A command-line interface chatbot application that uses OpenAI's GPT-4o-mini model to create an interactive AI assistant experience.
This project demonstrates a simple yet effective implementation of an AI chatbot using Python and the OpenAI API. The application allows users to have natural conversations with an AI assistant through a command-line interface.
- Real-time conversation with GPT-4o-mini
- Conversation history tracking
- Cost calculation for API usage
- Graceful conversation ending
- Python 3.8+
- OpenAI API key
- python-dotenv package
- openai package
- Clone this repository
- Create a
.envfile with your OpenAI API key:OPENAI_API_KEY=your_api_key_here - Run the script:
python main.py - Start chatting with the AI assistant!
- Type "end conversation" to exit the program
Working with AI APIs requires careful handling of authentication credentials. This project demonstrates using environment variables for storing API keys securely.
The way messages are constructed and passed to the model significantly impacts the quality of responses. The conversation history management shows how context can be maintained for more coherent interactions.
AI API calls can be expensive. The cost calculation function illustrates how to monitor and track usage costs, which is critical for production applications.
The project showcases OpenAI's function calling capability, demonstrating how to trigger specific application behaviors (like ending the conversation) through the AI interface.
When working with external AI services, robust error handling is essential for a good user experience, especially when network issues or rate limiting might occur.
Effective AI integration doesn't require complex code. This project demonstrates how powerful functionality can be achieved with clean, well-organized code.