Update app.py

app.py

@@ -29,6 +29,9 @@ def generate_mcq_quiz(pdf_content, num_questions, openai_api_key, model_choice):
     
     openai.api_key = openai_api_key
     
+    # Limit content length to avoid token limits
+    limited_content = pdf_content[:8000] if len(pdf_content) > 8000 else pdf_content
+    
     prompt = f"""Based on the following document content, generate {num_questions} multiple-choice quiz questions.
 For each question:
 1. Create a clear question based on key concepts in the document
@@ -39,21 +42,20 @@ For each question:
 Format the output clearly with each question numbered and separated.
 
 Document content:
-{pdf_content[:8000]}  # Limiting content to avoid token limits
+{limited_content}
 """
     
     try:
         messages = [
-            {"role": "user", "content": [{"type": "text", "text": prompt}]}
+            {"role": "user", "content": prompt}
         ]
         
         response = openai.ChatCompletion.create(
             model=model_choice,
-            messages=messages,
-            max_completion_tokens=2000
+            messages=messages
         )
         
-        return response["choices"][0]["message"]["content"]
+        return response.choices[0].message.content
     except Exception as e:
         return f"Error generating quiz: {str(e)}"
 
@@ -85,11 +87,11 @@ def generate_response(input_text, image, pdf_content, openai_api_key, reasoning_
             ]
         else:
             messages = [
-                {"role": "user", "content": [{"type": "text", "text": input_content}]}
+                {"role": "user", "content": input_content}
             ]
     elif model_choice == "o3-mini":
         messages = [
-            {"role": "user", "content": [{"type": "text", "text": input_content}]}
+            {"role": "user", "content": input_content}
         ]
     
     try:
@@ -97,11 +99,10 @@ def generate_response(input_text, image, pdf_content, openai_api_key, reasoning_
         response = openai.ChatCompletion.create(
             model=model_choice,
             messages=messages,
-            reasoning_effort=reasoning_effort,
-            max_completion_tokens=2000
+            max_tokens=2000
         )
 
-        return response["choices"][0]["message"]["content"]
+        return response.choices[0].message.content
     except Exception as e:
         return f"Error calling OpenAI API: {str(e)}"
 
@@ -132,12 +133,15 @@ def transcribe_audio(audio, openai_api_key):
 
         # Transcribe the audio to text using OpenAI's whisper model
         audio_file_transcription = openai.Audio.transcribe(file=audio_file_obj, model="whisper-1")
-        return audio_file_transcription['text']
+        return audio_file_transcription.text
     except Exception as e:
         return f"Error transcribing audio: {str(e)}"
 
 # The function that will be used by Gradio interface
-def chatbot(input_text, image, audio, pdf_file, openai_api_key, reasoning_effort, model_choice, pdf_content, num_quiz_questions, pdf_quiz_mode, history=[]):
+def chatbot(input_text, image, audio, pdf_file, openai_api_key, reasoning_effort, model_choice, pdf_content, num_quiz_questions, pdf_quiz_mode, history):
+    if history is None:
+        history = []
+        
     # If there's audio, transcribe it to text
     if audio:
         input_text = transcribe_audio(audio, openai_api_key)
@@ -148,10 +152,13 @@ def chatbot(input_text, image, audio, pdf_file, openai_api_key, reasoning_effort
         new_pdf_content = extract_text_from_pdf(pdf_file)
     
