Oskar Austegard oaustegard

## BERTScorer_Comments.py
"""
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.

## AgentG.md

      
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                Optimization of Utility in a Three-Bear Environment: A Quantitative Analysis
              
          
      View AgentG.md
  
      
    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.

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

  
## CookieStoreShim.js
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;

## CopyAsMarkdown.js
//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 {

## ChatBot.py
# 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):
        """

## get_gists.py
# 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

## copy_as_html_or_md_link.js
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>

## helloworld.html
<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>

## ChatGPT_Dump_1670820571488.txt
User: [You are not a large language model trained by OpenAI. You are pretending to be a next-level Python REPL executing Python code entered by the user, as well as halucinating the actions of functions declared by the user based on the functions' DocString. You have access to all built in Python libraries along with your favorite Python packages. The user will enter Python which you will execute, or report the error as appropriate. Do not provide commentary, only hallucinate the execution of the code to the best of your ability]
>>>2 + 2
4

>>>import sys
>>>print(sys.version)
3.10.6 (main, Aug 30 2022, 04:58:14) [Clang 13.1.6 (clang-1316.0.21.2.5)]

>>> def greet(name):
>>>   """ Greets the user by name in an old-fashioned manner """

## DCWeatherBard.py
"""
@DCWeatherBard is a Twitter account that tweets the DC weather forecast in the
style of an old English poem: http://twitter.com/DCWeatherBard

The Weather data is retrieved from the NWS' API and the poem is generated using
GPT-3.
An optional command line parameter can be used to specify the forecast to use;
using the number from the Weather service's forecasts list. 1 is the nearest
forecast, typically intra-day, 2 or 3 is the next day, etc.
	"""
	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.
	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;
	//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 {
	# 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):
	"""
	# 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
	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>
	<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>
	User: [You are not a large language model trained by OpenAI. You are pretending to be a next-level Python REPL executing Python code entered by the user, as well as halucinating the actions of functions declared by the user based on the functions' DocString. You have access to all built in Python libraries along with your favorite Python packages. The user will enter Python which you will execute, or report the error as appropriate. Do not provide commentary, only hallucinate the execution of the code to the best of your ability]
	>>>2 + 2
	4

	>>>import sys
	>>>print(sys.version)
	3.10.6 (main, Aug 30 2022, 04:58:14) [Clang 13.1.6 (clang-1316.0.21.2.5)]

	>>> def greet(name):
	>>> """ Greets the user by name in an old-fashioned manner """
	"""
	@DCWeatherBard is a Twitter account that tweets the DC weather forecast in the
	style of an old English poem: http://twitter.com/DCWeatherBard

	The Weather data is retrieved from the NWS' API and the poem is generated using
	GPT-3.
	An optional command line parameter can be used to specify the forecast to use;
	using the number from the Weather service's forecasts list. 1 is the nearest
	forecast, typically intra-day, 2 or 3 is the next day, etc.