Update app.py

app.py

@@ -47,25 +47,25 @@ with gr.Blocks() as bm25:
                     df = pd.read_excel(file)
                 else:
                     doc = "Unsupported file format. Please provide a CSV or Excel file."
-                    return doc  # Return immediately with the error message
+                    return None,doc  # Return immediately with the error message
             
                 # Ensure that the 'products' column is present in the dataframe
                 if 'products' not in df.columns.str.lower():
                     doc = "The input file must have a column named 'products'."
-                    return doc  # Return immediately with the error message
+                    return None,doc  # Return immediately with the error message
             
                 doc = 'File uploaded! Press Cluster button'
-                return doc  # Return the success message
+                return df,doc  # Return the success message
 
           
             def download_df():
-                df1=state.df
+                df1=df_bm25
                 print(df1)
                 return df1
 
             out = gr.Textbox()
             mode=gr.Radio(["Automated clustering", "Manually choose parameters"], label="Type of algorithm", value="Automated clustering",info="Choose any mode u want")
-            inputfile.upload(confirmation,inputs=[inputfile],outputs=out)
+            inputfile.upload(confirmation,inputs=[inputfile],outputs=[gr.File(label="Uploaded File"),out])
             with gr.Row():
               
                 min_cluster_size=gr.Slider(2, 500, value=5, step=1,label="min_cluster_size", info="Choose minimum No. of docs in a cluster. Lower the value ,higher the clusters created")
@@ -88,7 +88,7 @@ with gr.Blocks() as bm25:
                 gr.Plot(label="Hierarchy"),
                
             ])
-            llm_btn = gr.Button(value="AI generation ")
+            llm_btn = gr.Button(value="Download Excel with Topics ")
             llm_btn.click(download_df,inputs=[],outputs=gr.Dataframe(label="Output"))