Create app.py

app.py

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+import streamlit as st
+import google.generativeai as genai
+import PyPDF2
+import io
+import os
+
+# Set up API key
+GOOGLE_API_KEY = os.getenv('GOOGLE_API_KEY')  # Ensure this is set in the Hugging Face Spaces environment
+genai.configure(api_key=GOOGLE_API_KEY)
+
+# Initialize the Generative Model
+model = genai.GenerativeModel('gemini-pro')
+
+def extract_text_from_pdf(pdf_file):
+    """Extract text from the given PDF file."""
+    try:
+        text = ""
+        pdf_file.seek(0)
+        reader = PyPDF2.PdfReader(io.BytesIO(pdf_file.read()))
+        for page in reader.pages:
+            text += page.extract_text()
+        return text
+    except Exception as e:
+        return f"Error extracting text from PDF: {e}"
+
+def generate_quiz(text, difficulty):
+    """Generate a quiz based on the provided text and difficulty, limited to 10 questions."""
+    try:
+        prompt = (f"Based on the following text, generate a quiz with a maximum of 10 questions. "
+                  "Include both questions and answers in the format of question and answer pairs. "
+                  "Adjust the difficulty to {difficulty} level:\n\n"
+                  f"{text}\n\n"
+                  "Please provide the quiz in the format of:\n"
+                  "Q1: Question 1?\n"
+                  "A1: Answer to Question 1\n"
+                  "Q2: Question 2?\n"
+                  "A2: Answer to Question 2\n"
+                  "... and so on. Limit the total number of questions to 10.")
+        response = model.generate_content(prompt)
+        
+        # Limit the response to the first 10 questions
+        lines = response.text.split('\n')
+        limited_quiz = []
+        question_count = 0
+        
+        for line in lines:
+            if line.startswith('Q') and question_count >= 10:
+                break
+            if line.startswith('Q'):
+                question_count += 1
+            limited_quiz.append(line)
+        
+        return '\n'.join(limited_quiz)
+    except Exception as e:
+        return f"Error generating quiz: {e}"
+
+def explain_question(question):
+    """Explain the given question and its solution."""
+    try:
+        prompt = f"Explain the following question and its solution:\n{question}"
+        response = model.generate_content(prompt)
+        return response.text
+    except Exception as e:
+        return f"Error explaining question: {e}"
+
+def process_pdf(pdf_file, difficulty, explain_question_text):
+    """Process the uploaded PDF to generate and explain quiz questions."""
+    try:
+        # Extract text from the PDF
+        extracted_text = extract_text_from_pdf(pdf_file)
+        
+        # Generate a new quiz based on the extracted text
+        generated_quiz = generate_quiz(extracted_text, difficulty)
+        
+        # Explain the provided question
+        explanation = explain_question(explain_question_text)
+        
+        return generated_quiz, explanation
+    except Exception as e:
+        return f"Error processing PDF: {e}", f"Error processing PDF: {e}"
+
+def main():
+    st.title("AI Quiz Generator")
+    st.write("Upload an exam or quiz PDF to generate a new quiz with the same style and complexity. You can also ask for an explanation of any specific question.")
+    
+    uploaded_file = st.file_uploader("Upload PDF", type=["pdf"])
+    difficulty = st.selectbox("Difficulty Level", ['easy', 'medium', 'hard'])
+    explain_question_text = st.text_input("Question to Explain", "")
+
+    if st.button("Generate Quiz"):
+        if uploaded_file is not None:
+            questions_and_answers, explanation = process_pdf(uploaded_file, difficulty, explain_question_text)
+            
+            st.subheader("Generated Quiz")
+            st.text(questions_and_answers)
+            
+            st.subheader("Question Explanation")
+            st.text(explanation)
+        else:
+            st.error("Please upload a PDF file.")
+
+if __name__ == "__main__":
+    main()