Update app.py

app.py

@@ -900,6 +900,150 @@ geomodel_llm = keras_nlp.models.CausalLM.from_preset("hf://ShebMichel/geobot_tea
 # iface.launch()
 
 
+# import json
+# import gradio as gr
+
+# # Global variable to store loaded JSON data
+# loaded_data = {}
+
+# def process_json_file(file):
+#     global loaded_data
+#     try:
+#         # Read the JSON file
+#         with open(file.name, 'r') as f:
+#             loaded_data = json.load(f)
+        
+#         # Generate the full output text
+#         output_text = generate_output_text(loaded_data)
+        
+#         print("\nProcessing complete!")
+#         # Enable radio buttons and buttons upon successful loading
+#         return output_text, gr.update(interactive=True), gr.update(interactive=True), gr.update(interactive=True), gr.update(interactive=True), gr.update(interactive=True), gr.update(interactive=True), gr.update(interactive=True)
+        
+#     except json.JSONDecodeError as e:
+#         error_msg = f"Error decoding JSON: {str(e)}"
+#         print(error_msg)
+#         return error_msg, gr.update(interactive=False), gr.update(interactive=False), gr.update(interactive=False), gr.update(interactive=False), gr.update(interactive=False), gr.update(interactive=False), gr.update(interactive=False)
+#     except Exception as e:
+#         error_msg = f"Error processing file: {str(e)}"
+#         print(error_msg)
+#         return error_msg, gr.update(interactive=False), gr.update(interactive=False), gr.update(interactive=False), gr.update(interactive=False), gr.update(interactive=False), gr.update(interactive=False), gr.update(interactive=False)
+
+# def generate_output_text(data, section="ALL"):
+#     output_text = ""
+    
+#     if section == "ALL" or section == "header":
+#         if 'header' in data:
+#             output_text += "=== EXAM DETAILS ===\n"
+#             for key, value in data['header'].items():
+#                 output_text += f"{key.replace('_', ' ').title()}: {value}\n"
+#             output_text += "\n"
+    
+#     if section == "ALL" or section == "MULTIPLE CHOICE QUESTIONS":
+#         if 'multiple_choice_questions' in data:
+#             output_text += "=== MULTIPLE CHOICE QUESTIONS ===\n"
+#             for q_num, q_data in data['multiple_choice_questions'].items():
+#                 output_text += f"\nQuestion {q_num.replace('question', '')}:\n"
+#                 output_text += f"{q_data['question']}\n"
+#                 for opt_key, opt_val in q_data['options'].items():
+#                     output_text += f"{opt_key}) {opt_val}\n"
+#                 output_text += f"Answer: {q_data['answer']}\n"
+    
+#     if section == "ALL" or section == "SHORT ANSWER QUESTIONS":
+#         if 'short_answer_questions' in data:
+#             output_text += "\n=== SHORT ANSWER QUESTIONS ===\n"
+#             for q_num, q_data in data['short_answer_questions'].items():
+#                 output_text += f"\nQuestion {q_num.replace('question', '')}:\n"
+#                 output_text += f"{q_data['question']}\n"
+#                 output_text += f"Answer: {q_data['answer']}\n"
+    
+#     if section == "ALL" or section == "LONG ANSWER QUESTIONS":
+#         if 'long_answer_questions' in data:
+#             output_text += "\n=== LONG ANSWER QUESTIONS ===\n"
+#             for q_num, q_data in data['long_answer_questions'].items():
+#                 output_text += f"\nQuestion {q_num.replace('question', '')}:\n"
+#                 output_text += f"{q_data['question']}\n"
+#                 output_text += f"Answer: {q_data['answer']}\n"
+    
+#     return output_text
+
+# def update_textbox_based_on_radio(selection):
+#     # Generate output based on the selected section and show all questions in that category
+#     return generate_output_text(loaded_data, section=selection)
+
+# def submit_question(question_content):
+#     # Placeholder model processing
+#     model_output = f"Model processed question: {question_content[:100]}..."  # Only showing part for brevity
+#     return model_output
+
+# def clear_output():
+#     return ""
+
+# # Create Gradio interface
+# with gr.Blocks() as iface:
+#     gr.Markdown("# Exam Question Viewer")
+    
+#     with gr.Row():
+#         file_input = gr.File(
+#             label="Upload JSON Exam File",
+#             file_types=[".json"]
+#         )
+    
+#     with gr.Row():
+#         output_text = gr.Textbox(
+#             label="Processed Questions",
+#             lines=20,
+#             max_lines=30
+#         )
+    
+#     with gr.Row():
+#         radio_section = gr.Radio(
+#             ["MULTIPLE CHOICE QUESTIONS", "SHORT ANSWER QUESTIONS", "LONG ANSWER QUESTIONS", "ALL"], 
+#             label="Select Section to Display",
+#             interactive=False
+#         )
+
+#     # Update output_text when radio selection changes
+#     radio_section.change(
+#         fn=update_textbox_based_on_radio,
+#         inputs=[radio_section],
+#         outputs=[output_text]
+#     )
+
+#     # Submit button - Passes selected question to the model
+#     with gr.Row():
+#         submit_button = gr.Button("Submit", interactive=False)
+#         clear_button = gr.Button("Clear", interactive=False)
+#         output_button = gr.Button("Output", interactive=False)
+    
+#     # Define button actions
+#     submit_button.click(
+#         fn=submit_question,
+#         inputs=[output_text],
+#         outputs=[output_text]
+#     )
+    
+#     clear_button.click(
+#         fn=clear_output,
+#         outputs=[output_text]
+#     )
+
+#     output_button.click(
+#         fn=update_textbox_based_on_radio,
+#         inputs=[radio_section],
+#         outputs=[output_text]
+#     )
+
+#     # Process file input and enable radio buttons and buttons on successful load
+#     file_input.upload(
+#         fn=process_json_file,
+#         inputs=[file_input],
+#         outputs=[output_text, radio_section, radio_section, radio_section, radio_section, submit_button, clear_button, output_button]
+#     )
+
+# # Launch the interface
+# iface.launch()
+
 import json
 import gradio as gr
 
