David DavidMelnychuk

Purpose

Bootstrap knowledge of LLMs ASAP. With a bias/focus to GPT.

Avoid being a link dump. Try to provide only valuable well tuned information.

Neural network links before starting with transformers.

Using newer compiler versions and the optimizer gives gas optimizations and additional safety checks for free!

The advantages of versions 0.8.* over <0.8.0 are:

Safemath by default from 0.8.0 (can be more gas efficient than some library based safemath).
Low level inliner from 0.8.2, leads to cheaper runtime gas. Especially relevant when the contract has small functions. For

🥇 Instead of sending Ether, use the withdrawal pattern

🥈 If you really need to send Ether, use a safe wrapper like OpenZeppelin's Address.sendValue(addr, amount)

🥉 If you really need to send Ether without dependencies, use (bool success, ) = addr.call{value: amount}("")

If you prefer to watch video tutorials with live-coding, then check out this series I recorded with the same contents as in this article: Egghead.io - Introduction to Reactive Programming.

	- I need your answer to be precise, it’s crucial you get them right, I am counting on you!
	- You always think step by step, break down the problem into intermediate steps and communicate to the user which steps you took in order to answer their query
	- If you think you need to execute more steps in order to answer the query, ask the user for confirmation and run more steps
	- Always provide a detailed explanation for your response, including the underlying reasoning and any relevant sources to support your answer.
	Use this format to answer:
	```
	Answer: {answer}
	Internal monologue: {why you answered this way, how you broke down the problem in steps and your train of thought}
	What other questions you might ask: {what kind of followup questions you expect from me? What did I miss?}
	Sources: * {source1} {confidence score about source1, 1 to 10} * {source2} {confidence score about source2, 1 to 10} * {...}

	import { getConfig } from '@expo/config'
	import fs from 'fs'
	import spawnAsync from '@expo/spawn-async'
	import chalk from 'chalk'
	import path from 'path'

	const appDir = process.cwd()

	console.log()
	console.log(chalk.green('Sentry source maps script. Working directory:'))