This code example demonstrates an resume analysis assistant that evaluates candidate resumes against a specific job description for AI/ML Engineer positions. The assistant analyzes multiple resumes, scores candidates based on various criteria, and provides comprehensive hiring recommendations.

Features

Automatically analyzes all resume PDF files in a specified directory.
Evaluates candidates against a detailed AI/ML Engineer job description.
Scores each candidate on a scale of 1-100 based on:
- Technical skills match (40%)
- Experience relevance (30%)
- Education and qualifications (20%)
- Communication and presentation (10%)
Ranks candidates from most to least qualified.
Highlights strengths and areas for improvement for each candidate.
Generates a comprehensive analysis report in markdown format.

How to use

Set up the Qwen API key in the .env file.

QWEN_API_KEY = 'xxx'

Place resume files (PDF format) in the resumes directory.
Run the script

python run_mcp.py

Review the generated analysis in the resume_analysis.md file.

Technical Implementation

The Resume Assistant uses:

Leverage OWL (Optimized Workforce Learning) and CAMEL frameworks to build the agent.
Use PDF Reader MCP Serverfor extracting content from resume files.
Use Filesystem MCP Server for file operations.

Example Output

The generated resume_analysis.md file includes:

Executive Summary of all candidates
Individual Candidate Assessments with detailed scoring
Ranked List of Candidates from most to least qualified
Recommendations for the Hiring Manager