Update app.py

app.py

@@ -8,54 +8,152 @@ 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") # **حذف خط بارگیری gemini_api_key**
+gemini_api_key = os.environ.get("GEMINI_API_KEY")
 
 # Initialize expert roles
-pee_expert = PromptEngineeringExpert(openai_api_key=openai_api_key)
-cae_expert = CriticalAnalysisExpert() # **حذف آرگومان gemini_api_key**
+pee_expert = PromptEngineeringExpert()
+cae_expert = CriticalAnalysisExpert()
 dce_expert = DiscussionContinuityExpert()
 
+MAX_ITERATIONS = 3 # Define maximum number of iterations
 
-def nova_workflow(business_info_file, product_service_file):
-    try:
-        # Read data from uploaded Excel files using pandas
+
+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)
-
-        # 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')
+    else: # **Loading state from previous iteration**
+        iteration_number = history[-1]["iteration_number"] + 1 # Increment iteration number
 
+    if iteration_number > MAX_ITERATIONS: # **Check for max iterations limit**
+        return (
+            history,
+            "Maximum iterations reached. Final outputs are displayed below.",
+            gr.Button.update(visible=False), # Hide "Continue Iteration" button
+            gr.Button.update(visible=False), # Hide "Final Output" button
+        )
+
+
+    try:
+        # Run Nova System Workflow Iteration
         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=1,
+            iteration_number=iteration_number,
             expert_pee=pee_expert,
             expert_cae=cae_expert,
             business_info_form_data=business_info_form_data,
             product_service_form_data=product_service_form_data
         )
 
+        iteration_output = { # Store iteration outputs in a dictionary
+            "iteration_number": iteration_number,
+            "chatbot_prompt": chatbot_prompt,
+            "knowledge_base": knowledge_base,
+            "faq_section": faq_section,
+            "prompt_critique_suggestions": prompt_critique_suggestions,
+            "knowledge_base_critique_suggestions": knowledge_base_critique_suggestions,
+            "faq_section_critique_suggestions": faq_section_critique_suggestions,
+            "summary": summary,
+            "actions": actions,
+            "cae_analysis_summary": cae_analysis_summary,
+            "dce_state": dce_state,
+            "goals_next_iteration": goals_next_iteration,
+            "current_work_efforts": current_work_efforts,
+            "proposed_work_efforts": proposed_work_efforts,
+            "end_iteration_message": end_iteration_message
+        }
 
-        return chatbot_prompt, knowledge_base, faq_section # Return outputs for Gradio to display
+        history.append(iteration_output) # Append current iteration output to history
+
+        iteration_display = "" # Format iteration output for display
+        for iteration in history:
+            iteration_display += f"----\nIteration {iteration['iteration_number']}:\n----\n"
+            iteration_display += f"**DCE Summary:**\n{iteration['summary']}\n\n"
+            iteration_display += f"**PEE Output - Chatbot Prompt:**\n{iteration['chatbot_prompt']}\n\n"
+            iteration_display += f"**CAE Analysis - Prompt Critique:**\n{iteration['prompt_critique_suggestions']}\n\n"
+            iteration_display += f"**Knowledge Base:**\n{iteration['knowledge_base']}\n\n"
+            iteration_display += f"**FAQ Section:**\n{iteration['faq_section']}\n\n"
+            iteration_display += f"**CAE Analysis - Knowledge Base Critique:**\n{iteration['knowledge_base_critique_suggestions']}\n\n"
+            iteration_display += f"**CAE Analysis - FAQ Section Critique:**\n{iteration['faq_section_critique_suggestions']}\n\n"
+            iteration_display += f"**Actions:**\n{iteration['actions']}\n\n"
+            iteration_display += f"**DCE State:**\n{iteration['dce_state']}\n\n"
+            iteration_display += f"**Goals for next iteration:**\n{iteration['goals_next_iteration']}\n\n"
+            iteration_display += f"**Current Work Efforts:**\n{iteration['current_work_efforts']}\n\n"
+            iteration_display += f"**Proposed Work Efforts:**\n{iteration['proposed_work_efforts']}\n\n"
+            iteration_display += f"**End of Iteration:**\n{iteration['end_iteration_message']}\n\n"
+
+
+        return (
+            history, # Return history to gr.State
+            iteration_display, # Return formatted iteration display
+            gr.Button.update(visible=True), # Show "Continue Iteration" button
+            gr.Button.update(visible=True), # Show "Final Output" button
+        )
 
     except Exception as e:
-        return str(e), "Error generating Knowledge Base", "Error generating FAQ Section" # Return error messages
-
-
-iface = gr.Interface(
-    fn=nova_workflow,
-    inputs=[
-        gr.File(file_types=['.xlsx'], label="Upload Business Information Form (Excel File)"),
-        gr.File(file_types=['.xlsx'], label="Upload Product/Service Information Form (Excel File)")
-    ],
-    outputs=[
-        gr.Code(language="markdown", label="Final Chatbot Prompt (English - Markdown)"),
-        gr.Code(language="json", label="Knowledge Base (JSON-like)"),
-        gr.Code(language="json", label="FAQ Section (JSON-like)")
-    ],
-    title="Nova System - Chatbot Prompt & Knowledge Base Generator (Iterative - ChatGPT Only)", # **تغییر عنوان برای نشان دادن استفاده فقط از ChatGPT**
-    description="Upload Excel files containing business information and product/service details to generate a chatbot prompt, knowledge base, and FAQ section. **System now uses ChatGPT API only.**", # **اضافه کردن توضیحات در مورد استفاده فقط از ChatGPT**
-    flagging_mode="never"
-)
+        return (
+            history, # Return history even in case of error
+            str(e), # Return error message in iteration display
+            gr.Button.update(visible=False), # Hide "Continue Iteration" button in case of error
+            gr.Button.update(visible=False), # Hide "Final Output" button in case of error
+        )
+
+
+def finalize_outputs(history): # **Function for "Final Output" button**
+    if history:
+        final_iteration = history[-1] # Get the last iteration output from history
+        return (
+            final_iteration['chatbot_prompt'],
+            final_iteration['knowledge_base'],
+            final_iteration['faq_section'],
+            gr.Button.update(visible=False), # Hide "Continue Iteration" button after finalization
+            gr.Button.update(visible=False), # Hide "Final Output" button after finalization
+        )
+    else:
+        return "No output generated yet.", "No output generated yet.", "No output generated yet.", gr.Button.update(visible=False), gr.Button.update(visible=False)
+
+
+with gr.Blocks() as iface: # Use gr.Blocks for more control over layout and state
+    history_state = gr.State([]) # gr.State to store iteration history
+
+    gr.Markdown("## Nova System - Chatbot Prompt & Knowledge Base Generator (Iterative)")
+    gr.Markdown("Upload Excel files containing business information and product/service details to generate a chatbot prompt, knowledge base, and FAQ section. **System now runs in iterative mode with user control.**")
+
+    with gr.Row():
+        business_info_file = gr.File(file_types=['.xlsx'], label="Upload Business Information Form (Excel File)")
+        product_service_file = gr.File(file_types=['.xlsx'], label="Upload Product/Service Information Form (Excel File)")
+
+    generate_button = gr.Button("Generate Prompt, Knowledge Base & Start Iterations")
+    iteration_output_display = gr.Markdown(label="Iteration Output") # Component to display iteration details
+
+    with gr.Row():
+        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__":