.1 Setup ABIs and Bytecodes
const UniswapAbi = [{"inputs":[{"internalType":"address","name":"_factory","type":"address"},{"internalType":"address","name":"_WETH","type":"address"}],"stateMutability":"nonpayable","type":"constructor"},{"inputs":[],"name":"WETH","outputs":[{"internalType":"address","name":"","type":"address"}],"stateMutability":"view","type":"function"},{"inputs":[{"internalType":"address","name":"tokenA","type":"address"},{"internalType":"address","name":"tokenB","type":"address"},{"internalType":"uint256","name":"amountADesired","type":"uint256"},{"internalType":"uint256","name":"amountBDesire
@ih2502mk
ih2502mk / list.md
Last active May 15, 2026 02:47
Quantopian Lectures Saved
@alotaiba
alotaiba / google_speech2text.md
Created February 3, 2012 13:20
Google Speech To Text API

Google Speech To Text API

Base URL: https://www.google.com/speech-api/v1/recognize
It accepts POST requests with voice file encoded in FLAC format, and query parameters for control.

Query Parameters

client
The client's name you're connecting from. For spoofing purposes, let's use chromium

lang
Speech language, for example, ar-QA for Qatari Arabic, or en-US for U.S. English