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[แ„…แ…ตแ„แ…ฎแ„Œแ…ณ]_Prompt_Generation (1).ipynb ADDED
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+ {
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+ "nbformat": 4,
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+ "nbformat_minor": 0,
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+ "metadata": {
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+ "colab": {
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+ "provenance": []
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+ },
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+ "kernelspec": {
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+ "name": "python3",
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+ "display_name": "Python 3"
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+ },
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+ "language_info": {
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+ "name": "python"
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+ }
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+ },
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+ "cells": [
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+ {
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+ "cell_type": "code",
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+ "execution_count": 45,
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+ "metadata": {
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+ "collapsed": true,
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+ "id": "iWfIgUnFg-N6"
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+ },
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+ "outputs": [],
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+ "source": [
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+ "companies = [\"Google\", \"Meta\", \"Amazon\", \"Apple\", \"Tesla\", \"SpaceX\", \"OpenAI\", \"Perplexity\", \"Microsoft\", \"Netflix\", \"Nvidia\"]\n",
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+ "career_stages = [\"Junior\", \"Mid-level\", \"Senior\", \"Staff\"]\n",
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+ "cs_job_types = [\"Software Engineer\", \"Backend Engineer\", \"Frontend Developer\", \"Full Stack Engineer\", \"Machine Learning Researcher\", \"Data Scientist\", \"AI Engineer\", \"DevOps Engineer\", \"Cloud Infrastructure Engineer\", \"Mobile App Developer\", \"Embedded Systems Engineer\", \"Computer Vision Engineer\", \"Natural Language Processing Engineer\", \"Data Engineer\", \"Site Reliability Engineer (SRE)\", \"Database Administrator\", \"Security Engineer\", \"Quality Assurance Engineer (QA)\", \"Systems Engineer\", \"Robotics Engineer\", \"Game Developer\", \"AR/VR Engineer\", \"UI/UX Engineer\", \"Big Data Engineer\", \"Network Engineer\", \"IoT Engineer\", \"Blockchain Engineer\", \"Technical Program Manager\", \"Software Architect\", \"Research Scientist\"]"
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+ ]
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+ },
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+ {
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+ "cell_type": "code",
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+ "source": [
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+ "import uuid\n",
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+ "\n",
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+ "rows = []\n",
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+ "\n",
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+ "for job_type in cs_job_types:\n",
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+ " for career_stage in career_stages:\n",
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+ " for company in companies:\n",
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+ " curr_type_id = str(uuid.uuid4())\n",
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+ " curr_type_str = f\"{job_type}_{career_stage}_{company}\"\n",
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+ " resume_prompt = f\"{company}์—์„œ ์ผํ•˜๋Š” {career_stage} {job_type}์˜ ํ˜„์‹ค์ ์ธ ์ด๋ ฅ์„œ๋ฅผ ์ž‘์„ฑํ•˜๋˜, '์˜ˆ์‹œ', '[์ด๋ฆ„]'๊ณผ ๊ฐ™์€ ์ผ๋ฐ˜์ ์ธ ํ‘œํ˜„์ด๋‚˜ ์ž๋ฆฌ ํ‘œ์‹œ์ž๋Š” ์‚ฌ์šฉํ•˜์ง€ ๋งˆ์„ธ์š”.\\n์ด๋ ฅ์„œ:\"\n",
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+ " jd_prompt = f\"{company}์˜ {career_stage} {job_type} ์ฑ„์šฉ ๊ณต๊ณ ๋ฅผ ์‹ค์ œ์ฒ˜๋Ÿผ ์ž‘์„ฑํ•˜๋˜, ์ผ๋ฐ˜์ ์ธ ๋ฌธ๊ตฌ๋‚˜ ์˜ˆ์‹œ๋Š” ์‚ฌ์šฉํ•˜์ง€ ๋ง๊ณ , ๊ตฌ์ฒด์ ์ด๊ณ  ์ „๋ฌธ์ ์ธ ์–ด์กฐ๋ฅผ ์œ ์ง€ํ•˜์„ธ์š”.\\n์ฑ„์šฉ ๊ณต๊ณ :\"\n",
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+ " rows.append([curr_type_id, curr_type_str, resume_prompt, jd_prompt])"
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+ ],
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+ "metadata": {
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+ "collapsed": true,
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+ "id": "spYKmpjjh19J"
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+ },
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+ "execution_count": 46,
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+ "outputs": []
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+ },
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+ {
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+ "cell_type": "code",
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+ "source": [
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+ "import csv\n",
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+ "with open(\"dataset_creation_prompts.csv\", \"w\", newline=\"\", encoding=\"utf-8-sig\") as csvfile:\n",
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+ " writer = csv.writer(csvfile)\n",
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+ " writer.writerow([\"curr_type_id\", \"curr_type_str\", \"resume_prompts\", \"jd_prompts\"])\n",
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+ " writer.writerows(rows)"
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+ ],
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+ "metadata": {
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+ "id": "YCChD6NQWmhR"
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+ },
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+ "execution_count": 47,
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+ "outputs": []
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+ },
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+ {
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+ "cell_type": "markdown",
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+ "source": [
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+ "number of type: j\n",
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+ "\n",
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+ "number of exp level: e\n",
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+ "\n",
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+ "number of company: c\n",
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+ "\n",
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+ "\n",
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+ "==> total positive combinations: (j X e) X C^2\n",
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+ "\n",
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+ "\n",
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+ "j = 30, e = 4, c = 10\n",
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+ "\n",
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+ "(30 X 4) X 100 = 120 X 100 = 12000 pairs\n",
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+ "\n",
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+ "\n",
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+ "total positive pairs: 12000\n",
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+ "total negative pairs: 12000\n",
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+ "\n",
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+ "\n",
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+ "training with total 24000 pairs\n"
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+ ],
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+ "metadata": {
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+ "id": "hp7C9QIMVQAj"
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+ }
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+ }
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+ ]
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+ }
dataset_creation_prompts (1).csv ADDED
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