Update app.py

app.py

@@ -2,46 +2,79 @@ import streamlit as st
 import random
 
 # ------------------------------
-# Quiz Data (10 categories × 10 questions)
+# Quiz Data (10 categories × 5 questions each)
 # ------------------------------
 quizzes = {
     "Science": [
         {"question": "What planet is known as the Red Planet?", "options": ["Earth", "Mars", "Venus", "Jupiter"], "answer": "Mars"},
-        {"question": "Which gas do plants absorb?", "options": ["Oxygen", "Carbon Dioxide", "Nitrogen", "Hydrogen"], "answer": "Carbon Dioxide"},
+        {"question": "What gas do plants absorb?", "options": ["Oxygen", "Carbon Dioxide", "Nitrogen", "Hydrogen"], "answer": "Carbon Dioxide"},
         {"question": "Water freezes at what temperature (C)?", "options": ["0", "32", "-10", "100"], "answer": "0"},
         {"question": "What organ produces insulin?", "options": ["Liver", "Heart", "Pancreas", "Lung"], "answer": "Pancreas"},
         {"question": "What is the chemical symbol for gold?", "options": ["Au", "Ag", "Go", "Gd"], "answer": "Au"},
-        {"question": "What is the speed of light?", "options": ["300,000 km/s", "150,000 km/s", "500,000 km/s", "100,000 km/s"], "answer": "300,000 km/s"},
-        {"question": "Which gas is most abundant in the Earth's atmosphere?", "options": ["Oxygen", "Carbon Dioxide", "Nitrogen", "Hydrogen"], "answer": "Nitrogen"},
-        {"question": "What planet has the most moons?", "options": ["Jupiter", "Saturn", "Uranus", "Neptune"], "answer": "Saturn"},
-        {"question": "Which vitamin is produced in human skin in response to sunlight?", "options": ["A", "B12", "C", "D"], "answer": "D"},
-        {"question": "Which element has the atomic number 1?", "options": ["Oxygen", "Helium", "Hydrogen", "Carbon"], "answer": "Hydrogen"},
     ],
     "Artificial Intelligence (AI)": [
         {"question": "What does AI stand for?", "options": ["Artificial Intelligence", "Automatic Integration", "Automated Interface", "Actual Intelligence"], "answer": "Artificial Intelligence"},
-        {"question": "Which language is most used in AI?", "options": ["Python", "C++", "Java", "Ruby"], "answer": "Python"},
-        {"question": "Which algorithm is used for classification?", "options": ["KNN", "Gradient Descent", "PCA", "K-Means"], "answer": "KNN"},
-        {"question": "What is Turing Test used for?", "options": ["Test intelligence", "Test speed", "Test memory", "Test CPU"], "answer": "Test intelligence"},
-        {"question": "Which AI model is used for text generation?", "options": ["GPT", "CNN", "KNN", "SVM"], "answer": "GPT"},
-        {"question": "Which company developed ChatGPT?", "options": ["Google", "Facebook", "OpenAI", "Microsoft"], "answer": "OpenAI"},
-        {"question": "Which term describes AI that can learn from data?", "options": ["Machine Learning", "Hardcoding", "Compilation", "Automation"], "answer": "Machine Learning"},
-        {"question": "Which AI field handles speech recognition?", "options": ["NLP", "CV", "ML", "DL"], "answer": "NLP"},
-        {"question": "What is an agent in AI?", "options": ["Performer of actions", "Debugger", "Toolbox", "Compiler"], "answer": "Performer of actions"},
-        {"question": "AI that mimics human brain is called?", "options": ["Neural Network", "SVM", "Logistic Regression", "KNN"], "answer": "Neural Network"},
+        {"question": "Which company developed ChatGPT?", "options": ["Google", "Meta", "OpenAI", "Microsoft"], "answer": "OpenAI"},
+        {"question": "Which model is used for generating human-like text?", "options": ["CNN", "GPT", "RNN", "SVM"], "answer": "GPT"},