     # Check if we're in PDF quiz mode
-    if pdf_quiz_mode and new_pdf_content:
-        # Generate MCQ quiz questions
-        response = generate_mcq_quiz(new_pdf_content, num_quiz_questions, openai_api_key, model_choice)
-        history.append((f"User: [Uploaded PDF for Quiz - {num_quiz_questions} questions]", f"Assistant: {response}"))
+    if pdf_quiz_mode:
+        if new_pdf_content:
+            # Generate MCQ quiz questions
+            quiz_response = generate_mcq_quiz(new_pdf_content, int(num_quiz_questions), openai_api_key, model_choice)
+            history.append((f"User: [Uploaded PDF for Quiz - {int(num_quiz_questions)} questions]", f"Assistant: {quiz_response}"))
+        else:
+            history.append(("User: [Attempted to generate quiz without PDF]", "Assistant: Please upload a PDF file to generate quiz questions."))
     else:
         # Regular chat mode - generate the response
         response = generate_response(input_text, image, new_pdf_content, openai_api_key, reasoning_effort, model_choice)
@@ -159,8 +166,12 @@ def chatbot(input_text, image, audio, pdf_file, openai_api_key, reasoning_effort
         # Append the response to the history
         if input_text:
             history.append((f"User: {input_text}", f"Assistant: {response}"))
+        elif image is not None:
+            history.append((f"User: [Uploaded image]", f"Assistant: {response}"))
+        elif pdf_file is not None:
+            history.append((f"User: [Uploaded PDF]", f"Assistant: {response}"))
         else:
-            history.append((f"User: [Uploaded content]", f"Assistant: {response}"))
+            history.append((f"User: [No input provided]", f"Assistant: Please provide some input (text, image, or PDF) for me to respond to."))
     
     return "", None, None, None, new_pdf_content, history
 
@@ -177,15 +188,15 @@ def process_pdf(pdf_file):
 # Function to update visible components based on input type selection
 def update_input_type(choice):
     if choice == "Text":
-        return gr.update(visible=True), gr.update(visible=False), gr.update(visible=False), gr.update(visible=False), gr.update(visible=False), gr.update(visible=False)
+        return gr.update(visible=True), gr.update(visible=False), gr.update(visible=False), gr.update(visible=False), gr.update(visible=False), gr.update(value=False)
     elif choice == "Image":
-        return gr.update(visible=True), gr.update(visible=True), gr.update(visible=False), gr.update(visible=False), gr.update(visible=False), gr.update(visible=False)
+        return gr.update(visible=True), gr.update(visible=True), gr.update(visible=False), gr.update(visible=False), gr.update(visible=False), gr.update(value=False)
     elif choice == "Voice":
-        return gr.update(visible=False), gr.update(visible=False), gr.update(visible=True), gr.update(visible=False), gr.update(visible=False), gr.update(visible=False)
+        return gr.update(visible=False), gr.update(visible=False), gr.update(visible=True), gr.update(visible=False), gr.update(visible=False), gr.update(value=False)
     elif choice == "PDF":
-        return gr.update(visible=True), gr.update(visible=False), gr.update(visible=False), gr.update(visible=True), gr.update(visible=False), gr.update(visible=False)
+        return gr.update(visible=True), gr.update(visible=False), gr.update(visible=False), gr.update(visible=True), gr.update(visible=False), gr.update(value=False)
     elif choice == "PDF(QUIZ)":
-        return gr.update(visible=False), gr.update(visible=False), gr.update(visible=False), gr.update(visible=True), gr.update(visible=True), gr.update(visible=True)
+        return gr.update(visible=False), gr.update(visible=False), gr.update(visible=False), gr.update(visible=True), gr.update(visible=True), gr.update(value=True)
     
 # Custom CSS styles with animations and button colors
 custom_css = """
@@ -474,21 +485,30 @@ def create_interface():
             outputs=[pdf_content]
         )
 
-        # Update quiz mode when PDF(QUIZ) is selected
-        def update_quiz_mode(choice):
-            return True if choice == "PDF(QUIZ)" else False
-        
-        input_type.change(
-            fn=update_quiz_mode,
-            inputs=[input_type],
-            outputs=[quiz_mode]
-        )
-
         # Button interactions
         submit_btn.click(
             fn=chatbot, 
-            inputs=[input_text, image_input, audio_input, pdf_input, openai_api_key, reasoning_effort, model_choice, pdf_content, quiz_questions_slider, quiz_mode], 
-            outputs=[input_text, image_input, audio_input, pdf_input, pdf_content, chat_history]
+            inputs=[
+                input_text, 
+                image_input, 
+                audio_input, 
+                pdf_input, 
+                openai_api_key, 
+                reasoning_effort, 
+                model_choice, 
+                pdf_content, 
+                quiz_questions_slider, 
+                quiz_mode, 
+                chat_history
+            ], 
+            outputs=[
+                input_text, 
+                image_input, 
+                audio_input, 
+                pdf_input, 
+                pdf_content, 
+                chat_history
+            ]
         )
         
         clear_btn.click(