Developed a Weather Function-Calling Demonstration Notebook for the openai/openai-cookbook repository, focusing on illustrating few-shot prompting techniques for weather-related function calls. Leveraged Jupyter Notebook and Python to create an end-to-end workflow that enables rapid prototyping of function-calling experiments, specifically for querying current temperatures by location. The notebook improved reproducibility and onboarding for users exploring function-calling capabilities within data science and machine learning contexts. By providing experimental examples and clear demonstrations, the work helped clarify how models can interpret and respond to user queries about weather, supporting both educational and practical use cases for function-calling workflows in Python environments.