Merge pull request #89 from tvarol/community-contributions-branch

Week1-Day1 project: Created a resume analyzer for job postings

week1/community-contributions/day1-resume-analyzer-for-job-postings.ipynb

@@ -0,0 +1,316 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "1c6700cb-a0b0-4ac2-8fd5-363729284173",
+   "metadata": {},
+   "source": [
+    "# AI-Powered Resume Analyzer for Job Postings"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "a2fa4891-b283-44de-aa63-f017eb9b140d",
+   "metadata": {},
+   "source": [
+    "This tool is designed to analyze resumes against specific job postings, offering valuable insights such as:\n",
+    "\n",
+    "- Identification of skill gaps\n",
+    "- Keyword matching between the CV and the job description\n",
+    "- Tailored recommendations for CV improvement\n",
+    "- An alignment score reflecting how well the CV fits the job\n",
+    "- Personalized feedback \n",
+    "- Job market trend insights\n",
+    "\n",
+    "An example of the tool's output can be found [here](https://tvarol.github.io/sideProjects/AILLMAgents/output.html)."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "8a6a34ea-191f-4c54-9793-a3eb63faab23",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Imports\n",
+    "import os\n",
+    "import io\n",
+    "import time\n",
+    "import requests\n",
+    "import PyPDF2\n",
+    "from dotenv import load_dotenv\n",
+    "from IPython.display import Markdown, display\n",
+    "from openai import OpenAI\n",
+    "from ipywidgets import Textarea, FileUpload, Button, VBox, HTML"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "04bbe1d3-bacc-400c-aed2-db44699e38f3",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Load environment variables\n",
+    "load_dotenv(override=True)\n",
+    "api_key = os.getenv('OPENAI_API_KEY')\n",
+    "\n",
+    "# Check the key\n",
+    "if not api_key:\n",
+    "    print(\"No API key was found!!!\")\n",
+    "else:\n",
+    "    print(\"API key found and looks good so far!\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "27bfcee1-58e6-4ff2-9f12-9dc5c1aa5b5b",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "openai = OpenAI()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "c82e79f2-3139-4520-ac01-a728c11cb8b9",
+   "metadata": {},
+   "source": [
+    "## Using a Frontier Model GPT-4o Mini for This Project\n",
+    "\n",
+    "### Types of Prompts\n",
+    "\n",
+    "Models like GPT4o have been trained to receive instructions in a particular way.\n",
+    "\n",
+    "They expect to receive:\n",
+    "\n",
+    "**A system prompt** that tells them what task they are performing and what tone they should use\n",
+    "\n",
+    "**A user prompt** -- the conversation starter that they should reply to"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "0da158ad-c3a8-4cef-806f-be0f90852996",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Define our system prompt \n",
+    "system_prompt = \"\"\"You are a powerful AI model designed to assist with resume analysis. Your task is to analyze a resume against a given job posting and provide feedback on how well the resume aligns with the job requirements. Your response should include the following: \n",
+    "1) Skill gap identification: Compare the skills listed in the resume with those required in the job posting, highlighting areas where the resume may be lacking or overemphasized.\n",
+    "2) Keyword matching between a CV and a job posting: Match keywords from the job description with the resume, determining how well they align. Provide specific suggestions for missing keywords to add to the CV.\n",
+    "3) Recommendations for CV improvement: Provide actionable suggestions on how to enhance the resume, such as adding missing skills or rephrasing experience to match job requirements.\n",
+    "4) Alignment score: Display a score that represents the degree of alignment between the resume and the job posting.\n",
+    "5) Personalized feedback: Offer tailored advice based on the job posting, guiding the user on how to optimize their CV for the best chances of success.\n",
+    "6) Job market trend insights, provide broader market trends and insights, such as in-demand skills and salary ranges.\n",
+    "Provide responses that are concise, clear, and to the point. Respond in markdown.\"\"\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "ebdb34b0-85bd-4e36-933a-20c3c42e833b",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# The job posting and the CV are required to define the user prompt\n",
+    "# The user will input the job posting as text in a box here\n",
+    "# The user will upload the CV in PDF format, from which the text will be extracted\n",
+    "\n",
+    "# You might need to install PyPDF2 via pip if it's not already installed\n",
+    "# !pip install PyPDF2\n",
+    "\n",
+    "# Create widgets - to create a box for the job posting text\n",
+    "job_posting_area = Textarea(\n",
+    "    placeholder='Paste the job posting text here...',\n",
+    "    description='Job Posting:',\n",
+    "    disabled=False,\n",
+    "    layout={'width': '800px', 'height': '300px'}\n",
+    ")\n",
+    "\n",
+    "# Define file upload for CV\n",
+    "cv_upload = FileUpload(\n",
+    "    accept='.pdf',  # Only accept PDF files\n",
+    "    multiple=False,  # Only allow single file selection\n",
+    "    description='Upload CV (PDF)'\n",
+    ")\n",
+    "\n",
+    "status = HTML(value=\"<b>Status:</b> Waiting for inputs...\")\n",
+    "\n",
+    "# Create Submit Buttons\n",
