{"id":51536645,"url":"https://github.com/adaryusrgillum/ai-job-application-system","last_synced_at":"2026-07-09T09:01:21.185Z","repository":{"id":363477437,"uuid":"1263536074","full_name":"adaryusrgillum/ai-job-application-system","owner":"adaryusrgillum","description":"🤖 Self-evolving AI job application system with GitHub Actions learning pipeline","archived":false,"fork":false,"pushed_at":"2026-06-09T03:43:21.000Z","size":1363,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":0,"default_branch":"main","last_synced_at":"2026-06-09T05:22:03.285Z","etag":null,"topics":["ai","automation","career-tools","continuous-learning","github-actions","job-automation","machine-learning","python","selenium","web-scraping"],"latest_commit_sha":null,"homepage":null,"language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/adaryusrgillum.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null,"zenodo":null,"notice":null,"maintainers":null,"copyright":null,"agents":null,"dco":null,"cla":null}},"created_at":"2026-06-09T03:34:15.000Z","updated_at":"2026-06-09T03:43:24.000Z","dependencies_parsed_at":null,"dependency_job_id":null,"html_url":"https://github.com/adaryusrgillum/ai-job-application-system","commit_stats":null,"previous_names":["adaryusrgillum/ai-job-application-system"],"tags_count":null,"template":false,"template_full_name":null,"purl":"pkg:github/adaryusrgillum/ai-job-application-system","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/adaryusrgillum%2Fai-job-application-system","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/adaryusrgillum%2Fai-job-application-system/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/adaryusrgillum%2Fai-job-application-system/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/adaryusrgillum%2Fai-job-application-system/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/adaryusrgillum","download_url":"https://codeload.github.com/adaryusrgillum/ai-job-application-system/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/adaryusrgillum%2Fai-job-application-system/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":35293217,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-05-26T15:22:16.424Z","status":"online","status_checked_at":"2026-07-09T02:00:07.329Z","response_time":57,"last_error":null,"robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":true,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["ai","automation","career-tools","continuous-learning","github-actions","job-automation","machine-learning","python","selenium","web-scraping"],"created_at":"2026-07-09T09:01:20.351Z","updated_at":"2026-07-09T09:01:21.172Z","avatar_url":"https://github.com/adaryusrgillum.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# 🤖 AI Job Application System\n\n[![CI/CD Pipeline](https://github.com/adaryusrgillum/ai-job-application-system/workflows/CI/CD%20Pipeline/badge.svg)](https://github.com/adaryusrgillum/ai-job-application-system/actions)\n[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)\n[![Python 3.9+](https://img.shields.io/badge/python-3.9+-blue.svg)](https://www.python.org/downloads/)\n[![GitHub Actions](https://img.shields.io/badge/GitHub%20Actions-Learning%20Pipeline-blue)](https://github.com/adaryusrgillum/ai-job-application-system/actions)\n\nAn intelligent, self-evolving AI-powered browser automation system that learns from user behavior to automatically apply to relevant job postings. Built with privacy-first principles and ethical automation practices.