Update app.py

app.py

@@ -2,6 +2,7 @@ import gradio as gr
 from transformers import pipeline
 from gtts import gTTS
 import os
+import random
 
 # Initialize NLP pipelines
 qa = pipeline("question-answering", model="distilbert-base-uncased-distilled-squad")
@@ -11,14 +12,58 @@ except Exception as e:
     print(f"Error loading summarizer: {e}")
     summarizer = None
 
-def study_aid(question, context, font_size=16, audio_output=False, simplify_text=False):
+try:
+    question_generator = pipeline("text2text-generation", model="valhalla/t5-small-qg-hl")
+except Exception as e:
+    print(f"Error loading question generator: {e}")
+    question_generator = None
+
+# Initialize user stats
+if not os.path.exists("user_score.txt"):
+    with open("user_score.txt", "w") as f:
+        f.write("0")
+if not os.path.exists("questions_answered.txt"):
+    with open("questions_answered.txt", "w") as f:
+        f.write("0")
+
+def update_score(points):
+    with open("user_score.txt", "r") as f:
+        score = int(f.read())
+    score += points
+    with open("user_score.txt", "w") as f:
+        f.write(str(score))
+    return score
+
+def update_questions_answered():
+    with open("questions_answered.txt", "r") as f:
+        count = int(f.read())
+    count += 1
+    with open("questions_answered.txt", "w") as f:
+        f.write(str(count))
+    return count
+
+def get_progress():
+    with open("questions_answered.txt", "r") as f:
+        count = int(f.read())
+    progress = min(count * 10, 100)  # 10% per question, max 100%
+    return f"Progress: {progress}%"
+
+def get_motivational_message():
+    messages = [
+        "Great job! Keep learning!",
+        "You're doing awesome!",
+        "Amazing effort! Keep it up!",
+        "You're making great progress!"
+    ]
+    return random.choice(messages)
+
+def study_aid(question, context, font_size=16, audio_output=False, simplify_text=False, theme="dark"):
     with open("decision_log.txt", "a") as f:
-        f.write(f"Question: {question}, Simplified: {simplify_text}, Audio: {audio_output}, Font: {font_size}\n")
+        f.write(f"Question: {question}, Simplified: {simplify_text}, Audio: {audio_output}, Font: {font_size}, Theme: {theme}\n")
     
     simplified_context = context
     if simplify_text and summarizer is not None:
         try:
-            # Ensure input length is suitable
             if len(context.split()) < 10:
                 simplified_context = "Input too short to simplify."
             elif len(context.split()) > 512:
@@ -31,22 +76,68 @@ def study_aid(question, context, font_size=16, audio_output=False, simplify_text
     
     answer = qa(question=question, context=simplified_context)["answer"]
     
-    output = f"<div style='font-size:{font_size}px'>"
+    bg_color = "black" if theme == "dark" else "white"
+    text_color = "white" if theme == "dark" else "black"
+    output = f"<div style='font-size:{font_size}px; color:{text_color}; background-color:{bg_color}; padding:10px;'>"
     if simplify_text and simplified_context != context:
         output += f"<b>Simplified Context:</b> {simplified_context}<br>"
     output += f"<b>Answer:</b> {answer}</div>"
     
+    # Add visual diagram for neural network questions
+    diagram = None
+    if "neural network" in question.lower():
+        diagram = "https://upload.wikimedia.org/wikipedia/commons/thumb/4/46/Colored_neural_network.svg/300px-Colored_neural_network.svg.png"
+        output += f"<br><img src='{diagram}' alt='Neural Network Diagram' style='width:300px; height:auto;'>"
+    
+    # Update stats
+    score = update_score(10)
+    questions_answered = update_questions_answered()
+    progress = get_progress()
+    motivation = get_motivational_message()
+    
     if audio_output:
         tts = gTTS(text=answer, lang='en')
         tts.save("answer_audio.mp3")
-        return output, "answer_audio.mp3"
+        return output, "answer_audio.mp3", f"Your Score: {score} | {progress} | {motivation}"
     
