Sweep: update the readme.md that describe the project for furture working on it

[21hook]

Checklist

• README.md ✅ Commit 6b7b4ca

• Add a title for the project at the top of the README.md file. • Write a brief description of the project, explaining that it is a chat application that allows users to upload and parse PDF files. • Add a section titled "Installation" and provide step-by-step instructions for how to install and run the project. • Add a section titled "Project Structure" and provide an overview of the main components of the project, such as the frontend and backend code. • Add a section titled "Features" and describe the main functionalities of the project, such as the chat feature and the PDF parsing feature. • Add a section titled "Technologies" and list the main technologies and libraries used in the project, such as React, Flask, and OpenAI's GPT-3.

Sandbox Execution Logs

trunk init 1/3 ✅

⡿ Downloading Trunk 1.15.0...
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⡿ Verifying Trunk sha256...
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✔ 15 linters were enabled (.trunk/trunk.yaml)
  bandit 1.7.5 (4 python files)
  black 23.9.1 (4 python files)
  checkov 2.4.9 (2 docker, 2 json, 2 yaml files)
  git-diff-check (26 files)
  hadolint 2.12.0 (2 docker files) (created .hadolint.yaml)
  isort 5.12.0 (4 python files) (created .isort.cfg)
  markdownlint 0.36.0 (1 markdown file) (created .markdownlint.yaml)
  osv-scanner 1.4.0 (2 lockfile files)
  oxipng 8.0.0 (1 png file)
  prettier 3.0.3 (1 css, 1 html, 2 javascript, 1 json, 1 markdown, 2 yaml files)
  ruff 0.0.289 (4 python files) (created ruff.toml)
  terrascan 1.18.3 (2 docker files)
  trivy 0.45.0 (2 docker, 2 lockfile, 2 yaml files)
  trufflehog 3.56.0 (27 files)
  yamllint 1.32.0 (2 yaml files) (created .yamllint.yaml)
Next Steps
 1. Read documentation
    Our documentation can be found at https://docs.trunk.io
 2. Get help and give feedback
    Join the Trunk community at https://slack.trunk.io

trunk fmt README.md 2/3 ✅

Checked 1 file
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trunk check --fix README.md 3/3 ✅

Checked 1 file
✔ No issues

[sweep-ai-deprecated]

Here's the PR! #8.

⚡ Sweep Free Trial: I used GPT-4 to create this ticket. You have 1 GPT-4 tickets left for the month and 2 for the day. For more GPT-4 tickets, visit our payment portal. To retrigger Sweep, edit the issue.

---

Step 1: 📍 Planning

I found the following snippets in your repository. I will now analyze these snippets and come up with a plan.

Some code snippets I looked at (click to expand). If some file is missing from here, you can mention the path in the ticket description.

