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import pandas as pd
import matplotlib.pyplot as plt
from statsmodels.tsa.arima.model import ARIMA
def forecast_tool(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"
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