Update app.py

app.py

@@ -12,16 +12,25 @@ from ast import literal_eval
 api_key = os.getenv("OPENAI_API_KEY")
 client = OpenAI(api_key = api_key)
 
+
+
 # ---------------------------
 # Helper Function: Extract text from PDF
 # ---------------------------
 def extract_text(uploaded_file):
+    # Check file size (max 10MB)
+    uploaded_file.seek(0, os.SEEK_END)
+    file_size = uploaded_file.tell()
+    uploaded_file.seek(0)
+    if file_size > 10 * 1024 * 1024:
+        st.error("File size exceeds 10MB limit.")
+        return ""
     pdf_reader = PdfReader(uploaded_file)
     text = ""
     for page in pdf_reader.pages:
         page_text = page.extract_text()
         if page_text:
-            text += page_text
+            text += page_text + "\n"
     return text
 
 # ---------------------------
@@ -29,8 +38,7 @@ def extract_text(uploaded_file):
 # ---------------------------
 def generate_summary_from_text(text):
     prompt = (
-        f"Summarize the following document in a concise manner, "
-        "highlighting the key points that a student should know:\n\n{text}"
+        f"Summarize the following document in a concise manner, highlighting the key points that a student should know:\n\n{text}"
     )
     messages = [
         {"role": "system", "content": "You are an educational assistant."},
@@ -52,11 +60,26 @@ def chat_with_document(text, conversation_history, user_query):
     )
     return completion.choices[0].message.content.strip()
 
+def generate_questions_from_text(text, num_questions):
+    prompt = (
+        f"Generate up to {num_questions} study questions with answers based on the following document.\n"
+        "Return the output as a table with two columns: 'Question' and 'Answer'.\n\nDocument:\n\n{text}"
+    )
+    messages = [
+        {"role": "system", "content": "You are an educational assistant that generates study questions."},
+        {"role": "user", "content": prompt}
+    ]
+    completion = client.chat.completions.create(
+        model="gpt-4o-mini",
+        messages=messages
+    )
+    return completion.choices[0].message.content.strip()
+
 def generate_flashcards_from_text(text, num_cards):
     prompt = (
-        f"Generate {num_cards} flashcards based on the following document. \n\nDocument:\n\n{text} "
+        f"Generate {num_cards} flashcards based on the following document.\n\nDocument:\n\n{text}\n\n"
         "Return a Python dictionary where each key is a flashcard question and its corresponding value is the answer. "
-        #"Do not include any additional text.\n\nDocument:\n\n{text}"
+        "Do not include any additional text."
     )
     messages = [
         {"role": "system", "content": "You are an educational assistant that creates study flashcards."},
@@ -68,7 +91,6 @@ def generate_flashcards_from_text(text, num_cards):
     )
     output = completion.choices[0].message.content.strip()
     try:
-        # Use literal_eval to safely evaluate the string as a Python dictionary.
         flashcards = literal_eval(output)
         if isinstance(flashcards, dict):
             return flashcards
@@ -83,12 +105,16 @@ def generate_flashcards_from_text(text, num_cards):
 # ---------------------------
 st.sidebar.title("Study Companion Setup")
 
-uploaded_pdf = st.sidebar.file_uploader("Upload your study PDF", type="pdf")
-mode = st.sidebar.radio("Select Mode", ("Summary", "Chat", "Flashcards"))
+uploaded_pdf = st.sidebar.file_uploader("Upload your study PDF (max 10MB)", type="pdf")
+mode = st.sidebar.radio("Select Mode", ("Chat", "Test Your Knowledge", "Flashcards"))
 
+# For Test Your Knowledge and Flashcards modes, allow number input.
+num_questions = None
 num_flashcards = None
-if mode == "Flashcards":
-    num_flashcards = st.sidebar.number_input("Number of flashcards to generate:", min_value=1, max_value=20, value=5, step=1)
+if mode == "Test Your Knowledge":
+    num_questions = st.sidebar.number_input("Number of questions to generate (max 50):", min_value=1, max_value=50, value=10, step=1)
+elif mode == "Flashcards":
+    num_flashcards = st.sidebar.number_input("Number of flashcards to generate (max 5):", min_value=1, max_value=5, value=3, step=1)
 
 # ---------------------------
 # Session State Initialization
@@ -99,6 +125,8 @@ if "summary" not in st.session_state:
     st.session_state.summary = None
 if "chat_history" not in st.session_state:
     st.session_state.chat_history = [{"role": "assistant", "content": "Hi, how can I help you with your study material?"}]
+if "questions_table" not in st.session_state:
+    st.session_state.questions_table = None
 if "flashcards" not in st.session_state:
     st.session_state.flashcards = {}
 if "current_card" not in st.session_state:
@@ -112,29 +140,23 @@ if "show_answer" not in st.session_state:
 # Process PDF Upload
 # ---------------------------
 if uploaded_pdf is not None:
-    with tempfile.NamedTemporaryFile(delete=False, suffix=".pdf") as tmp:
-        tmp.write(uploaded_pdf.read())
-        st.session_state.pdf_file_path = tmp.name
     st.session_state.pdf_text = extract_text(uploaded_pdf)
-    st.sidebar.success("PDF uploaded and processed successfully!")
+    if st.session_state.pdf_text:
+        st.sidebar.success("PDF uploaded and processed successfully!")
+    else:
+        st.sidebar.error("Failed to extract text. Please check your PDF file.")
 
