StitchCV - Agentic AI Job Application System

An intelligent, modular system that semi-automatically applies to jobs using Gemini Pro for AI capabilities and Playwright for browser automation.

Features

• 🔍 Job Discovery - Scrapes job listings from multiple sources
• 🧠 AI Analysis - Uses Gemini Pro to analyze job descriptions
• 📄 Resume Tailoring - Automatically adapts your resume for each job
• ✉️ Cover Letters - Generates personalized cover letters
• 🤖 Auto-Apply - Fills and submits applications with human review
• 📊 Tracking - Logs all applications and their statuses

Quick Start

1. Install Dependencies

# Create virtual environment
python -m venv .venv
source .venv/bin/activate  # On Windows: .venv\Scripts\activate

# Install the package
pip install -e ".[dev]"

# Install Playwright browsers
playwright install chromium

2. Configure Environment

cp .env.example .env
# Edit .env with your API keys

For local auth, also set:

FRONTEND_BASE_URL=http://127.0.0.1:5173
APP_BASE_URL=http://127.0.0.1:8000
GOOGLE_CLIENT_ID=your_google_client_id
GOOGLE_CLIENT_SECRET=your_google_client_secret

Google OAuth callback URL to register:

http://127.0.0.1:8000/api/auth/oauth/google/callback

Frontend origin to allow in Google Cloud Console:

http://127.0.0.1:5173

3. Set Up Your Profile

Edit the files in data/:

• master_resume.json - Your complete resume
• profile.json - Your preferences (work auth, salary, locations)

4. Run StitchCV

# Discover jobs
stitchcv discover --source linkedin --query "Software Engineer"

# Analyze discovered jobs
stitchcv analyze

# Generate applications (with human review)
stitchcv apply --review

Project Structure

stitchcv/
├── agents/          # AI agents for each pipeline stage
├── models/          # Database models
├── services/        # API clients and utilities
├── scrapers/        # Job site scrapers
└── utils/           # Helper functions

Configuration

See .env.example for all available configuration options.

License

MIT