import pandas as pd
import matplotlib.pyplot as plt
from statsmodels.tsa.arima.model import ARIMA
from google.adk.tools import Tool

@Tool(name="forecast_tool", description="Forecast future sales using ARIMA")
def forecast(file_path: str) -> str:
    df = pd.read_csv(file_path)
    df['Month'] = pd.to_datetime(df['Month'])
    df.set_index('Month', inplace=True)
    model = ARIMA(df['Sales'], order=(1, 1, 1))
    model_fit = model.fit()
    forecast = model_fit.forecast(steps=3)
    df_forecast = pd.DataFrame(forecast, columns=['Forecast'])
    df_forecast.plot(title="Sales Forecast", figsize=(10, 6))
    plt.savefig("forecast_plot.png")
    return "Generated forecast_plot.png"