-    return output, None
+    return output, None, f"Your Score: {score} | {progress} | {motivation}"
 
 def submit_feedback(feedback):
     with open("feedback.txt", "a") as f:
         f.write(feedback + "\n")
-    return "Feedback submitted!"
+    score = update_score(5)
+    progress = get_progress()
+    motivation = get_motivational_message()
+    return f"Feedback submitted! Your Score: {score} | {progress} | {motivation}"
+
+def generate_quiz(context, theme="dark"):
+    if question_generator is None:
+        return "Question generation not available.", None, None
+    
+    try:
+        generated = question_generator(f"generate questions: {context}", max_length=50)
+        questions = generated[0]["generated_text"].split(" | ")
+        if not questions:
+            return "No questions generated.", None, None
+        
+        quiz_question = questions[0]
+        answer = qa(question=quiz_question, context=context)["answer"]
+        
+        bg_color = "black" if theme == "dark" else "white"
+        text_color = "white" if theme == "dark" else "black"
+        output = f"<div style='color:{text_color}; background-color:{bg_color}; padding:10px;'>"
+        output += f"<b>Quiz Question:</b> {quiz_question}<br><b>Answer:</b> {answer}</div>"
+        
+        tts = gTTS(text=answer, lang='en')
+        tts.save("quiz_audio.mp3")
+        
+        score = update_score(20)
+        questions_answered = update_questions_answered()
+        progress = get_progress()
+        motivation = get_motivational_message()
+        return output, "quiz_audio.mp3", f"Your Score: {score} | {progress} | {motivation}"
+    except Exception as e:
+        return f"Error generating quiz: {str(e)}", None, None
 
 with gr.Blocks(title="StudyBuddy: Accessible Study Aid for Neurodiverse Students") as app:
     gr.Markdown(
@@ -60,16 +151,32 @@ with gr.Blocks(title="StudyBuddy: Accessible Study Aid for Neurodiverse Students
         question_input = gr.Textbox(label="Question", placeholder="e.g., What is machine learning?")
         context_input = gr.Textbox(label="Context (Lecture Notes)", placeholder="Paste your notes here...")
         font_size_input = gr.Slider(12, 24, value=16, label="Font Size (px)")
+        theme_input = gr.Dropdown(choices=["dark", "light"], value="dark", label="Theme")
         audio_output_input = gr.Checkbox(label="Generate Audio Output")
         simplify_text_input = gr.Checkbox(label="Simplify Text")
         study_submit_btn = gr.Button("Get Answer")
         study_output_text = gr.HTML(label="Answer")
         study_output_audio = gr.Audio(label="Audio Narration")
+        score_output = gr.Text(label="Score & Progress")
         
         study_submit_btn.click(
             fn=study_aid,
-            inputs=[question_input, context_input, font_size_input, audio_output_input, simplify_text_input],
-            outputs=[study_output_text, study_output_audio]
+            inputs=[question_input, context_input, font_size_input, audio_output_input, simplify_text_input, theme_input],
+            outputs=[study_output_text, study_output_audio, score_output]
+        )
+    
+    with gr.Tab("Quiz Me"):
+        quiz_context_input = gr.Textbox(label="Context (Lecture Notes)", placeholder="Paste your notes here...")
+        quiz_theme_input = gr.Dropdown(choices=["dark", "light"], value="dark", label="Theme")
+        quiz_submit_btn = gr.Button("Generate Quiz Question")
+        quiz_output_text = gr.HTML(label="Quiz Question and Answer")
+        quiz_output_audio = gr.Audio(label="Audio Narration")
+        quiz_score_output = gr.Text(label="Score & Progress")
+        
+        quiz_submit_btn.click(
+            fn=generate_quiz,
+            inputs=[quiz_context_input, quiz_theme_input],
+            outputs=[quiz_output_text, quiz_output_audio, quiz_score_output]
         )
     
     with gr.Tab("Submit Feedback"):