Update app.py

app.py

@@ -5,7 +5,7 @@ import matplotlib.pyplot as plt
 import os
 import pandas as pd
 from io import StringIO
-from linePlot import plot_stacked_time_series, plot_emotion_topic_grid
+# from linePlot import plot_stacked_time_series, plot_emotion_topic_grid
 
 # Define your Hugging Face token (make sure to set it as an environment variable)
 HF_TOKEN = os.getenv("HF_TOKEN")  # Replace with your actual token if not using an environment variable
@@ -80,21 +80,21 @@ def heatmap(top_n):
     
     return plt.gcf()
 
-def linePlot_time_series(viz_type, weight, top_n):
-    result = client.predict(
-    		viz_type=viz_type,
-    		weight=weight,
-    		top_n=top_n,
-    		api_name="/linePlot_time_series"
-    )
+# def linePlot_time_series(viz_type, weight, top_n):
+#     result = client.predict(
+#     		viz_type=viz_type,
+#     		weight=weight,
+#     		top_n=top_n,
+#     		api_name="/linePlot_time_series"
+#     )
     
-    print("============== timeseries df transfer from pivate to public ===============")
-    print(result)
-    print(type(result))
+#     print("============== timeseries df transfer from pivate to public ===============")
+#     print(result)
+#     print(type(result))
 
-    df = pd.DataFrame(result['data'], columns=result['headers'])
-    df.set_index('Index', inplace=True)
-    return df
+#     df = pd.DataFrame(result['data'], columns=result['headers'])
+#     df.set_index('Index', inplace=True)
+#     return df
 
 
 # def update_visualization(viz_type, weight, top_n):
@@ -142,7 +142,9 @@ def linePlot_time_series(viz_type, weight, top_n):
         
 #     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')
@@ -153,7 +155,7 @@ def decode_plot(plot_base64):
 
 
 def linePlot(viz_type, weight, top_n):
-    client = Client("mangoesai/Elections_Comparison_Agent_V4.1")
+    # client = Client("mangoesai/Elections_Comparison_Agent_V4.1")
     result = client.predict(
     		viz_type=viz_type,
     		weight=weight,
@@ -165,8 +167,6 @@ def linePlot(viz_type, weight, top_n):
 
     
 
-
-
 # Create Gradio interface
 with gr.Blocks(title="Reddit Election Analysis") as demo:
     gr.Markdown("# Reddit Public sentiment & Social topic distribution ")
@@ -205,18 +205,6 @@ with gr.Blocks(title="Reddit Election Analysis") as demo:
                 label="Top N Items"
             )
 
-            # start_date_picker = gr.Date(
-            #     value=date_min.date(),
-            #     label="Start Date",
-            #     info=f"Available from: {date_min.strftime('%Y-%m-%d')}"
-            # )
-            
-            # end_date_picker = gr.Date(
-            #     value=date_max.date(),
-            #     label="End Date",
-            #     info=f"Available until: {date_min.strftime('%Y-%m-%d')}"
-            # )
-        
 
         # with gr.Column():
             viz_dropdown = gr.Dropdown(