Update app.py

app.py

@@ -16,6 +16,73 @@ embedding_model = SentenceTransformer('distilbert-base-uncased')
 # Streamlit UI
 st.title("RAG-based Quiz App")
 
+# File Upload
+uploaded_file = st.file_uploader("Upload a PDF", type="pdf")
+if uploaded_file is not None:
+    # Extract Text from PDF
+    pdf_reader = PdfReader(uploaded_file)
+    text = " ".join([page.extract_text() for page in pdf_reader.pages])
+    
+    # Chunking Text
+    st.write("Processing the PDF...")
+    chunk_size = 500
+    chunks = [text[i:i + chunk_size] for i in range(0, len(text), chunk_size)]
+    
+    # Create Embeddings
+    embeddings = embedding_model.encode(chunks)
+    embeddings = np.array(embeddings, dtype="float32")
+    
+    # FAISS Index
+    index = faiss.IndexFlatL2(embeddings.shape[1])
+    index.add(embeddings)
+    
+    st.success("PDF Processed! Embeddings Created.")
+    
+    # Generate Questions
+    st.write("Generating Quiz Questions...")
+    questions = []
+    for chunk in chunks[:3]:  # Process fewer chunks to improve performance
+        response = client.chat.completions.create(
+            messages=[{"role": "user", "content": f"Create a multiple-choice quiz question from this text: {chunk}"}],
+            model="llama3-8b-8192"
+        )
+        question = response.choices[0].message.content
+        questions.append(question)
+    
+    st.success("Quiz Questions Generated!")
+    
+    # Display Quiz
+    for idx, question in enumerate(questions):
+        st.write(f"**Question {idx+1}:** {question}")
+        
+        # Parse Question to Extract Correct Answer (Assuming the API formats it consistently)
+        # Example format: "Question: ... Options: A) ..., B) ..., C) ..., D) ... Correct: A"
+        lines = question.split("\n")
+        options = [line.split(") ")[1] for line in lines if line.strip().startswith(("A", "B", "C", "D"))]
+        correct_option_line = [line for line in lines if "Correct:" in line]
+        correct_option = correct_option_line[0].split(": ")[1].strip() if correct_option_line else None
+        
+        selected_option = st.radio(f"Select your answer for Question {idx+1}", options, key=idx)
+        
+        if st.button(f"Submit Answer for Question {idx+1}", key=f"submit_{idx}"):
+            if selected_option == correct_option:
+                st.success("Correct Answer!")
+            else:
+                st.error(f"Wrong Answer! Correct Answer: {correct_option}")
+            
+            # Highlight Correct and Selected Options
+            st.write(f"**Correct Option:** {correct_option}")
+            st.write(f"**Your Selection:** {selected_option}")
+
+# Footer
+st.write("App developed and deployed using Hugging Face Spaces.")
+
+# Initialize Embedding Model
+embedding_model = SentenceTransformer('distilbert-base-uncased')
+
+# Streamlit UI
+st.title("RAG-based Quiz App")
+
 # File Upload
 uploaded_file = st.file_uploader("Upload a PDF", type="pdf")
 if uploaded_file is not None: