Update app.py

app.py

@@ -7,8 +7,9 @@ from sklearn.preprocessing import StandardScaler
 import gradio as gr
 import traceback
 import logging
+import matplotlib.pyplot as plt
+
 
-# Set up logging
 logging.basicConfig(level=logging.ERROR)
 
 class TrendAnalysisAgent:
@@ -28,6 +29,13 @@ class AnomalyDetectionAgent:
         iso_forest = IsolationForest(contamination=0.1, random_state=42)
         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
 
 class FeatureExtractionAgent:
     def extract(self, data):
@@ -93,20 +101,24 @@ def analyze_time_series(data, forecast_steps):
         agentic_rag = AgenticRAG()
         trend, seasonality, anomalies, features, forecast, insight = agentic_rag.process(data, forecast_steps)
         
-        return {
-            "Trend": trend,
-            "Seasonality": seasonality,
-            "Anomalies": anomalies,
-            "Features": features.to_dict(orient='records')[0],
-            "Forecast": forecast.tolist(),
-            "Insight": insight
-        }
+        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")
+        
+        return (
+            trend_plot,
+            seasonality_plot,
+            anomalies_plot,
+            features.to_dict(orient='records')[0],
+            forecast_plot,
+            insight,
+            ""  # Empty string for the error output
+        )
     except Exception as e:
         error_msg = f"An error occurred: {str(e)}\n{traceback.format_exc()}"
         logging.error(error_msg)
-        return {
-            "Error": error_msg
-        }
+        return (None, None, None, None, None, "", error_msg)
 
 iface = gr.Interface(
     fn=analyze_time_series,
@@ -121,7 +133,7 @@ iface = gr.Interface(
         gr.JSON(label="Features"),
         gr.Plot(label="Forecast"),
         gr.Textbox(label="Insight"),
-        gr.Textbox(label="Error", visible=False)
+        gr.Textbox(label="Error")
     ],
     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."