Establish a robust testing framework for scalability and reliability

With kubectl-ai recently achieving significant traction, it's crucial to establish a robust and comprehensive testing framework. This will ensure the project's continued stability, reliability, and scalability as we add new features and attract more contributors.

Tasks include but not limited to:

• Comprehensive unit tests: to ensure individual components, functions, and logic are thoroughly tested in isolation. This includes, but is not limited to, command parsing, prompt generation logic, Kubernetes API interaction helpers, output formatting, and utility functions.
• Integration tests: Validate interactions between kubectl-ai's components and its external dependencies where appropriate.
• Mock frameworks that simulate LLM responses to test without real LLMs