Update excel_chat.py

excel_chat.py

@@ -85,7 +85,7 @@ def filter_df(df, column_name, keywords):
         filtered_df = df
     return filtered_df
 
-def chat_with_mistral(source_cols, dest_col, prompt, excel_file, url, search_col, keywords, client, user):
+def chat_with_mistral(source_cols, dest_col, prompt, excel_file, url, search_col, keywords, client, user, progress=gr.Progress):
     new_prompts, new_keywords, new_user, conf_file_path = update_json(user, prompt, keywords)
     print(f'xlsxfile = {excel_file}')
     df = pd.read_excel(excel_file)
@@ -103,12 +103,11 @@ def chat_with_mistral(source_cols, dest_col, prompt, excel_file, url, search_col
 
     for index, row in filtred_df.iterrows():
         concatenated_content = "\n\n".join(f"{column_name}: {str(row[column_name])}" for column_name in source_cols)
-        print('test')
         if not concatenated_content == "\n\n".join(f"{column_name}: nan" for column_name in source_cols):
-            print('c bon')
             llm_answer = ask_llm(prompt[0], concatenated_content, client, user)
-            print(f"QUERY:\n{prompt[0]}\nCONTENT:\n{concatenated_content[:200]}...\n\nANSWER:\n{llm_answer}")
+            print(f"{index+1}/{len(df)}\nQUERY:\n{prompt[0]}\nCONTENT:\n{concatenated_content[:200]}...\n\nANSWER:\n{llm_answer}")
             df.at[index, dest_col] = llm_answer
+            progress((index+1)/len(df),desc=f'Request {index+1}/{len(df)}')
 
     df.to_excel(file_name, index=False)