Update app.py

app.py

@@ -97,54 +97,73 @@ def linePlot_time_series(viz_type, weight, top_n):
     return df
 
 
-def update_visualization(viz_type, weight, top_n):
-    """
-    Update visualization based on user inputs and selected visualization type
+# def update_visualization(viz_type, weight, top_n):
+#     """
+#     Update visualization based on user inputs and selected visualization type
     
-    Parameters:
-    -----------
-    viz_type : str
-        Type of visualization to show ('emotions', 'topics', or 'grid')
-    weight : float
-        Weight for scoring (0-1)
-    top_n : int
-        Number of top items to show
-    """
-    try:
-
-        #     return None, "Error: Start date must be before end date"
-        series = linePlot_time_series(viz_type, weight, top_n)
-        if viz_type == "emotions":
-            # Create emotion time series
-            # series = linePlot_time_series(viz_type, weight, top_n)
-            fig = plot_stacked_time_series(
-                series,
-                f'Top {top_n} Emotions Popularity'
-            )
-            message = "Emotion time series updated"
+#     Parameters:
+#     -----------
+#     viz_type : str
+#         Type of visualization to show ('emotions', 'topics', or 'grid')
+#     weight : float
+#         Weight for scoring (0-1)
+#     top_n : int
+#         Number of top items to show
+#     """
+#     try:
+
+#         #     return None, "Error: Start date must be before end date"
+#         series = linePlot_time_series(viz_type, weight, top_n)
+#         if viz_type == "emotions":
+#             # Create emotion time series
+#             # series = linePlot_time_series(viz_type, weight, top_n)
+#             fig = plot_stacked_time_series(
+#                 series,
+#                 f'Top {top_n} Emotions Popularity'
+#             )
+#             message = "Emotion time series updated"
             
-        elif viz_type == "topics":
-            # Create topic time series
-            # series = linePlot_time_series(viz_type, weight, top_n)
-            fig = plot_stacked_time_series(
-                series,
-                f'Top {top_n} Topics Popularity'
-            )
-            message = "Topic time series updated"
+#         elif viz_type == "topics":
+#             # Create topic time series
+#             # series = linePlot_time_series(viz_type, weight, top_n)
+#             fig = plot_stacked_time_series(
+#                 series,
+#                 f'Top {top_n} Topics Popularity'
+#             )
+#             message = "Topic time series updated"
             
-        else:  # viz_type == "grid"
-            # Create emotion-topic grid
-            # pair_series = linePlot_time_series(viz_type, weight, top_n)
-            fig = plot_emotion_topic_grid(series, top_n)
-            message = "Emotion-Topic grid updated"
+#         else:  # viz_type == "grid"
+#             # Create emotion-topic grid
+#             # pair_series = linePlot_time_series(viz_type, weight, top_n)
+#             fig = plot_emotion_topic_grid(series, top_n)
+#             message = "Emotion-Topic grid updated"
         
-        return fig, message
+#         return fig, message
         
-    except Exception as e:
-        return None, f"Error: {str(e)}"
+#     except Exception as e:
+#         return None, f"Error: {str(e)}"
         
+def decode_plot(plot_base64):
+    plot_bytes = base64.b64decode(plot_base64['plot'].split(',')[1])
+    img = plt.imread(BytesIO(plot_bytes), format='PNG')
+    plt.imshow(img)
+    plt.axis('off')
+    plt.show()
+    return plt.gcf()
 
 
+def linePlot(viz_type, weight, top_n):
+    client = Client("mangoesai/Elections_Comparison_Agent_V4.1")
+    result = client.predict(
+    		viz_type=viz_type,
+    		weight=weight,
+    		top_n=top_n,
+    		api_name="/linePlot_3C1"
+    )
+    
+    return decode_plot(result)
+
+    
 
 
 
@@ -276,7 +295,7 @@ with gr.Blocks(title="Reddit Election Analysis") as demo:
     )
     
     linePlot_btn.click(
-        fn = update_visualization,
+        fn = linePlot,
         inputs = [viz_dropdown,weight_slider,top_n_slider],
         outputs = [time_series_fig, linePlot_status_text]
     )