Professional CLI Chatbot

A sophisticated command-line chatbot designed for professional interview scenarios.

Features

✅ Professional Interface: Clean, polished CLI with rich formatting ✅ Interview Assistance: Built-in knowledge base for interview questions ✅ Natural Language Processing: Sentiment analysis and keyword extraction ✅ Conversation Management: History tracking and context awareness ✅ Extensible Architecture: Modular design for easy customization ✅ Configuration Support: Environment variables and .env files ✅ Error Handling: Robust exception management ✅ Security: Input validation and sanitization

Installation

Prerequisites

• Python 3.8+
• pip (Python package manager)

Install from source

# Clone the repository
git clone https://github.com/sutharson20069/cli-chatbot.git
cd cli-chatbot

# Create a virtual environment (recommended)
python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

# Install dependencies
pip install -r requirements.txt

# Install the package
pip install -e .

Install via pip (when published)

pip install cli-chatbot

Usage

Basic Usage

# Start the chatbot
chatbot

Available Commands

• General Chat: Just type your message and press Enter
• help: Show help information
• about: Show information about the chatbot
• clear: Clear the conversation history
• config: Show current configuration
• version: Show version information
• exit/quit/bye: Exit the chatbot

Example Session

🤖 Professional CLI Chatbot

Interview Assistant v1.0.0

A sophisticated command-line chatbot designed for professional interview scenarios.

*Type 'exit', 'quit', or 'bye' to end the session*
*Type 'help' for available commands*

You: hello
Chatbot: Hi there! What would you like to discuss?

You: I have a job interview tomorrow
Chatbot: Can you explain your experience with Python?

You: tell me about behavioral questions
Chatbot: Tell me about a time you worked in a team.

You: exit
👋 Thank you for using Professional CLI Chatbot. Goodbye!

Configuration

Environment Variables

Create a .env file by copying .env.example:

cp .env.example .env

Then edit the .env file to customize your settings.

Available Configuration Options

Variable	Default	Description
CHATBOT_THEME	default	UI theme
CHATBOT_VERBOSE	false	Verbose logging
CHATBOT_MAX_HISTORY	10	Maximum conversation history
CHATBOT_LANGUAGE	english	Language setting
CHATBOT_DEBUG	false	Debug mode
CHATBOT_LOG_LEVEL	INFO	Logging level
CHATBOT_LOG_FILE	chatbot.log	Log file path

Development

Project Structure

cli-chatbot/
├── chatbot/                  # Main package
│   ├── __init__.py           # Package initialization
│   ├── cli.py                # Command-line interface
│   ├── core.py               # Core chatbot logic
│   ├── config.py             # Configuration management
│   └── utils.py              # Utility functions
├── setup.py                  # Package setup
├── requirements.txt          # Dependencies
├── .env.example             # Example configuration
├── LICENSE                   # MIT License
└── README.md                 # Documentation

Running Tests

# Install development dependencies
pip install -r requirements.txt
pip install pytest black flake8 mypy isort

# Run tests
pytest

# Run linting
black .
flake8 .
mypy .
isort .

Building and Distribution

# Build the package
python setup.py sdist bdist_wheel

# Upload to PyPI (requires twine)
pip install twine
twine upload dist/*

Architecture

Core Components

1. CLI Interface (cli.py): Handles user interaction and display
2. Core Logic (core.py): Contains chatbot intelligence and conversation management
3. Configuration (config.py): Manages settings and environment variables
4. Utilities (utils.py): Helper functions for common tasks

Design Patterns

• MVC-like Architecture: Separation of interface, logic, and data
• Singleton Pattern: Configuration management
• Factory Pattern: Response generation
• Observer Pattern: Event handling (future extension)

Contributing

Contributions are welcome! Please follow these guidelines:

1. Fork the repository
2. Create a feature branch: git checkout -b feature/your-feature
3. Commit your changes: git commit -m 'Add some feature'
4. Push to the branch: git push origin feature/your-feature
5. Open a pull request

Code Style

• Follow PEP 8 guidelines
• Use type hints
• Write docstrings for all public functions
• Include tests for new features
• Keep functions small and focused

License

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

Support

For issues, questions, or suggestions, please open an issue on GitHub.

Roadmap

• Basic CLI interface
• Core chatbot logic
• Configuration management
• Interview question knowledge base
• Advanced NLP integration
• Plugin system for extensibility
• Multi-language support
• Conversation persistence
• API integration for external services

Author

Sutharson - GitHub - sutharsonmohan@gmail.com

Acknowledgments

• Thanks to all contributors and users
• Inspired by professional interview preparation tools
• Built with Python and modern CLI libraries