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metadata 
title: SkillSync
emoji: 💼
colorFrom: green
colorTo: green
sdk: docker
app_file: app_new.py
pinned: false

Job Application AI Agent

An intelligent AI-powered tool that automates the job application process by:

  1. Scraping job listings from platforms like LinkedIn
  2. Analyzing job descriptions to extract key requirements
  3. Automatically tailoring your CV to match job requirements
  4. Generating customized cover letters

Features

  • Job Scraping: Automatically search and collect job listings from LinkedIn
  • Intelligent Analysis: Extract key skills and requirements from job descriptions
  • CV Customization: Tailor your CV to highlight relevant skills for each job
  • Batch Processing: Generate multiple tailored CVs for different jobs at once
  • User-Friendly Interface: Simple web interface to control the entire process

Setup

Prerequisites

  • Python 3.8+
  • Node.js 18+ and npm (for the React frontend)
  • Chrome browser (for web scraping)

Installation

  1. Clone this repository:
git clone https://github.com/yourusername/Job-apply-AI-agent.git
cd Job-apply-AI-agent
  1. Run the installation script:
# On Unix-based systems (macOS, Linux)
./install.sh

# On Windows
install.bat
  1. Install frontend dependencies:
cd frontend
npm install
cd ..

Windows: Keep Everything Inside This Project Folder

If your C drive is full, run installation and app commands with local state folders inside this project.

# Run from project root
$env:JOB_APPLY_AI_DATA_DIR = "$PWD\\.runtime"
$env:TMP = "$PWD\\.local_state\\temp"
$env:TEMP = "$PWD\\.local_state\\temp"
$env:PIP_CACHE_DIR = "$PWD\\.local_state\\pip-cache"
$env:PYTHONPYCACHEPREFIX = "$PWD\\.local_state\\pycache"

# First-time setup
./install.bat

# If your Chrome major version is different from auto-detected chromedriver
# (example shown for Chrome 146)
$env:UC_CHROME_VERSION_MAIN = "146"

The project is now configured to keep generated files under local folders such as .runtime and .local_state.

Environment Configuration

Using .env File (Recommended)

A .env file is included with all configuration options. To use Grok API:

  1. Open .env in the project root
  2. Replace your_groq_api_key_here with your actual Groq API key
  3. Save the file

The app will automatically load these settings when you run it.

Use API Tailoring in the Main UI (Optional)

The web UI can run in two modes:

  • CV_TAILORING_MODE=local (default): uses local rule/NLP tailoring in job_apply_ai/
  • CV_TAILORING_MODE=api: uses the API subproject engine in Automatic CV and Cover Letter with API/

When using API mode, set one provider:

# Choose one: ollama | groq  | openai
$env:LLM_PROVIDER = "groq"
$env:GROQ_API_KEY = "your_groq_key_here"
$env:GROQ_MODEL = "llama-3.3-70b-versatile"

# Enable API engine from the same web UI
$env:CV_TAILORING_MODE = "api"

Optional cover letter template path for API mode:

$env:API_COVER_LETTER_TEMPLATE_PATH = "D:\projects\job_search_agent\Job-apply-AI-agent-main\Automatic CV and Cover Letter with API\data\Cover Letter_Imon .docx"

Manual Environment Variables

Or set them in PowerShell before running commands:

$env:LLM_PROVIDER = "grok"
$env:GROK_API_KEY = "your_actual_key_here"
$env:UC_CHROME_VERSION_MAIN = "146"

This will:

  • Create a virtual environment
  • Install all dependencies
  • Download the required spaCy language model
  • Install the package in development mode
  • Keep temporary and cache files in this project folder (Windows install script)

API Cost Notes

  • The main app under job_apply_ai/ does not require a paid LLM API to run.
  • The optional subproject under Automatic CV and Cover Letter with API/ can run with:
    • Free local Ollama (default, slowest)
    • Groq API (fast and cost-effective)
    • Grok API (fast, affordable, free account available)
    • OpenAI API (premium quality, paid)

Usage

Web Interface (React Frontend - SaaS Edition)

The application now includes a modern React frontend with professional SaaS design, Framer Motion animations, and advanced state management.

Quick Start

  1. Install Frontend Dependencies (from project root):
cd frontend
npm install
  1. Start Backend (in one terminal):
# Activate the virtual environment first
source venv/bin/activate  # On Unix-based systems
venv\Scripts\activate.bat  # On Windows

# Start the Flask backend
python -m job_apply_ai.ui.app_new
# Or use the installed command:
job-apply-ai web
  1. Start Frontend (in another terminal):
cd frontend
npm run dev
  1. Open your browser: http://localhost:3000

Features

  • 🎨 Modern SaaS Design - Black & emerald green professional theme
  • ✨ Smooth Animations - Powered by Framer Motion
  • 📊 Smart State Management - Zustand for reactive updates
  • 📱 Fully Responsive - Works on all devices
  • 🔄 Real-time Progress - Batch CV generation tracking
  • 🎯 Workflow Steps - Guided experience from CV upload to generation

Workflow

  1. Upload CV - Upload your base CV template (.docx)
  2. Search Jobs - Find opportunities by keyword and location
  3. Review & Select - Browse matched jobs with extracted skills
  4. Generate CVs - Create tailored CVs with one click
  5. Download - Get all generated CVs as a ZIP file

Building for Production 

cd frontend
npm run build

This creates an optimized build that the Flask backend will serve.

Legacy Web Interface (HTML/Bootstrap)

The original HTML-based interface is still available. To use it, edit job_apply_ai/ui/app.py and ensure it's the active server file.

python -m flask --app job_apply_ai.ui.app run

Then visit: http://localhost:5000

Command Line

The application also provides a command-line interface:

# Scrape job listings
job-apply-ai scrape --keyword "Software Engineer" --location "Berlin" --max-jobs 5

# Generate tailored CVs for all jobs in an Excel file
job-apply-ai batch --cv path/to/cv_template.docx --jobs-file path/to/jobs.xlsx

# Generate a tailored CV for a single job description
job-apply-ai tailor --cv path/to/cv_template.docx --job path/to/job_description.txt

Project Structure

  • job_apply_ai/scraper/: Job listing scraping modules
  • job_apply_ai/cv_modifier/: CV customization functionality
  • job_apply_ai/utils/: Utility functions and helpers
  • job_apply_ai/ui/: User interface components
  • job_apply_ai/outputs/: Output directories for jobs and CVs
    • job_apply_ai/outputs/jobs/: Contains Excel files with job listings
    • job_apply_ai/outputs/cvs/: Contains generated CV files

Testing

For detailed testing instructions, see TESTING_GUIDE.md.

License

MIT

Contributing

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

..venv\Scripts\job-apply-ai.exe web

Set-Location "D:\projects\job_search_agent\Job-apply-AI-agent-main"

$env:PATH = "D:\projects\veloce.tools\node\node-v24.14.1-win-x64;$env:PATH" $env:NPM_CONFIG_CACHE = "$PWD.npm-cache" $env:NPM_CONFIG_PREFIX = "$PWD.npm-prefix"

Set-Location ".\frontend" npm.cmd run dev

Set-Location "D:\projects\job_search_agent\Job-apply-AI-agent-main"

$env:JOB_APPLY_AI_DATA_DIR = "$PWD.runtime" $env:TMP = "$PWD.local_state\temp" $env:TEMP = "$PWD.local_state\temp" $env:PIP_CACHE_DIR = "$PWD.local_state\pip-cache" $env:PYTHONPYCACHEPREFIX = "$PWD.local_state\pycache"

..venv\Scripts\python.exe -m job_apply_ai.ui.app_new