chatpdf/src/App.js

Lines 107 to 289 in 4f4ba73

	<img src={content.picUrl} alt="" />
	</Bubble>
	);
	case "file":
	return <FileCard file={content.file} />;
	case "list":
	return (
	<List bordered={true}>
	{content.list.map((item) => (
	<ListItem
	key={item}
	content={item}
	onClick={function () {
	handleSend("text", item);
	// appendMsg({
	// type: "text",
	// content: { text: item },
	// position: "right"
	// });
	}}
	/>
	))}
	</List>
	);
	default:
	return null;
	}
	}
	function handleQuickReplyClick(item) {
	handleSend("text", item.name);
	}
	// Only apply to toolbar event
	function handleToolbarClick(item, ctx) {
	// console.log(item, ctx);
	if (item.type === "image") {
	const file = document.createElement("input");
	file.setAttribute("accept", "image/*");
	file.type = "file";
	file.click();
	file.onchange = function () {
	console.log(file.files[0]);
	const reader = new FileReader();
	reader.readAsDataURL(file.files[0]);
	reader.onload = function (e) {
	// console.log(e.target.result);
	appendMsg({
	type: "image",
	content: {
	picUrl: reader.result
	},
	position: "right"
	});
	};
	const formData = new FormData();
	// Append the file
	formData.append("image", file.files[0]);
	};
	} else if (item.type === "file") {
	// console.log(item, ctx);
	/** 上传文件 */
	// 调用原生 input[type=file] 上传文件
	const file = document.createElement("input");
	file.setAttribute("accept", ".text,.pdf,.docx");
	file.type = "file";
	file.multiple = true;
	file.click();
	// 触发 onchange 事件
	file.onchange = function () {
	appendMsg({
	type: "file",
	content: {
	file: file.files[0]
	},
	position: "right"
	});
	const formData = new FormData();
	// Append the files
	for (let i = 0; i < file.files.length; i++) {
	formData.append("file", file.files[i]);
	}
	// request for upload
	fetch('http://localhost:8000/file', {
	fetch('http://localhost:8000/pdf', {
	method: 'POST',
	body: formData,
	}).then(res => res.json())
	.then(data => {
	appendMsgList(data.message.content)
	})
	.catch((err) => {
	console.log(err);
	})
	// Mock responses from Apis
	// let text =
	// "Summary: The text provides instructions for using Conda, a platform for managing packages and environments in Python. It includes commands for verifying and updating Conda, creating and managing environments, exporting and importing environments, and installing packages. The text also mentions Anaconda Navigator, a graphical user interface for managing Conda. Finally, it provides additional resources for support and training.\n\nQuestions:\n1. What is Conda?\n2. What are some of the commands for managing environments in Conda?\n3. What is Anaconda Navigator?\n4. What are some additional resources for support and training related to Conda?\n5. How can you update all packages within an environment using Conda?";
	// appendMsgList(text);
	};
	}
	}
	// Only apply to the input event
	function handleSend(type, val) {
	console.log(type, val);
	if (type === "text" && val.trim()) {
	if (val === "reset") {
	window.location.reload();
	} else if (val === "clear") {
	resetList();
	} else {
	// Add the new chat to chatHistory before calling fetch
	setChatHistory([...chatHistory, {role: "user", content: val}]);
	if (chatHistory.length > 10) {
	setChatHistory(chatHistory.slice(1));
	}
	appendMsg({
	type: "text",
	content: { text: val },
	position: "right"
	});
	fetch('http://localhost:8000/chat', {
	method: 'POST',
	headers: {
	"Content-Type": "application/json",
	},
	body: JSON.stringify({
	message: val
	}),
	}).then(res => res.json())
	.then(data => {
	// Add the response from the API to chatHistory
	setChatHistory([...chatHistory, {role: "assistant", content: data.message.content.trim()}]);
	if (chatHistory.length > 10) {
	setChatHistory(chatHistory.slice(1));
	}
	appendMsg({
	type: "text",
	content: { text: data.message.content.trim()},
	user: {
	avatar: ChatGPT
	}
	});
	setQuickRepliesVisible(true);
	})
	.catch((err) => {
	console.log(err);
	})
	// Mock responses from Apis
	// setTimeout(() => {
	// appendMsg({
	// type: "text",
	// content: { text: "Bala bala" },
	// user: {
	// avatar: ChatGPT
	// }
	// });
	// }, 1000);
	}
	}
	}
	return (
	<Chat
	// navbar={{ title: "智能助理" }}
	placeholder={""}
	messages={messages}
	renderMessageContent={renderMessageContent}
	quickReplies={defaultQuickReplies}
	quickRepliesVisible={quickRepliesVisible}
	onQuickReplyClick={handleQuickReplyClick}
	toolbar={toolbar}
	onToolbarClick={handleToolbarClick}
	onSend={handleSend}
	locale="en-US"
	/>
	);

chatpdf/service/utils/api.py

Lines 1 to 66 in 4f4ba73

	import openai
	openai.api_key = "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"
	# Global variable to store the chat history
	chat_history = []
	# Call the openai API with gpt-3.5-turbo
	# Give me a wrapper on this api calling
	def call_gpt(prompt):
	# Include the chats in chat_history in the messages parameter
	messages = [
	{"role": chat["role"], "content": chat["content"]} for chat in chat_history
	]
	messages.append({"role": "user", "content": prompt})
	response = openai.ChatCompletion.create(
	model="gpt-3.5-turbo",
	messages=messages,
	temperature=0.7,
	max_tokens=256,
	top_p=1,
	frequency_penalty=0,
	presence_penalty=0,
	# stream= True
	)
	answer = response.choices[0]
	# Add the new chat and the response to chat_history
	chat_history.append({"role": "user", "content": prompt})
	chat_history.append({"role": "assistant", "content": answer["message"]["content"]})
	# If the size of chat_history exceeds 10, remove the oldest chat
	while len(chat_history) > 10:
	chat_history.pop(0)
	return answer
	# Test code:
	# prompt = "What is the meaning of life?"
	# print("Response:", call_gpt(prompt))
	# Call the openai API with text-davinci-003
	# Give me a wrapper on this api calling
	def call_davinci(message):
	response = openai.Completion.create(
	model="text-davinci-003",
	prompt="Summarize this text: " + message + ", and return the summary.",
	temperature=0.7,
	max_tokens=256,
	top_p=1,
	frequency_penalty=0,
	presence_penalty=0,
	)
	completion = response.choices[0]
	return completion
	# Test code:
	# text = 'Jupiter is the fifth planet from the Sun and the largest in the Solar System. It is a gas giant with a mass one-thousandth that of the Sun, but two-and-a-half times that of all the other planets in the Solar System combined. Jupiter is one of the brightest objects visible to the naked eye in the night sky, and has been known to ancient civilizations since before recorded history. It is named after the Roman god Jupiter.[19] When viewed from Earth, Jupiter can be bright enough for its reflected light to cast visible shadows,[20] and is on average the third-brightest natural object in the night sky after the Moon and Venus.'
	# print('Response: ', call_davinci(text))
	# Fine-tune the GPT model with the prompt and answer