+        {"question": "Turing Test is used to test?", "options": ["Intelligence", "Speed", "Memory", "Computation"], "answer": "Intelligence"},
+        {"question": "Which is not a type of AI?", "options": ["Narrow AI", "General AI", "Super AI", "Organic AI"], "answer": "Organic AI"},
     ],
     "Machine Learning (ML)": [
-        {"question": "ML stands for?", "options": ["Machine Learning", "Manual Learning", "Mathematical Logic", "Modern Language"], "answer": "Machine Learning"},
-        {"question": "Which type of ML uses labeled data?", "options": ["Supervised", "Unsupervised", "Reinforcement", "Self-Learning"], "answer": "Supervised"},
-        {"question": "K-Means is used for?", "options": ["Classification", "Regression", "Clustering", "Prediction"], "answer": "Clustering"},
+        {"question": "Which of the following is a supervised learning algorithm?", "options": ["K-Means", "Linear Regression", "PCA", "DBSCAN"], "answer": "Linear Regression"},
+        {"question": "ML uses what to make predictions?", "options": ["Data", "Rules", "Hardware", "Code"], "answer": "Data"},
         {"question": "Which library is used in ML?", "options": ["NumPy", "Pandas", "Scikit-learn", "OpenCV"], "answer": "Scikit-learn"},
-        {"question": "Which is NOT an ML algorithm?", "options": ["SVM", "CNN", "Decision Tree", "KNN"], "answer": "CNN"},
-        {"question": "Which algorithm is used for regression?", "options": ["Linear Regression", "Naive Bayes", "PCA", "KNN"], "answer": "Linear Regression"},
-        {"question": "Overfitting happens when?", "options": ["Model learns too much", "Too little data", "Too much bias", "None"], "answer": "Model learns too much"},
-        {"question": "Which technique is used to reduce features?", "options": ["PCA", "KNN", "SVM", "RNN"], "answer": "PCA"},
-        {"question": "Which of these is a tree-based method?", "options": ["Random Forest", "SVM", "Naive Bayes", "PCA"], "answer": "Random Forest"},
-        {"question": "Which concept measures error?", "options": ["Loss function", "Activation", "Weight", "Bias"], "answer": "Loss function"},
+        {"question": "Which is not an ML algorithm?", "options": ["SVM", "CNN", "Decision Tree", "KNN"], "answer": "CNN"},
+        {"question": "What type of data does supervised learning require?", "options": ["Unlabeled", "Categorical", "Labeled", "Binary"], "answer": "Labeled"},
     ],
-    # Add more categories like Deep Learning, CV, Health, Environment, Math, etc. below...
+    "Deep Learning (DL)": [
+        {"question": "Deep Learning is a subset of?", "options": ["Machine Learning", "Data Mining", "Statistics", "Robotics"], "answer": "Machine Learning"},
+        {"question": "Which architecture is common in DL?", "options": ["CNN", "SVM", "KNN", "PCA"], "answer": "CNN"},
+        {"question": "Which library is used for DL?", "options": ["TensorFlow", "NumPy", "Matplotlib", "OpenCV"], "answer": "TensorFlow"},
+        {"question": "RNNs are best for what type of data?", "options": ["Images", "Time Series", "Tables", "Graphs"], "answer": "Time Series"},
+        {"question": "Which function is used in neural networks?", "options": ["Activation", "Loss", "Gradient", "Bias"], "answer": "Activation"},
+    ],
+    "Computer Vision (CV)": [
+        {"question": "What is the goal of CV?", "options": ["Understand images", "Translate text", "Play games", "Store files"], "answer": "Understand images"},
+        {"question": "Which library is popular in CV?", "options": ["OpenCV", "Pandas", "Flask", "Numpy"], "answer": "OpenCV"},
