Merge pull request #586 from Oluwaseyi-A/community-contributions-branch
Add notebook: day1-research-paper-summarizer-with-highlighter
This commit is contained in:
Ed Donner
GitHub
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{
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"cells": [
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{
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"cell_type": "markdown",
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"id": "5c527a13-459e-4a46-b00e-f2c5056de155",
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"metadata": {},
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"source": [
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"# Research Paper Summarizer with Text Highlighting"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"id": "861a0be5-6da7-4f66-8f82-bc083a913f9f",
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"metadata": {},
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"outputs": [],
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"source": [
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"# imports\n",
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"\n",
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"import os\n",
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"import requests\n",
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"from dotenv import load_dotenv\n",
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"from bs4 import BeautifulSoup\n",
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"from IPython.display import Markdown, display\n",
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"from openai import OpenAI"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"id": "74bf6765-53b6-457b-ac2d-0d1afa7fbf8f",
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"API key found and looks good so far!\n"
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]
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}
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],
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"source": [
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"# Load environment variables in a file called .env\n",
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"\n",
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"load_dotenv(override=True)\n",
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"api_key = os.getenv('OPENAI_API_KEY')\n",
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"\n",
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"# Check the key\n",
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"\n",
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"if not api_key:\n",
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" print(\"No API key was found - please head over to the troubleshooting notebook in this folder to identify & fix!\")\n",
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"elif not api_key.startswith(\"sk-proj-\"):\n",
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" print(\"An API key was found, but it doesn't start sk-proj-; please check you're using the right key - see troubleshooting notebook\")\n",
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"elif api_key.strip() != api_key:\n",
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" print(\"An API key was found, but it looks like it might have space or tab characters at the start or end - please remove them - see troubleshooting notebook\")\n",
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"else:\n",
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" print(\"API key found and looks good so far!\")\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 4,
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"id": "227ed7af-d539-4c87-988b-80e6e049c863",
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"metadata": {},
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"outputs": [],
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"source": [
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"openai = OpenAI()\n",
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"\n",
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"# If this doesn't work, try Kernel menu >> Restart Kernel and Clear Outputs Of All Cells, then run the cells from the top of this notebook down.\n",
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"# If it STILL doesn't work (horrors!) then please see the Troubleshooting notebook in this folder for full instructions"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 5,
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"id": "dcaadf8b-456d-48ca-af9d-9f57d3414308",
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"metadata": {},
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"outputs": [],
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"source": [
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"# A class to represent a Webpage\n",
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"# If you're not familiar with Classes, check out the \"Intermediate Python\" notebook\n",
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"\n",
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"# Some websites need you to use proper headers when fetching them:\n",
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"headers = {\n",
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" \"User-Agent\": \"Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/117.0.0.0 Safari/537.36\"\n",
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"}\n",
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"\n",
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"class Website:\n",
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"\n",
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" def __init__(self, url):\n",
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" \"\"\"\n",
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" Create this Website object from the given url using the BeautifulSoup library\n",
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" \"\"\"\n",
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" self.url = url\n",
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" response = requests.get(url, headers=headers)\n",
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" soup = BeautifulSoup(response.content, 'html.parser')\n",
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" self.title = soup.title.string if soup.title else \"No title found\"\n",
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" for irrelevant in soup.body([\"script\", \"style\", \"img\", \"input\"]):\n",
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" irrelevant.decompose()\n",
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" self.text = soup.body.get_text(separator=\"\\n\", strip=True)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 6,
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"id": "6315093f-be68-408e-a5e1-6a2e4ea675e8",
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"metadata": {},
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"outputs": [],
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"source": [
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"def user_prompt_for(website):\n",
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" user_prompt = f\"You are looking at an article website titled {website.title}\"\n",
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" user_prompt += \"\\nThe contents of this website is as follows; \\\n",
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"please provide a short summary of this website in markdown. \\\n",
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"I'm also looking for complete statements containing the following keywords (if found): \\\n",
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"'large circuit model', 'ChipGPT' \\n\\n\"\n",
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" user_prompt += website.text\n",
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" return user_prompt\n",
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"\n",
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"\n",
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"article = Website(\"https://arxiv.org/html/2401.12224v1\")\n",
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"# print(user_prompt_for(article))"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 7,
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"id": "ff8a4112-f118-4866-b6cf-82675de0a38d",
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"metadata": {},
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"outputs": [],
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"source": [
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"system_prompt = \"You are an assistant that analyzes the contents of a scientific \\\n",
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"article for a PhD student (who has to read a lot of papers and journals). The \\\n",
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"user will provide the article website and keyword(s) they are looking to learn and \\\n",
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"cite from. Your job is to summarize the paper and point out all the statements \\\n",
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"containing the specific keyword(s) the user typed. \\\n",
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"Respond in markdown.\"\n",
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"\n",
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"\n",
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"def messages_for(website):\n",
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" return [\n",
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" {\"role\": \"system\", \"content\": system_prompt},\n",
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" {\"role\": \"user\", \"content\": user_prompt_for(website)}\n",
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" ]\n",
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"\n",
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" \n",
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"#messages_for(article)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 8,
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"id": "b5e47bea-403d-48c3-ab9d-4d6adef83241",
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"metadata": {},
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"outputs": [],
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"source": [
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"def summarize(url):\n",
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" website = Website(url)\n",
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" response = openai.chat.completions.create(\n",
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" model = \"gpt-4o-mini\",\n",
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" messages = messages_for(website)\n",
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" )\n",
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" return response.choices[0].message.content\n",
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"\n",
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"\n",
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"def display_summary(url):\n",
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" summary = summarize(url)\n",
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" display(Markdown(summary))"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "9f6ac1bc-5bc8-4daa-8174-d201400e517a",
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"metadata": {},
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"outputs": [],
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"source": [
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"display_summary(\"https://arxiv.org/html/2401.12224v1\")"
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3 (ipykernel)",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.11.13"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 5
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}
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