Goals: Add links that are reasonable and good explanations of how stuff works. No hype and no vendor content if possible. Practical first-hand accounts of models in prod eagerly sought.
![Screenshot 2023-12-18 at 10 40 27 PM](https://private-user-images.githubusercontent.com/3837836/291468646-4c30ad72-76ee-4939-a5fb-16b570d38cf2.png?jwt=eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.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._M0gUuDqDq1qSPEIdf8e31ypW6r07WiOnGFS3Sbd1tk)
#!/bin/bash | |
# Grab oauth token for use with Nitter (requires Twitter account). | |
# results: {"oauth_token":"xxxxxxxxxx-xxxxxxxxx","oauth_token_secret":"xxxxxxxxxxxxxxxxxxxxx"} | |
username="" | |
password="" | |
if [[ -z "$username" || -z "$password" ]]; then | |
echo "needs username and password" | |
exit 1 |
from requests.adapters import HTTPAdapter, Retry | |
from requests import Session | |
retries = Retry( | |
total=5, backoff_factor=1, status_forcelist=[502, 503, 504] | |
) | |
session = Session() # reuse tcp connection | |
session.mount("http://", HTTPAdapter(max_retries=retries)) | |
session.mount("https://", HTTPAdapter(max_retries=retries)) |
# 2023-11-27 MIT LICENSE | |
Here's the open source version of my ChatGPT game MonkeyIslandAmsterdam.com. | |
It's an unofficial image+text-based adventure game edition of Monkey Island in Amsterdam, my home town. | |
Please use it however you want. It'd be nice to see more ChatGPT-based games appear from this. If you get inspired by it, please link back to my X https://x.com/levelsio or this Gist so more people can do the same! | |
Send me your ChatGPT text adventure game on X, I'd love to try it! |
#!/usr/bin/env python | |
# coding: utf-8 | |
# Enable azure speech service: | |
# https://docs.azure.cn/zh-cn/ai-services/speech-service/get-started-speech-to-text?tabs=macos%2Cterminal&pivots=programming-language-python | |
# | |
# Setup environement variables key and region that are found at page | |
# https://portal.azure.com | |
# Home -> Azure AI Service | Speech service -> <your_service_name> | |
# |
@layer base { | |
:root { | |
--flexoki-bg: 48 100% 97%; | |
--flexoki-bg-2: 51 33% 92%; | |
--flexoki-ui: 51 21% 88%; | |
--flexoki-ui-2: 50 14% 83%; | |
--flexoki-ui-3: 55 10% 79%; | |
--flexoki-tx: 0 3% 6%; |
// WARNING:此脚本仅做学习和演示用途,在不了解其用途前不建议使用 | |
// 本脚本的用途是将输入内容分页,每次提取一页内容,编辑第二条消息,发送,然后收集结果 | |
// 使用前,需要有两条消息,参考模板 https://chat.openai.com/share/17195108-30c2-4c62-8d59-980ca645f111 | |
// 演示视频: https://www.bilibili.com/video/BV1tp4y1c7ME/?vd_source=e71f65cbc40a72fce570b20ffcb28b22 | |
// | |
(function (fullText) { | |
const wait = (ms) => new Promise((resolve) => setTimeout(resolve, ms)); | |
const groupSentences = (fullText, maxCharecters = 2800) => { | |
const sentences = fullText.split("\n").filter((line) => line.trim().length > 0); |
[Script Info] | |
Title: How AI Could Empower Any Business | Andrew Ng | TED | |
ScriptType: v4.00+ | |
WrapStyle: 0 | |
Collisions: Reverse | |
PlayResX: 384 | |
PlayResY: 288 | |
Timer: 100.0000 | |
ScaledBorderAndShadow: no |
12th July, 2023. I'm going to try creating an iOS app called Paranovel, using Expo. My environment for mobile app dev (Xcode, Ruby, etc.) should be in reasonably good shape already as I frequently develop with React Native and NativeScript.
Go to https://docs.expo.dev, and see the Quick Start: npx create-expo-app paranovel
This runs with no problem, then I get this macOS system popup:
from langchain.chat_models import ChatOpenAI | |
from pydantic import BaseModel, Field | |
from langchain.document_loaders import UnstructuredURLLoader | |
from langchain.chains.openai_functions import create_extraction_chain_pydantic | |
class LLMItem(BaseModel): | |
title: str = Field(description="The simple and concise title of the product") | |
description: str = Field(description="The description of the product") | |
def main(): |