+        {"question": "What technique is used for object detection?", "options": ["YOLO", "RNN", "PCA", "SVM"], "answer": "YOLO"},
+        {"question": "What file format is NOT an image?", "options": ["JPG", "PNG", "TXT", "GIF"], "answer": "TXT"},
+        {"question": "Which model type is used for image classification?", "options": ["CNN", "RNN", "LSTM", "DBSCAN"], "answer": "CNN"},
+    ],
+    "Health": [
+        {"question": "Which vitamin is gained from sunlight?", "options": ["A", "B12", "C", "D"], "answer": "D"},
+        {"question": "What is the normal human body temperature?", "options": ["36.5°C", "37°C", "38°C", "39°C"], "answer": "37°C"},
+        {"question": "Which organ pumps blood?", "options": ["Lungs", "Liver", "Heart", "Kidney"], "answer": "Heart"},
+        {"question": "Which disease affects lungs?", "options": ["Asthma", "Diabetes", "Arthritis", "Jaundice"], "answer": "Asthma"},
+        {"question": "What nutrient builds muscle?", "options": ["Protein", "Carbohydrate", "Fat", "Sugar"], "answer": "Protein"},
+    ],
+    "Environment": [
+        {"question": "Which gas causes global warming?", "options": ["CO2", "O2", "N2", "H2"], "answer": "CO2"},
+        {"question": "What is the main source of air pollution?", "options": ["Vehicles", "Trees", "Wind", "Mountains"], "answer": "Vehicles"},
+        {"question": "Which is a renewable resource?", "options": ["Solar", "Coal", "Oil", "Gas"], "answer": "Solar"},
+        {"question": "Which layer protects us from UV rays?", "options": ["Ozone", "Clouds", "Stratosphere", "Troposphere"], "answer": "Ozone"},
+        {"question": "Which ocean is the largest?", "options": ["Atlantic", "Pacific", "Indian", "Arctic"], "answer": "Pacific"},
+    ],
+    "Mathematics": [
+        {"question": "What is 12 × 8?", "options": ["96", "108", "88", "104"], "answer": "96"},
+        {"question": "Square root of 64?", "options": ["6", "7", "8", "9"], "answer": "8"},
+        {"question": "π (Pi) value to 2 decimal places?", "options": ["3.12", "3.14", "3.16", "3.18"], "answer": "3.14"},
+        {"question": "What is 15% of 200?", "options": ["30", "25", "20", "35"], "answer": "30"},
+        {"question": "What is 100 ÷ 5?", "options": ["20", "15", "10", "25"], "answer": "20"},
+    ],
+    "Literature": [
+        {"question": "Who wrote 'Hamlet'?", "options": ["Shakespeare", "Chaucer", "Shelley", "Austen"], "answer": "Shakespeare"},
+        {"question": "'Pride and Prejudice' author?", "options": ["Jane Austen", "Bronte", "Eliot", "Shelley"], "answer": "Jane Austen"},
+        {"question": "Sherlock Holmes creator?", "options": ["Doyle", "Christie", "Rowling", "Brown"], "answer": "Doyle"},
+        {"question": "Which book starts with 'Call me Ishmael'?", "options": ["Moby Dick", "Odyssey", "Ulysses", "Don Quixote"], "answer": "Moby Dick"},
+        {"question": "Language of 'Les Misérables'?", "options": ["French", "English", "German", "Spanish"], "answer": "French"},
+    ],
+    "History": [
+        {"question": "First President of USA?", "options": ["Lincoln", "Washington", "Adams", "Jefferson"], "answer": "Washington"},
+        {"question": "Year WWII ended?", "options": ["1945", "1939", "1950", "1940"], "answer": "1945"},
+        {"question": "Pyramids built by?", "options": ["Egyptians", "Romans", "Greeks", "Mayans"], "answer": "Egyptians"},
+        {"question": "Who discovered America?", "options": ["Columbus", "Da Gama", "Magellan", "Marco Polo"], "answer": "Columbus"},
+        {"question": "Start of Industrial Revolution?", "options": ["England", "France", "USA", "Germany"], "answer": "England"},
+    ]
 }
 
