import gradio as gr
import pandas as pd
import plotly.graph_objects as go
def compute_return(month_deposit, initial_deposit, interest_rate, years):
    total = initial_deposit
    actual = initial_deposit
    total_values = []
    actual_values = []
    for i in range(years):
        for j in range(12):
            total += month_deposit
            actual += month_deposit
            total = total * (interest_rate/100 + 1)
        total_values.append(total)
        actual_values.append(actual)
    df = pd.DataFrame([[round(total,2), actual, round((total - actual)/actual*100, 2)]], columns=["Total asset", "Actual Investment", "Percentage Return"])
    # add a line plot for total asset with years
    years_range = list(range(1, years+1))
    fig = go.Figure()
    fig.add_trace(go.Scatter(x=years_range, y=total_values, mode='lines', name='Total'))
    fig.add_trace(go.Scatter(x=years_range, y=actual_values, mode='lines', name='Actual'))
    fig.update_layout(title='Evolution of Actual investment and Total asset with Years', xaxis_title='Years', yaxis_title='Amount')
    return df, fig

inputs = [
    gr.Slider(minimum=0, maximum=2000, step=100, value=500, label="Monthly Deposit"),
    gr.Slider(minimum=0, maximum=20000, step=1000, value=500, label="Initial Deposit"),
    gr.Slider(minimum=0, maximum=10, step=0.5, value=1, label="Monthly Return Rate"),
    gr.Slider(minimum=0, maximum=10, step=1, value=1, label="Years")
]

output = [gr.DataFrame(label="Summary"),
          gr.Plot()]

gr.Interface(fn=compute_return, inputs=inputs, outputs=output).launch()