import streamlit as st
import numpy as np
from sklearn.linear_model import LinearRegression

# Sample training data (Experience vs. Salary)
data = {
    "experience": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10],
    "salary": [30000, 35000, 40000, 45000, 50000, 55000, 60000, 65000, 70000, 75000, 80000]
}

# Train a simple linear regression model
X = np.array(data["experience"]).reshape(-1, 1)
y = np.array(data["salary"])
model = LinearRegression()
model.fit(X, y)

# Streamlit app
def main():
    st.title("Salary Prediction Application")
    st.write("This application predicts your salary based on your experience.")

    # Input from user
    experience = st.number_input("Enter your experience (in years):", min_value=0, max_value=50, value=0, step=1)

    # Predict salary
    predicted_salary = model.predict([[experience]])[0]

    # Display prediction
    st.header(f"Predicted Salary: ${predicted_salary:,.2f}")

if __name__ == "__main__":
    main()