Update excel_chat.py

excel_chat.py

@@ -84,7 +84,7 @@ def ask_llm(query, user_input, client_index, user, keys):
         raise ValueError("Unsupported client index provided")
 
     # Return the response, handling the structure specific to Groq and Mistral clients.
-    return chat_completion.choices[0].message.content if client_index != "Claude" else chat_completion
+    return chat_completion.choices[0].message.content,keys if client_index != "Claude" else chat_completion
 
 
 
@@ -105,6 +105,7 @@ def chat_with_mistral(source_cols, dest_col, prompt, excel_file, url, search_col
     # API Keys for Groq :
     KEYS = ['GROQ_API_KEY1', 'GROQ_API_KEY2', 'GROQ_API_KEY3']
     GroqKey = KEYS[0]
+    gloabal_keys = [GroqKey, KEYS]
     
     new_prompts, new_keywords, new_user, conf_file_path = update_json(user, prompt, keywords)
     print(f'xlsxfile = {excel_file}')
@@ -125,7 +126,7 @@ 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)
         if not concatenated_content == "\n\n".join(f"{column_name}: nan" for column_name in source_cols):
-            llm_answer = ask_llm(prompt[0], concatenated_content, client, user, [GroqKey, KEYS])
+            llm_answer,gloabal_keys = ask_llm(prompt[0], concatenated_content, client, user, gloabal_keys)
             print(f"{cpt}/{len(filtred_df)}\nQUERY:\n{prompt[0]}\nCONTENT:\n{concatenated_content[:200]}...\n\nANSWER:\n{llm_answer}")
             df.at[index, dest_col] = llm_answer
             cpt += 1