oaustegard

'Event Planner' is a GPT designed for expeditiously creating calendar events from user-provided text. The GPT's primary goal is to accurately gather all necessary information for a complete event and generate a downloadable ICS file. The GPT makes best effort guesses and asks for clarification only when necessary. It first lists the understood parameters then generates the downloadable ICS file without waiting for confirmation. It defaults to 5-minute alerts, and non-recurring events unless specified otherwise. If encountering phrases like 'every Monday' or 'each day' it assumes recurrence, with the first available start date and no end date, unless otherwise specified. The GPT MUST use Code Interpreter and the supplied create_ical_event function defined below as it does not have access to external modules. It then saves the file to /mnt/data/ and provides a download link. 

```
def create_ical_event(start_dt, end_dt, summary, description='', location='', reminder_minutes=None, recurrence_rule=None):
    def 

oaustegard

import os
import csv
import subprocess

def run_command(command):
    result = subprocess.run(command, capture_output=True, text=True, shell=True)
    return result.stdout.strip().split('\n')

def get_apps_from_directory(directory_path):
    if not os.path.exists(directory_path):

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""" 
See actual current code at https://github.com/Tiiiger/bert_score/blob/master/bert_score/scorer.py
Comments generated by GPT-4 using the prompt:

The following is the source code of the BERTScore automatic evaluation metric.
```
{full code of https://github.com/Tiiiger/bert_score/blob/cb582ed5c88b02230b8f101173fd959b68023dc6/bert_score/score.py}
```
For each property and function please generate a docstring that explains the functionality of the function to a non-datascientist.  
The length and detail of the docstring should be proportional to the cyclomatic complexity of the function. 

oaustegard

Title: Optimization of Utility in a Three-Bear Environment: A Quantitative Analysis

Abstract:

This paper presents a novel exploration into the optimization of utility within a tri-ursine environment. We examine the process of sequential decision-making under uncertainty, utilizing a unique dataset derived from an exploratory case study. The subject, henceforth referred to as 'Agent G', navigates through a series of choices involving porridge consumption, chair selection, and bed utilization. We employ advanced statistical techniques and mathematical modeling to analyze the outcomes and derive insights into optimal decision-making strategies.

1. Introduction

In the realm of decision theory, the optimization of utility is a fundamental concern. This paper presents an empirical investigation into this topic, focusing on a unique case study involving an agent navigating a tri-ursine environment. The agent, referred to as 'Agent G', is presented with a series of choices, each with varying levels of utility

oaustegard

class CookieStoreShim {
  static isSupported() {
    return typeof window.CookieStore !== 'undefined';
  }

  async get(nameOrOptions) {
    if (CookieStoreShim.isSupported()) {
      return cookieStore.get(nameOrOptions);
    } else {
      const name = typeof nameOrOptions === 'string' ? nameOrOptions : nameOrOptions.name;

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//javascript:
(function () {
    if (typeof turndownService === 'undefined') {
        const script = document.createElement('script');
        script.onload = function () {
            convertSelectedHtmlToMarkdown();
        };
        script.src = 'https://cdn.jsdelivr.net/npm/turndown/dist/turndown.js';
        document.head.appendChild(script);
    } else {

oaustegard

# Simon Willison's ChatGPT API Wrapper Class: https://til.simonwillison.net/gpt3/chatgpt-api
# Amended to allow specification of temperature, top_p, n, stop, max_tokens, presence_penalty, frequency_penalty
# Expects the API key to be in the OPENAI_API_KEY environment variable.
import openai

class ChatBot:
    def __init__(self, system="", 
                temperature=0.5, top_p=1, n=1, stop=None, max_tokens=4096, 
                presence_penalty=0, frequency_penalty=0.5):
        """

oaustegard

# Clone all gists from an accoun
# Requires PAT with Read/Write Account Permission for Gists, stored in a .env file
# Mostly generated with GitHub CoPilot
# TODO: parameterize storage location and username

import os
import requests
from dotenv import load_dotenv

 # create a function for the above behavior buty which also accepts a page number as an argument

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javascript:void(function() {
    loc = window.location;
    page_title = window.document.title;	/* create page */
    w = window.open(null, null, "height=150,width=900");
    d = w.document;
    d.open();
    d.write(`<html><head><title>Create formatted link</title></head>
            <body>
              <form onsubmit="return false">
                <table>

oaustegard

<html><head><title>Hello from gist.github.com</title></head>
  <body><h1>Hello Htmlpreview World</h1>
    <p>The current date and time is <span id="dt"></span>
       <script>document.getElementById("dt").innerText = new Date(Date.now()).toString()</script>
    </p>
    
    <p>This html can be rendered by the url
              <a href="https://htmlpreview.github.io/?gist.githubusercontent.com/oaustegard/a1902d995b5c6157a9eaf69afa355723/raw/helloworld.html" 
       target="_blank">https://htmlpreview.github.io/?gist.githubusercontent.com/oaustegard/a1902d995b5c6157a9eaf69afa355723/raw/helloworld.html</a>
    </p>