Create app(backup).py

app(backup).py

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+import streamlit as st
+import openai
+import time
+
+# Set your OpenAI API key from Hugging Face Secrets
+openai.api_key = st.secrets["OPENAI_API_KEY"]
+
+# Initialize OpenAI client
+client = openai.OpenAI(api_key=openai.api_key)
+
+# Function to generate exam questions using OpenAI API with retry logic
+def generate_questions_with_retry(knowledge_material, question_type, cognitive_level, extra_instructions, case_based, num_choices=None, max_retries=3):
+    # Adjust the number of questions based on the type
+    if question_type == "Multiple Choice":
+        num_questions = 3
+    elif question_type == "Fill in the Blank":
+        num_questions = 10
+    elif question_type == "True/False":
+        num_questions = 5  # Generate 5 true/false questions
+    else:  # Open-ended
+        num_questions = 3
+
+    # Base prompt
+    prompt = f"Generate {num_questions} {question_type.lower()} exam questions based on {cognitive_level.lower()} level from the following material: {knowledge_material}. {extra_instructions}"
+
+    # If case-based medical situation is selected, modify the prompt
+    if case_based:
+        prompt = f"Generate {num_questions} {question_type.lower()} exam questions based on {cognitive_level.lower()} level from the following medical material: {knowledge_material}. The questions should be based on case-based medical situations, such as patient scenarios. {extra_instructions}"
+        if question_type != "Fill in the Blank":
+            prompt += " Provide answers with short explanations."
+
+    # Add specific handling for Multiple Choice and True/False
+    if question_type == "Multiple Choice" and num_choices:
+        prompt += f" Each multiple choice question should have {num_choices} choices."
+
+    if question_type == "True/False":
+        prompt += " Provide short explanations for each question based on the given material, without stating True or False explicitly."
+
+    retries = 0
+    while retries < max_retries:
+        try:
+            response = client.chat.completions.create(
+                model="gpt-4o-mini",
+                messages=[
+                    {"role": "system", "content": "You are a helpful assistant for generating exam questions."},
+                    {"role": "user", "content": prompt}
+                ]
+            )
+            return response.choices[0].message.content
+        except openai.error.APIConnectionError:
+            retries += 1
+            time.sleep(2)  # Wait for 2 seconds before retrying
+            if retries == max_retries:
+                st.error("Failed to connect to OpenAI API after several attempts.")
+                return None
+
+# Login page
+if 'username' not in st.session_state:
+    # Show the login form if the username is not set
+    st.title("Login")
+    username_input = st.text_input("Enter your username:")
+    if st.button("Login"):
+        if username_input:
+            st.session_state['username'] = username_input
+            st.success(f"Welcome, {username_input}!")
+        else:
+            st.warning("Please enter a valid username.")
+else:
+    # Main App after login
+    st.title(f"Welcome, {st.session_state['username']}! Generate your exam questions")
+
+    # Input field for knowledge material (text) with 3,000-word limit
+    knowledge_material = st.text_area("Enter knowledge material to generate exam questions:")
+    
+    # Word count check
+    if len(knowledge_material.split()) > 3000:
+        st.warning("Please limit the knowledge material to 3,000 words or fewer.")
+
+    # File uploader for PDFs (limited to 5 MB)
+    uploaded_file = st.file_uploader("Upload a file (PDF)", type="pdf")
+    
+    if uploaded_file is not None:
+        if uploaded_file.size > 5 * 1024 * 1024:  # 5 MB limit
+            st.warning("File size exceeds 5 MB. Please upload a smaller file.")
+        else:
+            # Here you can add code to extract text from the PDF if needed
+            # For simplicity, we're focusing on the text input for now
+            st.success("File uploaded successfully! (Text extraction not implemented yet.)")
+
+    # Select question type
+    question_type = st.selectbox("Select question type:", 
+                                 ["Multiple Choice", "Fill in the Blank", "Open-ended", "True/False"])
+
+    # For multiple choice, let users select the number of choices
+    num_choices = None
+    if question_type == "Multiple Choice":
+        num_choices = st.selectbox("Select the number of choices for each question:", [3, 4, 5])
+
+    # Select cognitive level
+    cognitive_level = st.selectbox("Select cognitive level:", 
+                                   ["Recall", "Understanding", "Application", "Analysis", "Synthesis", "Evaluation"])
+
+    # Checkbox for Case-Based Medical Situations
+    case_based = st.checkbox("Generate case-based medical exam questions")
+
+    # Extra input field for additional instructions (placed below cognitive level)
+    extra_instructions = st.text_area("Enter additional instructions (e.g., how you want the questions to be phrased):")
+
+    # Generate questions button
+    if 'previous_questions' not in st.session_state:
+        st.session_state['previous_questions'] = []
+
+    if st.button("Generate Questions"):
+        if len(knowledge_material.split()) <= 3000:
+            # Generate questions with retry logic
+            questions = generate_questions_with_retry(
+                knowledge_material, 
+                question_type, 
+                cognitive_level, 
+                extra_instructions, 
+                case_based, 
+                num_choices
+            )
+            
+            if questions:
+                st.write("Generated Exam Questions:")
+                st.write(questions)
+
+                # Avoid showing repeated content in future requests
+                st.session_state['previous_questions'].append(questions)
+
+                # Option to download the questions as a text file
+                st.download_button(
+                    label="Download Questions",
+                    data=questions,
+                    file_name='generated_questions.txt',
+                    mime='text/plain'
+                )
+        else:
+            st.warning("Please reduce the word count to 3,000 or fewer.")
+
+    # Button to generate more questions based on the same material
+    if st.button("Generate More Questions"):
+        if len(knowledge_material.split()) <= 3000:
+            # Regenerate new questions, trying to avoid repeated content
+            questions = generate_questions_with_retry(
+                knowledge_material, 
+                question_type, 
+                cognitive_level, 
+                extra_instructions, 
+                case_based, 
+                num_choices
+            )
+
+            # Check if the new set of questions is not the same as the previous set
+            if questions and questions not in st.session_state['previous_questions']:
+                st.write("Generated More Exam Questions:")
+                st.write(questions)
+
+                # Append the new questions to the session state
+                st.session_state['previous_questions'].append(questions)
+
+                # Option to download the new set of questions
+                st.download_button(
+                    label="Download More Questions",
+                    data=questions,
+                    file_name='more_generated_questions.txt',
+                    mime='text/plain'
+                )
+            else:
+                st.warning("New questions seem to overlap with the previous ones. Try adjusting the instructions.")
+        else:
+            st.warning("Please reduce the word count to 3,000 or fewer.")