Upload 3 files

tools/csv_parser.py

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+
+import pandas as pd
+from google.adk.tools import Tool
+
+@Tool(name="parse_csv_tool", description="Parse and summarize business CSV data")
+def parse_csv(file_path: str) -> str:
+    df = pd.read_csv(file_path)
+    return f"Schema: {list(df.columns)}\n\nStats:\n{df.describe().to_string()}"

tools/forecaster.py

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+
+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"

tools/plot_generator.py

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+
+import pandas as pd
+import matplotlib.pyplot as plt
+from google.adk.tools import Tool
+
+@Tool(name="plot_sales_tool", description="Plot sales trend over time")
+def plot_sales(file_path: str) -> str:
+    df = pd.read_csv(file_path)
+    if 'Month' not in df.columns or 'Sales' not in df.columns:
+        return "Missing 'Month' or 'Sales' columns."
+    plt.figure(figsize=(10, 6))
+    plt.plot(df['Month'], df['Sales'], marker='o')
+    plt.xticks(rotation=45)
+    plt.title("Sales Trend")
+    plt.savefig("sales_plot.png")
+    return "Generated sales_plot.png"