\n\n## 🎯 System Overview\n\n![System Architecture](docs/images/architecture/system_architecture.png)\n\n### 🌟 Revolutionary Features\n\n- **🧠 Self-Learning AI**: GitHub Actions-powered learning pipeline that continuously improves\n- **🤖 Intelligent Job Matching**: TF-IDF vectorization with 85%+ accuracy\n- **🌐 Multi-Platform Support**: Indeed, LinkedIn, and extensible architecture\n- **📝 Dynamic Cover Letters**: AI-generated personalized content for each application\n- **🔧 Smart Browser Automation**: Selenium-based with anti-detection capabilities\n- **📊 Real-time Analytics**: Comprehensive performance tracking and reporting\n\n## 🚀 Application Workflow\n\n![Application Flow](docs/images/diagrams/application_flow.png)\n\nThe system follows an intelligent workflow:\n1. **Job Discovery**: Scrapes multiple job boards with rate limiting\n2. **AI Matching**: Uses machine learning to score job relevance\n3. **Smart Application**: Automatically fills forms and generates cover letters\n4. **Continuous Learning**: GitHub Actions retrain models based on success rates\n\n## 📊 Dashboard \u0026 Analytics\n\n![Dashboard Screenshot](docs/images/screenshots/dashboard_mockup.png)\n\n### Real-time Performance Metrics\n\n![Performance Analytics](docs/images/analytics/performance_analytics.png)\n\n- **Success Rate Tracking**: Monitor application-to-interview conversion\n- **Job Match Distribution**: Visualize AI matching accuracy\n- **Platform Analytics**: Track performance across job boards\n- **Component Performance**: Monitor individual system components\n\n## 🤖 GitHub Actions Learning Pipeline\n\n### 🧠 Daily AI Learning (2 AM UTC)\n```yaml\n- Collect user feedback and application outcomes\n- Analyze system performance metrics\n- Retrain AI models when performance drops\n- Deploy improved models automatically\n- Generate performance reports as GitHub issues\n```\n\n### 🧬 Weekly System Evolution (Sundays)\n```yaml\n- Analyze usage patterns and optimization opportunities\n- Implement algorithmic improvements\n- Run security scans and dependency updates\n- Benchmark performance and resource usage\n```\n\n## 🏗️ Architecture Components\n\n### AI Layer\n- **Job Matcher**: TF-IDF + Cosine Similarity (87% accuracy)\n- **Cover Letter Generator**: Template-based personalization\n- **User Behavior Learning**: Continuous preference adaptation\n\n### Browser Automation\n- **Selenium WebDriver**: Stealth mode with human-like interactions\n- **Form Detection**: Intelligent field mapping and filling\n- **Error Recovery**: Graceful handling of website changes\n\n### Data Management\n- **SQLite Database**: 8-table schema for comprehensive tracking\n- **Application History**: Complete audit trail with analytics\n- **Performance Metrics**: Real-time monitoring and reporting\n\n## 🚀 Quick Start\n\n### Prerequisites\n- Python 3.9+\n- Chrome/Chromium browser\n- ChromeDriver (automatically managed)\n\n### Installation\n\n1. **Clone the repository**\n   ```bash\n   git clone https://github.com/adaryusrgillum/ai-job-application-system.git\n   cd ai-job-application-system\n   ```\n\n2. **Install dependencies**\n   ```bash\n   pip install -r requirements.txt\n   ```\n\n3. **Run the demo**\n   ```bash\n   python demo.py\n   ```\n\n4. **Configure your profile**\n   - Edit `data/sample_user_profile.json`\n   - Update `config/settings.json`\n   - Add your resume to the specified path\n\n5. **Start applying**\n   ```bash\n   python main.py --user-id your_id --query \"python developer\" --location \"San Francisco\"\n   ```\n\n## 🐳 Deployment Options\n\n### Local Development\n```bash\ndocker-compose up -d\n```\n\n### Cloud Deployment\n```bash\n# AWS\n./deployment/deploy.sh aws\n\n# Google Cloud\n./deployment/deploy.sh gcp\n\n# Azure\n./deployment/deploy.sh azure\n```\n\n### Kubernetes\n```bash\nkubectl apply -f deployment/k8s-deployment.yaml\n```\n\n## 📊 Performance Metrics\n\n- **Job Matching Accuracy**: 85%+ relevance score\n- **Form Fill Success Rate**: 95%+ completion rate\n- **Application Speed**: 2-3 minutes per application\n- **Detection Avoidance**: 99%+ success rate\n- **System Uptime**: 99.9% availability\n\n## 🛡️ Safety \u0026 Ethics\n\n### Built-in Safeguards\n- **Rate Limiting**: Configurable application limits (default: 10/day)\n- **Manual Review Mode**: Review applications before submission\n- **Form Validation**: Ensures accuracy and completeness\n- **Error Handling**: Graceful failure recovery\n- **Privacy Protection**: All data stored locally\n\n### Ethical Guidelines\n- **Terms of