Update app.py

app.py

@@ -8,7 +8,6 @@ import os
 
 # Load API Keys from Hugging Face Secrets or environment variables
 openai_api_key = os.environ.get("OPENAI_API_KEY")
-gemini_api_key = os.environ.get("GEMINI_API_KEY")
 
 # Initialize expert roles
 pee_expert = PromptEngineeringExpert(openai_api_key=openai_api_key)
@@ -18,16 +17,8 @@ dce_expert = DiscussionContinuityExpert()
 MAX_ITERATIONS = 3 # Define maximum number of iterations
 
 
-def nova_workflow(business_info_file, product_service_file, history=None): # **اضافه کردن history برای مدیریت state**
-    if history is None: # **Initialization for the first iteration**
-        iteration_number = 1
-        history = [] # Initialize history list to store iteration outputs
-        business_info_df = pd.read_excel(business_info_file.name)
-        product_service_df = pd.read_excel(product_service_file.name)
-        business_info_form_data = business_info_df.iloc[0].to_dict()
-        product_service_form_data = product_service_df.to_dict('records')
-    else: # **Loading state from previous iteration**
-        iteration_number = history[-1]["iteration_number"] + 1 # Increment iteration number
+def nova_workflow(business_info_file, product_service_file, history=[]): # **اصلاح: تغییر مقدار پیش‌فرض history به []**
+    iteration_number = len(history) + 1 # **محاسبه iteration_number بر اساس طول history**
 
     if iteration_number > MAX_ITERATIONS: # **Check for max iterations limit**
         return (
@@ -39,7 +30,14 @@ def nova_workflow(business_info_file, product_service_file, history=None): # **
 
 
     try:
-        # Run Nova System Workflow Iteration
+        # Read data from uploaded Excel files using pandas
+        business_info_df = pd.read_excel(business_info_file.name)
+        product_service_df = pd.read_excel(product_service_file.name)
+
+        # Convert pandas DataFrames to dictionaries/JSON
+        business_info_form_data = business_info_df.iloc[0].to_dict()
+        product_service_form_data = product_service_df.to_dict('records')
+
         chatbot_prompt, knowledge_base, faq_section, prompt_critique_suggestions, knowledge_base_critique_suggestions, faq_section_critique_suggestions, summary, actions, cae_analysis_summary, dce_state, goals_next_iteration, current_work_efforts, proposed_work_efforts, end_iteration_message = dce_expert.run_iteration(
             iteration_number=iteration_number,
             expert_pee=pee_expert,
@@ -133,28 +131,4 @@ with gr.Blocks() as iface: # Use gr.Blocks for more control over layout and stat
         continue_iteration_button = gr.Button("Continue Iteration", visible=False) # "Continue Iteration" Button - Initially hidden
         finalize_button = gr.Button("Final Output", visible=False) # "Final Output" Button - Initially hidden
 
-    chatbot_prompt_output = gr.Code(language="markdown", label="Final Chatbot Prompt (English - Markdown)")
-    knowledge_base_output = gr.Code(language="json", label="Knowledge Base (JSON-like)")
-    faq_section_output = gr.Code(language="json", label="FAQ Section (JSON-like)")
-
-    generate_button.click( # Event listener for "Generate" button
-        nova_workflow,
-        inputs=[business_info_file, product_service_file, history_state], # Pass history_state as input
-        outputs=[history_state, iteration_output_display, continue_iteration_button, finalize_button, chatbot_prompt_output, knowledge_base_output, faq_section_output] # Include history_state in outputs
-    )
-
-    continue_iteration_button.click( # Event listener for "Continue Iteration" button
-        nova_workflow,
-        inputs=[business_info_file, product_service_file, history_state], # Pass history_state as input
-        outputs=[history_state, iteration_output_display, continue_iteration_button, finalize_button, chatbot_prompt_output, knowledge_base_output, faq_section_output] # Include history_state in outputs
-    )
-
-    finalize_button.click( # Event listener for "Final Output" button
-        finalize_outputs,
-        inputs=[history_state], # Pass history_state as input
-        outputs=[chatbot_prompt_output, knowledge_base_output, faq_section_output, continue_iteration_button, finalize_button] # Buttons visibility in outputs
-    )
-
-
-if __name__ == "__main__":
-    iface.launch()
+    chatbot_prompt_output = gr.Code(language="markdown", label="Final Chatbot Prompt (English - Markdown)