job_finder_agent

Job Search Agent with Bright Data and Nebius Token Factory

A powerful AI-powered job search agent that analyzes LinkedIn profiles and finds relevant job opportunities using Bright Data for web scraping and Nebius Token Factory for intelligent analysis.

Features

• LinkedIn Profile Analysis

  • Professional experience and career progression
  • Education and certifications
  • Core skills and expertise
  • Industry reputation

• Intelligent Job Matching

  • Domain classification (Software Engineering, Design, Product Management, etc.)
  • Y Combinator job board integration
  • Personalized job recommendations
  • Direct application links

• Modern Web Interface

  • Real-time analysis
  • Interactive results display
  • Progress tracking
  • Error handling

How it Works

Prerequisites

Before running this project, make sure you have:

• Python 3.10 or higher
• A Bright Data account and API credentials
• Nebius Token Factory account and API key

Project Structure

job_finder_agent/
├── app.py              # Streamlit web interface
├── job_agents.py       # AI agent definitions and analysis logic
├── mcp_server.py       # Bright Data MCP server management
├── requirements.txt    # Python dependencies
├── assets/            # Static assets (images, GIFs)
└── .env              # Environment variables (create this)

Installation

1. Clone the repository:

git clone https://github.com/Arindam200/awesome-ai-apps.git
cd advance_ai_agents/job_finder_agent

2. Create a virtual environment:

python -m venv venv
source venv/bin/activate  # On Windows, use: venv\Scripts\activate

3. Install dependencies:

# Using pip
pip install -r requirements.txt

# Or using uv (recommended)
uv sync

Configuration

Create a .env file in the project root with:

NEBIUS_API_KEY="Your Nebius API Key"
BRIGHT_DATA_API_KEY="Your Bright Data API Key"
BROWSER_AUTH="Your Bright Data Browser Auth"

Usage

1. Start the application:

streamlit run app.py

2. Open your browser at http://localhost:8501

3. Enter your Nebius API key in the sidebar

4. Input a LinkedIn profile URL to analyze

5. Click "Analyze Profile" and wait for results

How It Works

1. Profile Analysis: The LinkedIn Profile Analyzer agent extracts key information from the provided LinkedIn profile.

2. Domain Classification: The Job Suggestions agent identifies the primary professional domain and confidence score.

3. Job Matching: The system searches Y Combinator's job board for relevant positions based on the identified domain.

4. URL Processing: Job application URLs are processed to provide direct application links.

5. Summary Generation: A comprehensive report is generated with profile analysis, skill assessment, and job recommendations.

Technical Details

• Uses Streamlit for the web interface
• Implements asynchronous processing with asyncio
• Leverages Bright Data's MCP server for web scraping
• Utilizes Nebius Token Factory's Llama-3.3-70B-Instruct model for analysis
• Implements proper error handling and logging

Contributing

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

Acknowledgments

• Bright Data for web scraping capabilities
• Nebius Token Factory for AI model access
• Streamlit for the web interface framework