Update app.py

app.py

@@ -1111,13 +1111,6 @@ def chat_with_excel_data_dataframe(question):
     #response_dataframe.to_excel(save_file_path, index=False)
     #save_file_to_hostinger(save_file_path)
     
-    # Check if the response is a DataFrame
-    """if isinstance(response_dataframe, pd.DataFrame):
-        # Convert DataFrame to HTML for display
-        df_html = response_dataframe.to_html(classes='dataframe', index=False)   
-        print(f"dfhtml:{df_html}")     
-        return df_html"""
-    
     #return response_dataframe.head(10)#, len(response_dataframe)
 
 def save_file_to_hostinger(save_file_path):
@@ -1184,45 +1177,12 @@ def handle_large_dataset(df, create_document,isDataFrame):
         
         file_path = os.path.join(current_folder, 'output_data.xlsx')
         df.to_excel(file_path, index=False)
-        #if not os.path.exists("/data/"):
-            #os.makedirs("/data/")
-        #df.to_excel('/data/output_data.xlsx', index=False)
-        
-        files = os.listdir(current_folder)
-        print(f"Files in persistent storage: {files}")
-        print(f"The current folder is: {current_folder}")
-        """from huggingface_hub import Repository
-
-        repo = Repository(
-        local_dir="./",
-        repo_type="space",
-        repo_id="Redmind/NewageNXTGPT",
-        use_auth_token=os.getenv("HF_TOKEN"),
-        )"""
+              
     
         file_path = "output_data.xlsx"
         #download_url = repo.get_download_url(file_path)
-
-        from huggingface_hub import upload_file
-        
-        # Upload file to the Hugging Face Hub
-        repo_id = "Redmind/NewageNXTGPT"
-        #file_path = "/app/example.txt"  # Path to the file to upload
-        from huggingface_hub import login
-
-        # Login to Hugging Face Hub
-        login(token=os.getenv("HF_TOKEN"))
-        from huggingface_hub import HfApi
-        api = HfApi()
-        #api.upload_file(path_or_fileobj=file_path, repo_id=repo_id, repo_type= "space", path_in_repo="static/output.xlsx")
-        
-        from huggingface_hub import hf_hub_url
-
-        print(hf_hub_url(
-            repo_id="Redmind/NewageNXTGPT", filename="static/output.xlsx"
-            ))
-
-        #print(f"Download the file here: {download_url}")
+        create_file_HF(file_path)
+       
         #save_file_to_hostinger('output_data.xlsx')
         # 4. Create a summary and table of the first 10 rows for display
     
@@ -1247,7 +1207,7 @@ def handle_large_dataset(df, create_document,isDataFrame):
     else:
         return "Your query returns a large dataset which is not supported in the current version. Please try a different query."
 
-def create_file_HF():
+def create_file_HF(file_path):
     from huggingface_hub import create_branch, create_tag
     from huggingface_hub import login
     
@@ -1258,7 +1218,7 @@ def create_file_HF():
     
     from huggingface_hub import HfApi
     api = HfApi()
-    api.upload_file(path_or_fileobj="Inbound.pdf", repo_id="Redmind/NewageNXTGPT_Repo_trial",revision = "test-branch", repo_type= "space", path_in_repo="Inbound.pdf")
+    api.upload_file(path_or_fileobj=file_path, repo_id="Redmind/NewageNXTGPT_Repo_trial",revision = "test-branch", repo_type= "space", path_in_repo='./output')
             
         
 def create_pdf(cname,ename,account_number):