Update agents/analytics_pipeline.py

agents/analytics_pipeline.py

@@ -1,9 +1,7 @@
-
 from google.adk.agents import LlmAgent
-from tools.csv_parser import parse_csv_tool
-from tools.plot_generator import plot_sales_tool
-from tools.forecaster import forecast_tool
+from tools import csv_parser, plot_generator, forecaster
 
+# Define the agents using raw function references as tools
 trend_detector_agent = LlmAgent(
     name="trend_detector_agent",
     model="gemini-2.5-pro-exp-03-25",
@@ -12,7 +10,10 @@ trend_detector_agent = LlmAgent(
         Analyze the input table. Identify major trends, seasonal patterns,
         and anomalies (spikes or drops). Return a concise summary.
     """,
-    tools=[parse_csv_tool, plot_sales_tool]
+    tools=[
+        csv_parser.parse_csv_tool,
+        plot_generator.plot_sales_tool
+    ]
 )
 
 forecast_agent = LlmAgent(
@@ -23,7 +24,9 @@ forecast_agent = LlmAgent(
         Forecast next 3 months of sales based on historical patterns.
         Use the forecast tool to generate a visual chart.
     """,
-    tools=[forecast_tool]
+    tools=[
+        forecaster.forecast_tool
+    ]
 )
 
 strategy_agent = LlmAgent(
@@ -36,6 +39,7 @@ strategy_agent = LlmAgent(
     """
 )
 
+# Parent coordinator that orchestrates all sub-agents
 analytics_coordinator = LlmAgent(
     name="analytics_coordinator",
     model="gemini-2.5-pro-exp-03-25",
@@ -47,5 +51,9 @@ analytics_coordinator = LlmAgent(
         3. Recommend business strategies using strategy_agent
         Return a full dashboard-style summary.
     """,
-    sub_agents=[trend_detector_agent, forecast_agent, strategy_agent]
+    sub_agents=[
+        trend_detector_agent,
+        forecast_agent,
+        strategy_agent
+    ]
 )