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job_search_agent

README.md

Job Search Agent with Memory

An AI-powered job search agent that uses ExaAI for intelligent web search and Memori for contextual memory. Built with LangChain for agent orchestration and Streamlit for the user interface.

Features

  • 🔍 Smart Job Search: Uses ExaAI to search across multiple job sites (LinkedIn, Indeed, Glassdoor, Monster, etc.)
  • 🎯 Flexible Filters: Search by job title, location, and work style (Remote/Hybrid/Onsite)
  • 📊 Configurable Results: Choose how many job listings to display (1-20, default: 5)
  • 🔗 Direct Links: Click through directly to job postings to apply
  • 🧠 Memory: Ask questions about your previous job searches using Memori-powered contextual memory
  • 💼 Detailed Listings: View job descriptions, company names, locations, and salary information when available
  • 📄 Resume Upload: Upload your resume to get personalized job recommendations and resume improvement suggestions
  • 🎯 Resume Matching: Ask which jobs you're best suited for based on your resume
  • ✏️ Resume Improvement: Get suggestions on what to add to your resume for specific job positions

Prerequisites

  • Python 3.11 or higher
  • uv package manager (fast Python package installer)
  • ExaAI API key (Get one here)
  • Nebius API key (Get one here)

Installation

1. Install uv

If you don't have uv installed, install it with:

curl -LsSf https://astral.sh/uv/install.sh | sh

Or using pip:

pip install uv

2. Clone and Navigate

git clone https://github.com/Arindam200/awesome-ai-apps/brand-reputation-monitor.git
cd memory_agents/job_search_agent

3. Install Dependencies

Using uv (recommended - much faster):

uv sync

This will:

  • Create a virtual environment automatically
  • Install all dependencies from pyproject.toml
  • Make the project ready to run

4. Set Up Environment Variables

Create a .env file in this directory:

EXA_API_KEY=your_exa_api_key_here
NEBIUS_API_KEY=your_nebius_api_key_here

Usage

Run the Application

Activate the virtual environment and run Streamlit:

# Activate the virtual environment (created by uv)
source .venv/bin/activate  # On macOS/Linux
# or
.venv\Scripts\activate  # On Windows

# Run the app
streamlit run app.py

Or using uv directly:

uv run streamlit run app.py

The app will open in your browser. You can:

  1. Enter API Keys: Add your API keys in the sidebar (or use the .env file)
  2. Upload Resume (optional): Go to the Resume tab to upload your resume for personalized matching
  3. Search Jobs: Go to the Job Search tab and:
    • Enter Job Title (required)
    • Enter Location (optional)
    • Select Work Style (Any/Remote/Hybrid/Onsite)
    • Choose Number of Jobs (1-20, default: 5)
    • Click Search Jobs
  4. View Results: Browse job listings with direct links to apply
  5. Ask Questions: Go to the Memory tab to:
    • Ask about previous searches
    • Get job matching recommendations (if resume uploaded)
    • Get resume improvement suggestions for specific jobs

How It Works

Job Search Flow

  1. Query Building: The app builds a search query from your inputs (job title, location, work style)
  2. ExaAI Search: Uses ExaAI to search across job board domains with intelligent semantic search
  3. Result Processing: Extracts job details (title, company, location, description, salary) using LLM
  4. Display: Shows results in an organized format with clickable links
  5. Memory Storage: Stores search results and job descriptions in Memori for future reference

Memory System

  • Uses Memori to store:
    • Search history and conversations
    • Resume information (if uploaded)
    • Individual job descriptions for matching
  • Ask questions like:
    • "What jobs did I search for?"
    • "Which job am I best suited for with my resume?"
    • "What can I add to my resume to make it fit for Software Engineer at Google?"
    • "What companies did I find for software engineer positions?"
  • The memory system uses contextual embeddings to find relevant past searches and resume data

Resume Matching

When you upload your resume:

  • Resume details are extracted and stored in Memori
  • Job descriptions are stored individually for matching
  • You can ask personalized questions about:
    • Job fit based on your skills
    • Resume improvements for specific positions
    • Skills gaps for target roles

Project Structure

job_search_agent/
├── app.py              # Streamlit interface
├── workflow.py         # LangChain and ExaAI integration
├── resume_parser.py    # Resume parsing and extraction
├── pyproject.toml      # Project dependencies (uv format)
├── README.md           # This file
├── .streamlit/         # Streamlit configuration
│   └── config.toml     # Theme settings
├── assets/             # Logo images
│   ├── Memori_Logo.png
│   └── exa_logo.png
└── memori.db           # Memori database (created automatically)

License

See the main repository LICENSE file.

Contributing

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

Made with ❤️ by Studio1 Team