https://github.com/chandansoren/ai-based-candidate-screening-system
An intelligent candidate screening solution powered by GPT-3.5, Langchain, and Streamlit. This system automates the initial interview process by evaluating candidate responses based on technical knowledge, problem-solving skills, and communication ability.
https://github.com/chandansoren/ai-based-candidate-screening-system
gpt-3-5-turbo langchain python3 streamlit
Last synced: 2 months ago
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An intelligent candidate screening solution powered by GPT-3.5, Langchain, and Streamlit. This system automates the initial interview process by evaluating candidate responses based on technical knowledge, problem-solving skills, and communication ability.
- Host: GitHub
- URL: https://github.com/chandansoren/ai-based-candidate-screening-system
- Owner: chandansoren
- Created: 2024-10-05T12:38:02.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2024-11-03T11:05:03.000Z (over 1 year ago)
- Last Synced: 2025-06-11T09:14:41.784Z (about 1 year ago)
- Topics: gpt-3-5-turbo, langchain, python3, streamlit
- Language: Jupyter Notebook
- Homepage:
- Size: 34.2 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# AI-Based Candidate Screening System
An intelligent candidate screening solution powered by GPT-3.5, Langchain, and Streamlit. This system automates the initial interview process by evaluating candidate responses based on technical knowledge, problem-solving skills, and communication ability.
## 🚀 Features
- **Interactive Interview Interface**: Streamlit-based UI for seamless candidate response collection
- **AI-Powered Evaluation**: Leverages GPT-3.5 through Langchain for comprehensive response analysis
- **Multi-criteria Assessment**: Evaluates candidates on:
- Technical Knowledge
- Problem-solving Skills
- Communication Ability
- **Automated Ranking**: Generates candidate rankings based on performance metrics
- **Real-time Feedback**: Instant evaluation results and insights
## 🛠️ Technical Stack
- **Frontend**: Streamlit
- **AI Engine**: GPT-3.5
- **Framework**: Langchain
- **Language**: Python 3.8+
## 📋 Prerequisites
Before running the system, ensure you have:
- Python 3.8 or higher installed
- OpenAI API key
- Basic understanding of terminal/command line operations
## ⚙️ Installation
1. Clone the repository:
```bash
git clone https://github.com/csoren66/AI-Based-Candidate-Screening-System.git
cd AI-Based-Candidate-Screening-System
```
2. Create and activate a virtual environment:
```bash
python -m venv venv
source venv/bin/activate # On Windows: venv\Scripts\activate
```
3. Install required dependencies:
```bash
pip install -r requirements.txt
```
4. Set up your environment variables:
```bash
# Create a .env file and add your OpenAI API key
echo "OPENAI_API_KEY=your_api_key_here" > .env
```
## 🚀 Usage
1. Start the Streamlit application:
```bash
streamlit run app.py
```
2. Access the application in your web browser (typically http://localhost:8501)
3. Follow the on-screen instructions to:
- Input candidate responses
- Review evaluation results
- Access candidate rankings
## 📊 Evaluation Criteria
The system evaluates candidates based on the following parameters:
### Technical Knowledge (40%)
- Understanding of core concepts
- Technical accuracy
- Depth of knowledge
### Problem-solving Skills (35%)
- Analytical thinking
- Solution approach
- Innovation and creativity
### Communication Ability (25%)
- Clarity of expression
- Structure and organization
- Professional language use