Update app.py

app.py

@@ -30,12 +30,17 @@ class AnomalyDetectionAgent:
         anomalies = iso_forest.fit_predict(data_scaled)
         return anomalies == -1
         
-def plot_data(data, title):
-    plt.figure(figsize=(10, 6))
-    plt.plot(data)
-    plt.title(title)
-    plt.close()
-    return plt
+
+def plot_data(data, title, anomalies=None):
+    fig, ax = plt.subplots(figsize=(10, 6))
+    ax.plot(data, label='Data')
+    if anomalies is not None:
+        anomaly_indices = np.where(anomalies)[0]
+        ax.scatter(anomaly_indices, data[anomaly_indices], color='red', label='Anomalies')
+    ax.set_title(title)
+    ax.legend()
+    plt.close(fig)
+    return fig
 
 class FeatureExtractionAgent:
     def extract(self, data):
@@ -103,8 +108,13 @@ def analyze_time_series(data, forecast_steps):
         
         trend_plot = plot_data(trend, "Trend")
         seasonality_plot = plot_data(seasonality, "Seasonality")
-        anomalies_plot = plot_data(data * anomalies, "Anomalies")
-        forecast_plot = plot_data(np.concatenate([data, forecast]), "Forecast")
+        anomalies_plot = plot_data(data, "Anomalies", anomalies)
+        
+        full_data = np.concatenate([data, forecast])
+        forecast_plot = plot_data(full_data, "Forecast")
+        ax = forecast_plot.axes[0]
+        ax.axvline(x=len(data) - 1, color='r', linestyle='--', label='Forecast Start')
+        ax.legend()
         
         return (
             trend_plot,
@@ -120,10 +130,12 @@ def analyze_time_series(data, forecast_steps):
         logging.error(error_msg)
         return (None, None, None, None, None, "", error_msg)
 
+example_input = "120,125,130,140,135,145,150,160,155,165,170,180,175,185,190,200,195,205,210,220,215,225,230,240,235,245,250,260,255,265,270,280,275,285,290,300,295,305,310,320,315,325,330,340,335,345,350,360,355,365,370,380,375,385,390,400,395,405,410,420"
+
 iface = gr.Interface(
     fn=analyze_time_series,
     inputs=[
-        gr.Textbox(label="Enter comma-separated time series data"),
+        gr.Textbox(label="Enter comma-separated time series data", value=example_input),
         gr.Number(label="Number of steps to forecast", value=5)
     ],
     outputs=[
@@ -133,7 +145,7 @@ iface = gr.Interface(
         gr.JSON(label="Features"),
         gr.Plot(label="Forecast"),
         gr.Textbox(label="Insight"),
-        gr.Textbox(label="Error")
+        gr.Textbox(label="Error", visible=False)
     ],
     title="Agentic RAG Time Series Analysis",
     description="Enter a comma-separated list of numbers representing your time series data, and specify the number of steps to forecast."