chatpdf/public/index.html

Lines 1 to 45 in 4f4ba73

	<!DOCTYPE html>
	<html lang="en">
	<head>
	<meta charset="utf-8" />
	<meta
	name="viewport"
	content="width=device-width, initial-scale=1, user-scalable=0, minimum-scale=1, maximum-scale=1, viewport-fit=cover"
	/>
	<meta name="theme-color" content="#000000" />
	<!--
	manifest.json provides metadata used when your web app is added to the
	homescreen on Android. See https://developers.google.com/web/fundamentals/engage-and-retain/web-app-manifest/
	-->
	<link rel="manifest" href="%PUBLIC_URL%/manifest.json" />
	<link rel="shortcut icon" href="%PUBLIC_URL%/favicon.ico" />
	<!--
	Notice the use of %PUBLIC_URL% in the tags above.
	It will be replaced with the URL of the `public` folder during the build.
	Only files inside the `public` folder can be referenced from the HTML.
	Unlike "/favicon.ico" or "favicon.ico", "%PUBLIC_URL%/favicon.ico" will
	work correctly both with client-side routing and a non-root public URL.
	Learn how to configure a non-root public URL by running `npm run build`.
	-->
	<title>React App</title>
	<script src="https://g.alicdn.com/chatui/icons/0.2.7/index.js" id="external-js"></script>
	</head>
	<body>
	<noscript>
	You need to enable JavaScript to run this app.
	</noscript>
	<div id="root"></div>
	<!--
	This HTML file is a template.
	If you open it directly in the browser, you will see an empty page.
	You can add webfonts, meta tags, or analytics to this file.
	The build step will place the bundled scripts into the <body> tag.
	To begin the development, run `npm start` or `yarn start`.
	To create a production bundle, use `npm run build` or `yarn build`.
	-->
	<script src="//g.alicdn.com/chatui/icons/0.3.0/index.js"></script>
	</body>

chatpdf/service/app.py

Lines 1 to 77 in 4f4ba73

	import os
	import io
	from flask import Flask, request
	from flask_cors import CORS, cross_origin
	from werkzeug.utils import secure_filename
	from utils.parse import parse_pdf
	from utils.parse_docx import parse_docx
	from utils.api import call_gpt, call_davinci
	@app.route('/file', methods=['POST'])
	app = Flask(__name__)
	CORS(app, origins="http://localhost:3000")
	@app.route('/')
	def hello_world():
	return 'Hello, World!'
	# Define a post method to parse a pdf file
	# Set cors to allow the request from the frontend
	@app.route('/pdf', methods=['POST'])
	@cross_origin()
	def upload_pdf():
	# Get the file uploads from the request
	files = request.files.getlist('pdf')
	for file in files:
	# Save the file to the upload folder
	filename = secure_filename(file.filename)
	file.save(os.path.join(app.config['UPLOAD_FOLDER'], filename))
	for file in files:
	# Save the file to the upload folder
	filename = secure_filename(file.filename)
	file.save(os.path.join(app.config['UPLOAD_FOLDER'], filename))
	# Get the text from the file
	# Parse the file based on its extension
	if filename.endswith('.pdf'):
	text = parse_pdf(os.path.join(app.config['UPLOAD_FOLDER'], filename))
	elif filename.endswith('.docx'):
	text = parse_docx(os.path.join(app.config['UPLOAD_FOLDER'], filename))
	# Call with the davinci
	# response = call_davinci(message=text)
	# Call with the gpt-3.5-turbo and append the response to a list
	responses = []
	for file in files:
	message = f"""
	Summarize this text: {text}, and return the summary.
	And alose give me a series of questions about information, insights, and suggestions related to this file.
	Please give me the related questions in the next line.
	"""
	response = call_gpt(prompt=message)
	responses.append(response)
	# return responses with json format
	return {'responses': responses}
	# Open-ended chat with gpt-3.5-turbo
	@app.route('/chat', methods=['POST'])
	@cross_origin()
	def chat_with_gpt():
	text = request.json['message']
	print(text)
	response = call_gpt(prompt=text)
	return response
	if __name__ == '__main__':
	app.config['UPLOAD_FOLDER'] = 'upload'
	# Listen on the localhost
	# conditions for dev & prod env
	if os.environ.get('FLASK_ENV') == 'dev':
	app.run(host='localhost', debug=True, port=8000)
	else:
	app.run(host='0.0.0.0', port=8000)