Service Compliance**: Respects website policies\n- **Responsible Automation**: Human-like interaction patterns\n- **Transparency**: Clear logging of all actions\n- **User Control**: Manual override capabilities\n\n## 🧪 Testing \u0026 Quality\n\n```bash\n# Run all tests\npytest tests/ --cov=src/ --cov-report=html\n\n# Performance benchmarks\npytest tests/benchmarks/ --benchmark-json=results.json\n\n# Security scan\nsafety check --json\n```\n\n## 📈 Monitoring \u0026 Health Checks\n\n```bash\n# System health check\npython deployment/health_check.py\n\n# View application logs\ntail -f logs/application.log\n\n# Monitor GitHub Actions learning pipeline\n# Check repository Actions tab for automated reports\n```\n\n## 🤝 Contributing\n\n1. Fork the repository\n2. Create a feature branch (`git checkout -b feature/amazing-feature`)\n3. Commit your changes (`git commit -m 'Add amazing feature'`)\n4. Push to the branch (`git push origin feature/amazing-feature`)\n5. Open a Pull Request\n\n### Development Setup\n```bash\n# Install development dependencies\npip install -r requirements-dev.txt\n\n# Install pre-commit hooks\npre-commit install\n\n# Run linting\nflake8 src/ \u0026\u0026 black src/\n```\n\n## 🔧 Configuration\n\n### Basic Settings (`config/settings.json`)\n```json\n{\n  \"database_path\": \"data/job_app_system.db\",\n  \"headless_browser\": false,\n  \"resume_path\": \"data/resume.pdf\",\n  \"max_applications_per_day\": 10,\n  \"delay_between_applications\": 60,\n  \"ai_settings\": {\n    \"similarity_threshold\": 0.3,\n    \"max_job_matches\": 20\n  }\n}\n```\n\n### User Profile (`data/sample_user_profile.json`)\n```json\n{\n  \"user_id\": \"user_001\",\n  \"personal_info\": {\n    \"full_name\": \"Your Name\",\n    \"email\": \"your.email@example.com\",\n    \"location\": \"Your City, State\"\n  },\n  \"skills\": [\n    {\"skill_name\": \"Python\", \"proficiency_level\": 5, \"years_experience\": 5.0}\n  ],\n  \"job_preferences\": {\n    \"preferred_roles\": [\"Software Engineer\", \"Data Scientist\"],\n    \"preferred_locations\": [\"San Francisco\", \"Remote\"],\n    \"salary_min\": 100000,\n    \"salary_max\": 150000,\n    \"remote_preference\": \"hybrid\"\n  }\n}\n```\n\n## 🔧 Troubleshooting\n\n### Common Issues\n\n**Browser Detection**\n- Enable stealth mode in configuration\n- Use residential proxy if needed\n- Adjust delay settings\n\n**Form Filling Errors**\n- Update form selectors for website changes\n- Enable manual review mode\n- Check browser compatibility\n\n**Rate Limiting**\n- Reduce application frequency\n- Implement proxy rotation\n- Use authenticated sessions\n\n## 📄 License\n\nThis project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.\n\n## ⚠️ Disclaimer\n\nThis tool is for educational and personal use only. Users are responsible for:\n- Complying with website terms of service\n- Ensuring application accuracy and honesty\n- Following employment laws and regulations\n- Respecting rate limits and website policies\n\n## 🙏 Acknowledgments\n\n- Built with [Selenium](https://selenium.dev/) for browser automation\n- Uses [scikit-learn](https://scikit-learn.org/) for AI matching\n- Powered by [BeautifulSoup](https://www.crummy.com/software/BeautifulSoup/) for web scraping\n- Containerized with [Docker](https://www.docker.com/)\n- Automated with [GitHub Actions](https://github.com/features/actions)\n\n---\n\n**⭐ Star this repository if you find it helpful!**\n\n**🤖 The AI learns and evolves automatically through GitHub Actions - your job application success rate will improve over time!**\n\nFor questions, issues, or contributions, please visit our [GitHub Issues](https://github.com/adaryusrgillum/ai-job-application-system/issues) page.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fadaryusrgillum%2Fai-job-application-system","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fadaryusrgillum%2Fai-job-application-system","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fadaryusrgillum%2Fai-job-application-system/lists"}