user: I've been working on some data analysis and I need to fit a linear regression model. I have these data points with x-coordinates as [1, 2, -3] and corresponding y-coordinates as [4, -5, 6]. I want to understand the relationship between these variables and make a prediction for when x is 10. Can you help me with that?

Available functions:
name: linear_regression
description: Finds the linear regression of a set of points and evaluates it at a given point.
parameters: type: dict
properties: x: type: array
description: The x coordinates of the points.
items: type: integer
y: type: array
description: The y coordinates of the points.
items: type: integer
point: type: integer
description: The point to calculate the linear regression at.
required: x
y
point
name: calculate_slope
description: Calculates the slope of the linear regression line from a set of points.
parameters: type: dict
properties: x: type: array
description: The x coordinates of the points.
items: type: integer
y: type: array
description: The y coordinates of the points.
items: type: integer
required: x
y
name: calculate_intercept
description: Calculates the y-intercept of the linear regression line from a set of points and a given slope.
parameters: type: dict
properties: x: type: array
description: The x coordinates of the points.
items: type: integer
y: type: array
description: The y coordinates of the points.
items: type: integer
slope: type: integer
description: The slope of the linear regression line.
required: x
y
slope
name: predict_value
description: Predicts the value of y given the slope, intercept, and an x value.
parameters: type: dict
properties: slope: type: integer
description: The slope of the linear regression line.
intercept: type: integer
description: The y-intercept of the linear regression line.
x: type: integer
description: The x value to predict the y for.
required: slope
intercept
x

Ground truth function call(s):
linear_regression(x=[1,2,-3],y=[4,-5,6],point=10)