---

Step 2: ⌨️ Coding

• README.md ✅ Commit 6b7b4ca

• Add a title for the project at the top of the README.md file. • Write a brief description of the project, explaining that it is a chat application that allows users to upload and parse PDF files. • Add a section titled "Installation" and provide step-by-step instructions for how to install and run the project. • Add a section titled "Project Structure" and provide an overview of the main components of the project, such as the frontend and backend code. • Add a section titled "Features" and describe the main functionalities of the project, such as the chat feature and the PDF parsing feature. • Add a section titled "Technologies" and list the main technologies and libraries used in the project, such as React, Flask, and OpenAI's GPT-3.

Sandbox Execution Logs

trunk init 1/3 ✅

⡿ Downloading Trunk 1.15.0...
⡿ Downloading Trunk 1.15.0...
⢿ Downloading Trunk 1.15.0...
⣻ Downloading Trunk 1.15.0...
⣽ Downloading Trunk 1.15.0...
⣾ Downloading Trunk 1.15.0...
⣷ Downloading Trunk 1.15.0...
✔ Downloading Trunk 1.15.0... done
⡿ Verifying Trunk sha256...
✔ Verifying Trunk sha256... done
⡿ Unpacking Trunk...
✔ Unpacking Trunk... done























✔ 15 linters were enabled (.trunk/trunk.yaml)
  bandit 1.7.5 (4 python files)
  black 23.9.1 (4 python files)
  checkov 2.4.9 (2 docker, 2 json, 2 yaml files)
  git-diff-check (26 files)
  hadolint 2.12.0 (2 docker files) (created .hadolint.yaml)
  isort 5.12.0 (4 python files) (created .isort.cfg)
  markdownlint 0.36.0 (1 markdown file) (created .markdownlint.yaml)
  osv-scanner 1.4.0 (2 lockfile files)
  oxipng 8.0.0 (1 png file)
  prettier 3.0.3 (1 css, 1 html, 2 javascript, 1 json, 1 markdown, 2 yaml files)
  ruff 0.0.289 (4 python files) (created ruff.toml)
  terrascan 1.18.3 (2 docker files)
  trivy 0.45.0 (2 docker, 2 lockfile, 2 yaml files)
  trufflehog 3.56.0 (27 files)
  yamllint 1.32.0 (2 yaml files) (created .yamllint.yaml)
Next Steps
 1. Read documentation
    Our documentation can be found at https://docs.trunk.io
 2. Get help and give feedback
    Join the Trunk community at https://slack.trunk.io

trunk fmt README.md 2/3 ✅

Checked 1 file
✔ No issues

trunk check --fix README.md 3/3 ✅

Checked 1 file
✔ No issues

---

Step 3: 🔁 Code Review

Here are my self-reviews of my changes at sweep/update-readme.

Here is the 1st review

Thank you for your contribution. However, there are still some sections that need to be added to the README.md file.

Please add the following sections to the README.md file:

• A brief description of the project
• Instructions for how to install and run the project
• An overview of the project's structure and main components
• A description of the main functionalities of the project
• A list of the main technologies and libraries used in the project

These sections are crucial for other developers or users to understand the purpose and functionality of the project.

Keep up the good work!

I finished incorporating these changes.

---

🎉 Latest improvements to Sweep:

• Getting Sweep to run linters before committing! Check out Sweep Sandbox Configs to set it up.
• Added support for self-hosting! Check out Self-hosting Sweep to get started.
• [Self Hosting] Multiple options to compute vector embeddings, configure your .env file using VECTOR_EMBEDDING_SOURCE

---

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