An intelligent Python application that automatically fetches software engineering jobs from multiple sources, generates engaging captions using Google Gemini AI, creates AI-generated job posting images, and posts them to LinkedIn with optimal timing and engagement tracking.

• Multi-Source Job Fetching: Integrates with RapidAPI (Indeed) and Jooble for comprehensive job listings
• AI-Powered Caption Generation: Uses Google Gemini to create professional, engaging LinkedIn posts
• AI Image Generation: Creates custom job posting images with company logos and job details using Gemini
• LinkedIn Automation: Automated posting via Selenium with anti-detection measures
• Smart Scheduling: Intelligent posting schedule optimization based on engagement analytics
• Database Management: MongoDB support with comprehensive job tracking and analytics
• Deduplication & Filtering: Advanced job matching and filtering by skills, location, and seniority

┌─────────────────┐    ┌──────────────────┐    ┌─────────────────┐
│   Job Sources   │    │  Job Processor   │    │  Caption Gen    │
│                 │    │                  │    │                 │
│ • RapidAPI      │───▶│ • Normalization  │───▶│ • Gemini AI     │
│ • Jooble        │    │ • Deduplication  │    │ • Style Config  │
│                 │    │ • Filtering      │    │ • Hashtags      │
└─────────────────┘    └──────────────────┘    └─────────────────┘
                                │                        │
                                ▼                        ▼
                       ┌──────────────────┐    ┌─────────────────┐
                       │   Database       │    │  Image Gen      │
                       │                  │    │                 │
                       │ • MongoDB       │    │ • Gemini Vision │
                       │ • Collections    │    │ • Company Logos │
                       │ • Indexes       │    │ • Job Details   │
                       │ • Analytics     │    │ • Fallback PIL  │
                       └──────────────────┘    └─────────────────┘
                                │                        │
                                ▼                        ▼
                       ┌──────────────────┐    ┌─────────────────┐
                       │   Scheduler      │    │  Social Poster  │
                       │                  │    │                 │
                       │ • APScheduler    │───▶│ • LinkedIn      │
                       │ • Cron Jobs      │    │ • Selenium      │
                       │ • Timezone       │    │ • Anti-Detection│
                       └──────────────────┘    └─────────────────┘

• Python 3.10+
• MongoDB 5.0+ (local or cloud instance)
• Chrome browser (for LinkedIn automation)
• Google Gemini API key
• RapidAPI key
• Jooble API key
• LinkedIn account credentials

1. Clone the repository

   git clone <repository-url>
   cd job-automation

2. Create virtual environment

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

3. Install dependencies

   pip install -r requirements.txt

4. Setup MongoDB

   • Local MongoDB: Install and start MongoDB service
   • Cloud MongoDB: Use MongoDB Atlas or similar service
   • Update connection string in .env file

5. Configure environment

   cp env.template .env
   # Edit .env with your API keys and credentials

6. Initialize database

   python cli.py init

# MongoDB Configuration
MONGODB_URI=mongodb://localhost:27017
MONGODB_DB=job_automation

# Google Gemini API
GOOGLE_API_KEY=your_gemini_api_key_here

# LinkedIn Credentials
[email protected]
LINKEDIN_PASSWORD=your_linkedin_password

# Job Sources
RAPIDAPI_KEY=your_rapidapi_key_here
JOOBLE_API_KEY=your_jooble_api_key_here

The application uses a YAML configuration file for:

• Job source preferences and API settings
• AI model settings (Gemini configuration)
• Image generation preferences
• Posting schedules and platform settings
• Database configuration
• Logging and monitoring settings

# Initialize database
python cli.py init

# Check system status
python cli.py status

# Manually fetch jobs
python cli.py fetch

# Manually post content
python cli.py post

# Start automated mode
python cli.py start

# Run system tests
python test_system.py

# Test Gemini integration
python test_gemini.py

The application can run in automated mode with:

• Scheduled job fetching (every 6 hours)
• Automated caption generation
• AI image creation
• Scheduled LinkedIn posting (9 AM and 6 PM IST)
• Engagement analytics collection

• Indeed Jobs: Comprehensive job listings with advanced filtering
• Configurable Keywords: Software engineering, Python, ML, Data Science
• Rate Limiting: Respects API limits with intelligent retry logic

• Global Job Aggregator: Access to millions of job listings
• Smart Filtering: Location, skills, and experience-based filtering
• Real-time Updates: Fresh job postings as they become available

• Google Gemini Integration: Advanced AI-powered caption creation
• Professional Style: Business-appropriate tone for LinkedIn
• Hashtag Optimization: Relevant industry hashtags for better reach
• Customizable Templates: Configurable caption styles and lengths

• Gemini Vision: AI-generated job posting images
• Company Branding: Integration with company logos and branding
• Professional Design: Clean, modern layouts for social media
• Fallback System: Pillow-based image generation if AI fails

• Automated Posting: Selenium-based automation with anti-detection
• Image Support: AI-generated job posting images with company branding
• Professional Content: Optimized for LinkedIn's business audience
• Engagement Tracking: Monitor likes, comments, and shares

The application uses several key tables:

• jobs_raw: Raw job data from various sources
• jobs_clean: Processed and normalized job listings
• posts_ready: Generated captions ready for posting
• posted_items: Record of all posted content
• analytics: Engagement metrics and performance data

• Real-time Logging: Comprehensive logging with loguru
• Performance Metrics: Track posting success rates and engagement
• Error Handling: Intelligent retry logic with exponential backoff
• Health Checks: System status monitoring and alerting

1. LinkedIn Login Issues

   • Verify credentials in .env
   • Check for 2FA requirements
   • Ensure account is not locked

2. API Rate Limits

   • Check RapidAPI and Jooble quotas
   • Verify API keys are valid
   • Review rate limiting configuration

3. Database Connection

   • Verify MongoDB service is running
   • Check connection credentials
   • Ensure database exists and is accessible

4. Gemini API Issues

   • Verify GOOGLE_API_KEY is set
   • Check API quota and billing
   • Review model configuration

• Ensure MongoDB service is running
• Verify user permissions and database access
• Check connection string format in .env
• Use python setup_mongodb.py for initial setup

job-automation/
├── cli.py                 # Command line interface
├── orchestrator.py        # Main application orchestrator
├── job_fetchers.py        # Job source integrations
├── job_processor.py       # Job processing and filtering
├── caption_generator.py   # AI caption generation
├── image_generator.py     # AI image generation
├── social_posters.py      # LinkedIn posting automation
├── database.py            # Database management
├── models.py              # Data models
├── config.yaml            # Application configuration
├── requirements.txt       # Python dependencies
├── env.template           # Environment variables template
├── test_system.py         # System testing
├── test_gemini.py         # Gemini API testing
├── setup_mongodb.py       # MongoDB setup automation
└── README.md              # This file

1. Fork the repository
2. Create a feature branch
3. Make your changes
4. Add tests if applicable
5. Submit a pull request

This project is licensed under the MIT License - see the LICENSE file for details.

For issues and questions:

1. Check the troubleshooting section
2. Review the logs in logs/ directory
3. Run system tests: python test_system.py
4. Create an issue with detailed error information