{"id":28591372,"url":"https://github.com/chandansoren/ai-based-candidate-screening-system","last_synced_at":"2026-04-14T03:32:54.956Z","repository":{"id":260888302,"uuid":"868082766","full_name":"chandansoren/AI-Based-Candidate-Screening-System","owner":"chandansoren","description":"An intelligent candidate screening solution powered by GPT-3.5, Langchain, and Streamlit. 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This system automates the initial interview process by evaluating candidate responses based on technical knowledge, problem-solving skills, and communication ability.\n\n![download (1)](https://github.com/user-attachments/assets/10ac7391-a63a-4729-9ef3-0ffce38894ae)\n\n\n\n## 🚀 Features\n\n- **Interactive Interview Interface**: Streamlit-based UI for seamless candidate response collection\n- **AI-Powered Evaluation**: Leverages GPT-3.5 through Langchain for comprehensive response analysis\n- **Multi-criteria Assessment**: Evaluates candidates on:\n  - Technical Knowledge\n  - Problem-solving Skills\n  - Communication Ability\n- **Automated Ranking**: Generates candidate rankings based on performance metrics\n- **Real-time Feedback**: Instant evaluation results and insights\n\n## 🛠️ Technical Stack\n\n- **Frontend**: Streamlit\n- **AI Engine**: GPT-3.5\n- **Framework**: Langchain\n- **Language**: Python 3.8+\n\n## 📋 Prerequisites\n\nBefore running the system, ensure you have:\n\n- Python 3.8 or higher installed\n- OpenAI API key\n- Basic understanding of terminal/command line operations\n\n## ⚙️ Installation\n\n1. Clone the repository:\n```bash\ngit clone https://github.com/csoren66/AI-Based-Candidate-Screening-System.git\ncd AI-Based-Candidate-Screening-System\n```\n\n2. Create and activate a virtual environment:\n```bash\npython -m venv venv\nsource venv/bin/activate  # On Windows: venv\\Scripts\\activate\n```\n\n3. Install required dependencies:\n```bash\npip install -r requirements.txt\n```\n\n4. Set up your environment variables:\n```bash\n# Create a .env file and add your OpenAI API key\necho \"OPENAI_API_KEY=your_api_key_here\" \u003e .env\n```\n\n## 🚀 Usage\n\n1. Start the Streamlit application:\n```bash\nstreamlit run app.py\n```\n\n2. Access the application in your web browser (typically http://localhost:8501)\n\n3. Follow the on-screen instructions to:\n   - Input candidate responses\n   - Review evaluation results\n   - Access candidate rankings\n\n## 📊 Evaluation Criteria\n\nThe system evaluates candidates based on the following parameters:\n\n### Technical Knowledge (40%)\n- Understanding of core concepts\n- Technical accuracy\n- Depth of knowledge\n\n### Problem-solving Skills (35%)\n- Analytical thinking\n- Solution approach\n- Innovation and creativity\n\n### Communication Ability (25%)\n- Clarity of expression\n- Structure and organization\n- Professional language use\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fchandansoren%2Fai-based-candidate-screening-system","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fchandansoren%2Fai-based-candidate-screening-system","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fchandansoren%2Fai-based-candidate-screening-system/lists"}