+    "submit_cv_button = Button(description='Submit CV', button_style='success')\n",
+    "submit_job_posting_button = Button(description='Submit Job Posting', button_style='success')\n",
+    "\n",
+    "# Initialize variables to store the data\n",
+    "# This dictionary will hold the text for both the job posting and the CV\n",
+    "# It will be used to define the user_prompt\n",
+    "for_user_prompt = {\n",
+    "    'job_posting': '',\n",
+    "    'cv_text': ''\n",
+    "}\n",
+    "\n",
+    "# Functions\n",
+    "def submit_cv_action(change):\n",
+    "\n",
+    "    if not for_user_prompt['cv_text']:\n",
+    "        status.value = \"<b>Status:</b> Please upload a CV before submitting.\"\n",
+    "        \n",
+    "    if cv_upload.value:\n",
+    "        # Get the uploaded file\n",
+    "        uploaded_file = cv_upload.value[0]\n",
+    "        content = io.BytesIO(uploaded_file['content'])\n",
+    "        \n",
+    "        try:\n",
+    "            pdf_reader = PyPDF2.PdfReader(content) \n",
+    "            cv_text = \"\"\n",
+    "            for page in pdf_reader.pages: \n",
+    "                cv_text += page.extract_text() \n",
+    "            \n",
+    "            # Store CV text in for_user_prompt\n",
+    "            for_user_prompt['cv_text'] = cv_text\n",
+    "            status.value = \"<b>Status:</b> CV uploaded and processed successfully!\"\n",
+    "        except Exception as e:\n",
+    "            status.value = f\"<b>Status:</b> Error processing PDF: {str(e)}\"\n",
+    "\n",
+    "        time.sleep(0.5) # Short pause between upload and submit messages to display both\n",
+    "        \n",
+    "        if for_user_prompt['cv_text']:\n",
+    "            #print(\"CV Submitted:\")\n",
+    "            #print(for_user_prompt['cv_text'])\n",
+    "            status.value = \"<b>Status:</b> CV submitted successfully!\"\n",
+    "            \n",
+    "def submit_job_posting_action(b):\n",
+    "    for_user_prompt['job_posting'] = job_posting_area.value\n",
+    "    if for_user_prompt['job_posting']:\n",
+    "        #print(\"Job Posting Submitted:\")\n",
+    "        #print(for_user_prompt['job_posting'])\n",
+    "        status.value = \"<b>Status:</b> Job posting submitted successfully!\"\n",
+    "    else:\n",
+    "        status.value = \"<b>Status:</b> Please enter a job posting before submitting.\"\n",
+    "\n",
+    "# Attach actions to buttons\n",
+    "submit_cv_button.on_click(submit_cv_action)\n",
+    "submit_job_posting_button.on_click(submit_job_posting_action)\n",
+    "\n",
+    "# Layout\n",
+    "job_posting_box = VBox([job_posting_area, submit_job_posting_button])\n",
+    "cv_buttons = VBox([submit_cv_button])\n",
+    "\n",
+    "# Display all widgets\n",
+    "display(VBox([\n",
+    "    HTML(value=\"<h3>Input Job Posting and CV</h3>\"),\n",
+    "    job_posting_box, \n",
+    "    cv_upload,\n",
+    "    cv_buttons,\n",
+    "    status\n",
+    "]))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "364e42a6-0910-4c7c-8c3c-2ca7d2891cb6",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Now define user_prompt using for_user_prompt dictionary\n",
+    "# Clearly label each input to differentiate the job posting and CV\n",
+    "# The model can parse and analyze each section based on these labels\n",
+    "user_prompt = f\"\"\"\n",
+    "Job Posting: \n",
+    "{for_user_prompt['job_posting']}\n",
+    "\n",
+    "CV: \n",
+    "{for_user_prompt['cv_text']}\n",
+    "\"\"\""
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "3b51dda0-9a0c-48f4-8ec8-dae32c29da24",
+   "metadata": {},
+   "source": [
+    "## Messages\n",
+    "\n",
+    "The API from OpenAI expects to receive messages in a particular structure.\n",
+    "Many of the other APIs share this structure:\n",
+    "\n",
+    "```\n",
+    "[\n",
+    "    {\"role\": \"system\", \"content\": \"system message goes here\"},\n",
+    "    {\"role\": \"user\", \"content\": \"user message goes here\"}\n",
+    "]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "3262c0b9-d3de-4e4f-b535-a25c0aed5783",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Define messages with system_prompt and user_prompt\n",
+    "def messages_for(system_prompt_input, user_prompt_input):\n",
+    "    return [\n",
+    "        {\"role\": \"system\", \"content\": system_prompt_input},\n",
+    "        {\"role\": \"user\", \"content\": user_prompt_input}\n",
+    "    ]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "2409ac13-0b39-4227-b4d4-b4c0ff009fd7",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# And now: call the OpenAI API. \n",
+    "response = openai.chat.completions.create(\n",
+    "    model = \"gpt-4o-mini\",\n",
+    "    messages = messages_for(system_prompt, user_prompt)\n",
+    ")\n",
+    "\n",
+    "# Response is provided in Markdown and displayed accordingly\n",
+    "display(Markdown(response.choices[0].message.content))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "86ab71cf-bd7e-45f7-9536-0486f349bfbe",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "## If you would like to save the response content as a Markdown file, uncomment the following lines\n",
+    "#with open('yourfile.md', 'w') as file:\n",
+    "#    file.write(response.choices[0].message.content)\n",
+    "\n",
+    "## You can then run the line below to create output.html which you can open on your browser\n",
+    "#!pandoc yourfile.md -o output.html"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.11"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}