194 lines
7.4 KiB
Plaintext
194 lines
7.4 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 1,
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"id": "a9e05d2a",
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"metadata": {},
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"outputs": [],
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"source": [
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"# ----- (My project)\n",
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"# Date: 09.01.25\n",
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"# Plan: Make a Gradio UI, that lets you pick a job on seek.com, then scape key words and come up with a \n",
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"# plan on how to land jobs of the type selected."
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]
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},
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{
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"cell_type": "markdown",
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"id": "312c3746",
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"metadata": {},
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"source": [
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"# My project"
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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": "394dbcfc",
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"metadata": {},
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"outputs": [],
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"source": [
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"#pip install markdown"
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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": "15f1024d",
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"metadata": {},
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"outputs": [],
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"source": [
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"\n",
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"import os\n",
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"import requests\n",
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"import json\n",
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"from typing import List\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, update_display\n",
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"import gradio as gr\n",
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"import markdown\n",
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"\n",
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"# ---- 1\n",
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"# Initialize and constants & set up Gemini Flash LLM\n",
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"load_dotenv()\n",
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"api_key = os.getenv('GOOGLE_API_KEY')\n",
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"import os\n",
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"import google.generativeai as genai\n",
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"genai.configure(api_key= api_key)\n",
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"# Create the model\n",
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"generation_config = {\n",
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" \"temperature\": 1,\n",
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" \"top_p\": 0.95,\n",
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" \"top_k\": 40,\n",
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" \"max_output_tokens\": 8192,\n",
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" \"response_mime_type\": \"text/plain\",}\n",
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"model = genai.GenerativeModel(model_name=\"gemini-1.5-flash\",\n",
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" generation_config=generation_config,)\n",
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"chat_session = model.start_chat(history=[ ])\n",
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"\n",
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"\n",
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"# ---- 2\n",
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"# A class to represent a Webpage\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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" A utility class to represent a Website that we have scraped, now with links\n",
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" \"\"\"\n",
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"\n",
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" def __init__(self, url):\n",
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" self.url = url\n",
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" response = requests.get(url, headers=headers)\n",
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" self.body = response.content\n",
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" soup = BeautifulSoup(self.body, 'html.parser')\n",
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" self.title = soup.title.string if soup.title else \"No title found\"\n",
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" if soup.body:\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)\n",
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" else:\n",
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" self.text = \"\"\n",
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" links = [link.get('href') for link in soup.find_all('a')]\n",
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" self.links = [link for link in links if link]\n",
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"\n",
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" def get_contents(self):\n",
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" return f\"Webpage Title:\\n{self.title}\\nWebpage Contents:\\n{self.text}\\n\\n\"\n",
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"\n",
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"\n",
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"# ---- 3\n",
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"# Data + set up\n",
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"def get_all_details(url):\n",
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" result = \"Landing page:\\n\"\n",
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" result += Website(url).get_contents()\n",
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" return result\n",
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"\n",
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"system_prompt = \"You are an experience recrutiment and talent management assistant, who will be provided a list of roles on offer.\\\n",
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"You will display those roles along with a high level summary of the key steps you suggest to land those roles. \\\n",
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"Output is to be in markdown (i.e. a professional format, with bold headders, proper spacing between different sections, etc.)\\\n",
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"Include suggested next steps on how to successfully apply for and land each of these jobs.\"\n",
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"\n",
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"def get_brochure_user_prompt(url):\n",
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" user_prompt = f\"Here are the contents of your recruitment search. Please list out individual roles and your best advise on landing those roles.\"\n",
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" user_prompt += f\"Please provide output in a professional style with bold text for headings, content nicely layed out under headings, different content split out into sections, etc.)\\n\"\n",
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" user_prompt += get_all_details(url)\n",
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" #user_prompt = user_prompt[:5_000] # Truncate if more than 5,000 characters\n",
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" user_prompt = user_prompt[:7_500] # Truncate if more than 5,000 characters\n",
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" return user_prompt\n",
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"\n",
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"def create_brochure(url):\n",
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" response = chat_session.send_message(system_prompt + get_brochure_user_prompt(url))\n",
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" result = response.text\n",
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" html_output = markdown.markdown(result)\n",
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" return html_output\n",
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"\n",
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"# ---- 4 \n",
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"# Gradio UI\n",
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"with gr.Blocks(css=\"\"\"\n",
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" #header-container { text-align: left; position: fixed; top: 10px; left: 0; padding: 10px; background-color: #f0f0f0; }\n",
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" #input-container { text-align: left; position: fixed; top: 100px; left: 0; right: 0; background: white; z-index: 100; padding: 8px; line-height: 0.5;}\n",
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" #output-container { margin-top: 160px; height: calc(100vh - 280px); overflow-y: auto; }\n",
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" #output-html { white-space: pre-wrap; font-family: monospace; border: 1px solid #ccc; padding: 5px; line-height: 1.2;}\n",
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" .button-container { margin-top: 10px; } /* Space above the button */\n",
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" .output-label { margin-top: 10px; font-weight: bold; } /* Style for output label */\n",
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"\"\"\") as iface:\n",
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" with gr.Column(elem_id=\"main-container\"):\n",
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" # Add header and description\n",
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" with gr.Row(elem_id=\"header-container\"):\n",
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" gr.Markdown(\"# Job seeker guide\")\n",
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" gr.Markdown(\"1.0 Works best with recruitment site https://www.seek.com.au/ (but can try others).\")\n",
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" gr.Markdown(\"2.0 Search for jobs of your choice, copy URL from that search & paste in input field below to get helpful advice on how to land those roles.\")\n",
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"\n",
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"\n",
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" \n",
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" with gr.Row(elem_id=\"input-container\"):\n",
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" input_text = gr.Textbox(label=\"Input\", elem_id=\"input-box\")\n",
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" \n",
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" with gr.Column(elem_id=\"output-container\"):\n",
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" output_label = gr.Markdown(\"<div class='output-label'>Output:</div>\")\n",
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" output_text = gr.HTML(elem_id=\"output-html\")\n",
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" \n",
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" # Move the button below the output box\n",
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" submit_btn = gr.Button(\"Generate\", elem_id=\"generate-button\", elem_classes=\"button-container\")\n",
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" \n",
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" submit_btn.click(fn=create_brochure, inputs=input_text, outputs=output_text)\n",
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"\n",
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"iface.launch(share=True)\n",
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"\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": null,
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"id": "21c4b557",
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"metadata": {},
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"outputs": [],
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"source": []
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": ".venv",
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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": "3.12.8"
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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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