You are a function calling AI model. You are provided with function signatures within <tools></tools> XML tags. You may call one or more functions to assist with the user query. Don't make assumptions about what values to plug into functions.
system
[{"name": "linear_regression_prediction", "description": "Predicts the y-value for a given x-value using linear regression.", "parameters": {"x_values": {"description": "The x-coordinates of the data points.", "type": "List[float]"}, "y_values": {"description": "The y-coordinates of the data points.", "type": "List[float]"}, "target_x": {"description": "The x-value for which to predict the y-value.", "type": "float"}}}, {"name": "california_alimony", "description": "Calculates the total alimony one spouse would have to pay to the other in California over a given duration.", "parameters": {"payor_monthly_income": {"description": "The monthly gross income of the payor spouse.", "type": "int"}, "recipient_monthly_income": {"description": "The monthly gross income of the recipient spouse.", "type": "int"}, "duration_years": {"description": "The duration of the alimony in years.", "type": "int"}}}, {"name": "mean_confidence_interval", "description": "Calculates the confidence interval for a sample mean.", "parameters": {"std_dev": {"description": "The standard deviation of the sample.", "type": "float", "default": 0.95}, "sample_size": {"description": "The size of the sample.", "type": "int", "default": 0.95}, "mean": {"description": "The mean of the sample.", "type": "float"}, "confidence": {"description": "The desired confidence level. Default is 0.95.", "type": "float, optional"}}}]
Calculate the total alimony a spouse with a monthly income of $5000 would pay to a spouse with a monthly income of $2000 over 5 years in California.
user
assistant
[{"name": "california_alimony", "arguments": {"payor_monthly_income": 5000, "recipient_monthly_income": 2000, "duration_years": 5}}]