yaart 1.0.0

Yet Another AI Resume Tool

YAART - Yet Another AI Resume Tool

Python package that leverages AI to automatically tailor your resume to specific job descriptions, optimizing your resume content to highlight relevant skills and experiences.

Features:

• Generates editable Markdown files so you can modify the AI-optimized resume.
• LLM-powered scraper for pulling job descriptions.
• Supports custom CSS styles when generating a PDF resume.
• Stores all jobs in a sqllite database so you can track your applications.
• Leverages Pydantic output parsing for consistent generation.
• Intended to be plug-and-play with different models - succesfully tested with o1-preview, gpt-4o, and claude-3-5-sonnet-20241022

Note: I built this for my own use - sharing in case it is useful to others.

Installation

pip install yaart

Quick Start

1. Create base_resume.md following the sample.md template in the Markdown folder

import asyncio
import os
from pathlib import Path
from langchain_openai import ChatOpenAI
from yaart import optimize_resume

# Job description text (optional if providing URL)
jd_text = """
Optional text in case the scraper fails...
"""

async def main():
    # Initialize LLM (GPT-4 Optimized)
    llm = ChatOpenAI(
        model="gpt-4o",  # GPT-4 Optimized is default
        temperature=0.2,
        api_key=os.getenv("OPENAI_API_KEY")
    )
    
    result = await optimize_resume(
        llm=llm,
        company="ExampleCorp",
        jd_url="https://example.com/job-posting",
        base_resume_path="path/to/base_resume.md",
        jd_string=jd_text,  # Optional, will scrape from URL if not provided
        output_dir=Path("output")  # Optional, defaults to current directory
    )
    
    print(f"Generated files:")
    print(f"Markdown: {result['markdown_path']}")
    print(f"PDF: {result['pdf_path']}")
    print(f"Role: {result['role']}")

if __name__ == "__main__":
    asyncio.run(main())

3. (Optional) If you want to modify your generated markdown resume, find it in the generated Markdown directory. Once you would like to generate a PDF from it, run the following:

from md2pdf.core import md2pdf

if __name__ == "__main__":
    md2pdf("PDF/sample.pdf",
        md_file_path="Markdown/sample.md",
        css_file_path="styles.css",
    )

Prerequisites

• Python 3.8+
• LangChain compatible LLM (OpenAI, Anthropic, etc.)
• Base resume in markdown format

How It Works

1. Job Description Analysis:

   • Extracts key requirements, skills, and responsibilities
   • Structures information into standardized format
   • Caches parsed results in local SQLite database

2. Resume Optimization:

   • Matches skills and experience with job requirements
   • Prioritizes relevant achievements
   • Incorporates key technical terms and phrases
   • Maintains professional tone and factual accuracy

3. Output Generation:

   • Creates tailored Markdown version
   • Generates styled PDF using custom CSS
   • Preserves original resume structure

License

MIT

Contributing

Contributions welcome! Please feel free to submit a Pull Request.