An automated Python pipeline that scrapes job postings, uses a multi-stage filtering process to find the most relevant roles, and leverages the Gemini API to tailor your LaTeX resume for the top-ranked positions.

See CONTRIBUTING.md for guidelines on how to contribute to this project.

This project automates the tedious parts of a job search. Instead of manually searching for jobs and customizing your resume for each application, this assistant does it for you. It runs a pipeline that:

1. Scrapes new job postings from multiple sites.
2. Filters them based on your salary, experience, and keywords.
3. Ranks the filtered jobs for relevance against your resume using AI.
4. Tailors your resume's content for the best matches.
5. Delivers the generated PDF resumes to your email.

• Multi-Source Scraping: Gathers job postings from LinkedIn, Indeed, Google, Naukri, and more using jobspy.
• Intelligent Multi-Stage Filtering:
  • Deduplication: Tracks previously processed jobs to avoid duplicates.
  • Salary & Experience: Filters jobs based on your configured salary and experience levels.
  • Keyword Analysis: A fast, initial pass to remove obviously irrelevant senior-level roles.
  • Cosine Similarity: Pre-filters for jobs with descriptions that are mathematically most similar to your resume, saving on expensive API calls.
• Gemini-Powered Analysis:
  • Resume Parsing: Understands your LaTeX resume to create a clean text summary for matching.
  • Job Ranking: Deeply analyzes and ranks the most promising jobs against your professional summary.
  • Content Tailoring: Subtly rephrases and reorders content in your LaTeX resume to align with each top-ranked job description.
• Automated PDF Generation: Compiles the tailored LaTeX source into a polished PDF document.
• Email Notifications: Sends a summary email with all generated resume PDFs attached.
• CI/CD Automation: Includes a GitHub Actions workflow to run the job search on a schedule (e.g., daily).

1. Scrape Jobs
2. Filter out Processed Jobs
3. Filter by Salary and experience keywords
4. Filter by Cosine Similarity (Top 20)
5. Rank Jobs with Gemini (Top 10)
6. For each Top Job:
   • Generate Tailored LaTeX with Gemini
   • Compile to PDF
7. Send Summary Email with tailored resume PDFs
8. Update Processed Jobs Tracker

Follow these steps to set up and run the assistant.

• Python 3.12+: Ensure you have a modern version of Python installed.
• A LaTeX Distribution: The script uses pdflatex to compile .tex files into PDFs. Make sure you have a distribution like MiKTeX (Windows), MacTeX (macOS), or texlive (Linux) installed and available in your system's PATH.
• uv (Optional but Recommended): This project uses uv for package management. You can install it with pip install uv.

1. Clone the repository:

   git clone https://github.com/your-username/ai-job-assistant.git
   cd ai-job-assistant

2. Create a virtual environment and install dependencies:

   # Create the virtual environment
   uv venv
   
   # Install dependencies from the lock file
   uv sync
   
   # OR
   pip install -r requirements.txt

3. Configure Environment Variables: Create a file named .env in the root directory by copying the example. Then, fill in your credentials.

   # .env
   
   # --- Gemini API Key ---
   # Get yours from Google AI Studio: https://makersuite.google.com/app/apikey
   GEMINI_API_KEY="YOUR_GEMINI_API_KEY"
   
   # --- Email Notification Settings ---
   EMAIL_SMTP_HOST="smtp.gmail.com"  # Example for Gmail
   EMAIL_SMTP_PORT="587"
   EMAIL_SENDER_ADDRESS="your_email@gmail.com"
   # IMPORTANT: Use an App Password for security, not your regular password.
   # https://support.google.com/accounts/answer/185833
   EMAIL_SENDER_PASSWORD="your_google_app_password"
   EMAIL_TO="recipient_email@example.com"
   
   # --- (Optional) Zyte Proxy for Scraping ---
   # Not really required, but if your IP gets blocked, you might need a proxy
   # Set USE_PROXIES_IN_WORKFLOW=True in config.py to enable.
   ZYTE_API_KEY="YOUR_ZYTE_API_KEY"

4. Add Your Resume: Place your resume in the root directory and name it source_resume.tex. The assistant will use this as the template for all modifications.

Once configured, you can run the entire pipeline with a single command:

uv run python main.py
# OR
python main.py

The script will print its progress to the console. Generated resumes will be placed in the generated_resumes/ directory, and if email is configured, you will receive a notification.

The primary configuration file is config.py. Open it to tailor the job search to your specific needs.

This repository includes a pre-configured GitHub Actions workflow in .github/workflows/ai-job-assistant.yml.

To enable it:

1. Fork this repository.
2. Go to your new repository's Settings > Secrets and variables > Actions.
3. Add the same keys from your .env file (e.g., GEMINI_API_KEY, EMAIL_SENDER_PASSWORD) as repository secrets.
4. The workflow is configured to run on a schedule (e.g., every day at 10:00 IST). You can adjust the cron schedule in the .yml file.

This project is licensed under the MIT License. See the LICENSE file for details.