 # ------------------------------
@@ -59,12 +92,7 @@ def evaluate(questions):
         is_correct = selected == correct
         if is_correct:
             score += 1
-        results.append({
-            "question": q["question"],
-            "selected": selected,
-            "correct": correct,
-            "is_correct": is_correct
-        })
+        results.append({"question": q["question"], "selected": selected, "correct": correct, "is_correct": is_correct})
     return score, results
 
 def show_feedback(score):
@@ -80,37 +108,45 @@ def show_feedback(score):
 # ------------------------------
 st.set_page_config(page_title="BrainQuest AI", layout="centered")
 
+# First page welcome screen
+if "started" not in st.session_state:
+    st.session_state.started = False
+
+if not st.session_state.started:
+    st.markdown("""
+        <div style='text-align:center;'>
+            <h1 style='font-size:48px;'>🎓 Welcome to BrainQuest AI</h1>
+            <p style='font-size:24px;'>Test your knowledge across 10 powerful fields</p>
+            <br>
+            <form action="/">
+                <input type="submit" value="🚀 Get Started Now" style="font-size:24px; padding:10px 30px; background-color:#4CAF50; color:white; border:none; border-radius:10px;">
+            </form>
+        </div>
+    """, unsafe_allow_html=True)
+    if st.button("Get Started Now"):
+        st.session_state.started = True
+    st.stop()
+
+# Sidebar
 with st.sidebar:
     st.title("ℹ️ About")
     st.markdown("""
     **🎓 BrainQuest AI**
-    
-    - Educational Quiz App  
+    - 10 Dynamic Categories  
     - Built with ❤️ by **Sabir Ali**  
-    - Responsive & Offline  
-    - No login, No database  
+    - Fully Offline, Fast & Engaging
     """)
 
-st.title("🎓 BrainQuest AI")
-st.subheader("Test your knowledge across various fields")
-st.markdown("---")
-
-# Session Initialization
-if "questions" not in st.session_state:
-    st.session_state.questions = []
-    st.session_state.submitted = False
-
-# Category Selection
-category = st.selectbox("📘 Choose a Category", list(quizzes.keys()))
+st.title("🧠 Choose a Quiz Category")
+category = st.selectbox("📘 Select Category", list(quizzes.keys()))
 
-if st.button("🚀 Start Quiz"):
+if st.button("Start Quiz"):
     st.session_state.questions = load_questions(category)
     st.session_state.submitted = False
     for i in range(5):
         st.session_state[f"answer_{i}"] = None
 
-# Display Quiz Questions
-if st.session_state.questions and not st.session_state.submitted:
+if "questions" in st.session_state and not st.session_state.submitted:
     for i, q in enumerate(st.session_state.questions):
         st.markdown(f"**Q{i+1}:** {q['question']}")
         st.radio("Your Answer:", q["options"], key=f"answer_{i}", label_visibility="collapsed")
@@ -121,7 +157,7 @@ if st.session_state.questions and not st.session_state.submitted:
         score, results = evaluate(st.session_state.questions)
         show_feedback(score)
 
-        st.markdown("## 📝 Result Summary")
+        st.markdown("## 📊 Results Summary")
         for i, r in enumerate(results):
             emoji = "✅" if r["is_correct"] else "❌"
             st.markdown(f"**Q{i+1}:** {r['question']}")
@@ -130,6 +166,6 @@ if st.session_state.questions and not st.session_state.submitted:
                 st.markdown(f"- Correct answer: `{r['correct']}`")
             st.markdown("---")
 
-        if st.button("🔄 Try Another Quiz"):
+        if st.button("🔁 Try Another Quiz"):
             st.session_state.questions = []
             st.session_state.submitted = False