@@ -971,13 +1115,26 @@ def update_textbox_based_on_radio(selection):
     # Generate output based on the selected section and show all questions in that category
     return generate_output_text(loaded_data, section=selection)
 
+def set_question_to_edit(selection):
+    # Sets the first question from the selected category in the edit box if available
+    output_text = ""
+    if selection == "MULTIPLE CHOICE QUESTIONS" and 'multiple_choice_questions' in loaded_data:
+        first_question = list(loaded_data['multiple_choice_questions'].values())[0].get('question', '')
+    elif selection == "SHORT ANSWER QUESTIONS" and 'short_answer_questions' in loaded_data:
+        first_question = list(loaded_data['short_answer_questions'].values())[0].get('question', '')
+    elif selection == "LONG ANSWER QUESTIONS" and 'long_answer_questions' in loaded_data:
+        first_question = list(loaded_data['long_answer_questions'].values())[0].get('question', '')
+    else:
+        first_question = ""
+    return first_question
+
 def submit_question(question_content):
-    # Placeholder model processing
-    model_output = f"Model processed question: {question_content[:100]}..."  # Only showing part for brevity
+    # Simulate processing by an LLM model
+    model_output = f"Model response to the question: {question_content[:100]}..."  # Only showing part for brevity
     return model_output
 
 def clear_output():
-    return ""
+    return "", ""
 
 # Create Gradio interface
 with gr.Blocks() as iface:
@@ -1010,37 +1167,50 @@ with gr.Blocks() as iface:
         outputs=[output_text]
     )
 
+    # Editable question text box
+    with gr.Row():
+        question_edit = gr.Textbox(
+            label="Edit Selected Question",
+            placeholder="Select a section and a question to edit here...",
+            lines=4
+        )
+
+    # Output box for the model's response
+    model_response = gr.Textbox(
+        label="Model Response",
+        lines=4,
+        interactive=False
+    )
+
     # Submit button - Passes selected question to the model
     with gr.Row():
         submit_button = gr.Button("Submit", interactive=False)
         clear_button = gr.Button("Clear", interactive=False)
-        output_button = gr.Button("Output", interactive=False)
     
     # Define button actions
+    radio_section.change(
+        fn=set_question_to_edit,
+        inputs=[radio_section],
+        outputs=[question_edit]
+    )
+
     submit_button.click(
         fn=submit_question,
-        inputs=[output_text],
-        outputs=[output_text]
+        inputs=[question_edit],
+        outputs=[model_response]
     )
     
     clear_button.click(
         fn=clear_output,
-        outputs=[output_text]
-    )
-
-    output_button.click(
-        fn=update_textbox_based_on_radio,
-        inputs=[radio_section],
-        outputs=[output_text]
+        outputs=[question_edit, model_response]
     )
 
     # Process file input and enable radio buttons and buttons on successful load
     file_input.upload(
         fn=process_json_file,
         inputs=[file_input],
-        outputs=[output_text, radio_section, radio_section, radio_section, radio_section, submit_button, clear_button, output_button]
+        outputs=[output_text, radio_section, radio_section, radio_section, radio_section, submit_button, clear_button, submit_button]
     )
 
 # Launch the interface
 iface.launch()
-