Upload analytics_pipeline.py

agents/analytics_pipeline.py

@@ -0,0 +1,51 @@
+
+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
+
+trend_detector_agent = LlmAgent(
+    name="trend_detector_agent",
+    model="gemini-2.5-pro-exp-03-25",
+    description="Detects trends and anomalies in business data.",
+    instruction="""
+        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]
+)
+
+forecast_agent = LlmAgent(
+    name="forecast_agent",
+    model="gemini-2.5-pro-exp-03-25",
+    description="Forecasts future metrics from time series data.",
+    instruction="""
+        Forecast next 3 months of sales based on historical patterns.
+        Use the forecast tool to generate a visual chart.
+    """,
+    tools=[forecast_tool]
+)
+
+strategy_agent = LlmAgent(
+    name="strategy_agent",
+    model="gemini-2.5-pro-exp-03-25",
+    description="Recommends strategic business decisions.",
+    instruction="""
+        Based on trends and forecasts, suggest optimization strategies
+        across marketing, operations, and finance (ROI, CAC, churn).
+    """
+)
+
+analytics_coordinator = LlmAgent(
+    name="analytics_coordinator",
+    model="gemini-2.5-pro-exp-03-25",
+    description="Coordinates full BI pipeline: trends, forecast, strategy.",
+    instruction="""
+        Run the following:
+        1. Analyze the CSV with trend_detector_agent
+        2. Forecast future metrics using forecast_agent
+        3. Recommend business strategies using strategy_agent
+        Return a full dashboard-style summary.
+    """,
+    sub_agents=[trend_detector_agent, forecast_agent, strategy_agent]
+)