 # ---------------------------
-# Main Area: Mode-Based Display
+# Main Area: Mode-Based Display (all functions via side menu)
 # ---------------------------
 st.title("Study Companion: PDF-based Learning")
 
 if st.session_state.pdf_text is None:
     st.info("Please upload a PDF from the sidebar to begin.")
 else:
-    if mode == "Summary":
-        st.header("Summary & Key Points")
-        if st.session_state.summary is None:
-            with st.spinner("Generating summary..."):
-                st.session_state.summary = generate_summary_from_text(st.session_state.pdf_text)
-        st.write(st.session_state.summary)
-
-    elif mode == "Chat":
+    if mode == "Chat":
         st.header("Chat with Your Study Companion")
+        # Display persistent chat history
         for msg in st.session_state.chat_history:
             st.chat_message(msg["role"]).write(msg["content"])
         user_question = st.chat_input("Ask a question about the document:")
@@ -146,6 +168,18 @@ else:
             st.session_state.chat_history.append({"role": "assistant", "content": response})
             st.chat_message("assistant").write(response)
 
+    elif mode == "Test Your Knowledge":
+        st.header("Test Your Knowledge")
+        if num_questions is None:
+            st.info("Please specify the number of questions in the sidebar.")
+        else:
+            with st.spinner("Generating questions..."):
+                questions_output = generate_questions_from_text(st.session_state.pdf_text, num_questions)
+            # Assume the output is a table in markdown format
+            st.markdown("### Generated Questions")
+            st.markdown(questions_output)
+            # Optionally, you can parse the table and display it with st.table if it's in a CSV-like format.
+
     elif mode == "Flashcards":
         st.header("Practice Flashcards")
         if st.button("Generate Flashcards"):
@@ -191,6 +225,185 @@ else:
 
 
 
+# # ---------------------------
+# # Helper Function: Extract text from PDF
+# # ---------------------------
+# def extract_text(uploaded_file):
+#     pdf_reader = PdfReader(uploaded_file)
+#     text = ""
+#     for page in pdf_reader.pages:
+#         page_text = page.extract_text()
+#         if page_text:
+#             text += page_text
+#     return text
+
+# # ---------------------------
+# # OpenAI Response Functions (using new style)
+# # ---------------------------
+# def generate_summary_from_text(text):
+#     prompt = (
+#         f"Summarize the following document in a concise manner, "
+#         "highlighting the key points that a student should know:\n\n{text}"
+#     )
+#     messages = [
+#         {"role": "system", "content": "You are an educational assistant."},
+#         {"role": "user", "content": prompt}
+#     ]
+#     completion = client.chat.completions.create(
+#         model="gpt-4o-mini",
+#         messages=messages
+#     )
+#     return completion.choices[0].message.content.strip()
+
+# def chat_with_document(text, conversation_history, user_query):
+#     messages = conversation_history + [
+#         {"role": "user", "content": f"Based on the following document:\n\n{text}\n\nQuestion: {user_query}"}
+#     ]
+#     completion = client.chat.completions.create(
+#         model="gpt-4o-mini",
+#         messages=messages
+#     )
+#     return completion.choices[0].message.content.strip()
+
+# def generate_flashcards_from_text(text, num_cards):
+#     prompt = (
+#         f"Generate {num_cards} flashcards based on the following document. \n\nDocument:\n\n{text} "
+#         "Return a Python dictionary where each key is a flashcard question and its corresponding value is the answer. "
+#         #"Do not include any additional text.\n\nDocument:\n\n{text}"
+#     )
+#     messages = [
+#         {"role": "system", "content": "You are an educational assistant that creates study flashcards."},
+#         {"role": "user", "content": prompt}
+#     ]
+#     completion = client.chat.completions.create(
+#         model="gpt-4o-mini",
+#         messages=messages
+#     )
+#     output = completion.choices[0].message.content.strip()
+#     try:
+#         # Use literal_eval to safely evaluate the string as a Python dictionary.
+#         flashcards = literal_eval(output)
+#         if isinstance(flashcards, dict):
+#             return flashcards
+#         else:
+#             return {}
+#     except Exception as e:
+#         st.error(f"Error parsing flashcards: {e}")
+#         return {}
+
+# # ---------------------------
+# # Sidebar: File Upload & Mode Selection
+# # ---------------------------
+# st.sidebar.title("Study Companion Setup")
+
+# uploaded_pdf = st.sidebar.file_uploader("Upload your study PDF", type="pdf")
+# mode = st.sidebar.radio("Select Mode", ("Summary", "Chat", "Flashcards"))
+
+# num_flashcards = None
+# if mode == "Flashcards":
+#     num_flashcards = st.sidebar.number_input("Number of flashcards to generate:", min_value=1, max_value=20, value=5, step=1)
+
+# # ---------------------------
+# # Session State Initialization
+# # ---------------------------
+# if "pdf_text" not in st.session_state:
+#     st.session_state.pdf_text = None
+# if "summary" not in st.session_state:
+#     st.session_state.summary = None
+# if "chat_history" not in st.session_state:
+#     st.session_state.chat_history = [{"role": "assistant", "content": "Hi, how can I help you with your study material?"}]
+# if "flashcards" not in st.session_state:
+#     st.session_state.flashcards = {}
+# if "current_card" not in st.session_state:
+#     st.session_state.current_card = 0
+# if "score" not in st.session_state:
+#     st.session_state.score = 0
+# if "show_answer" not in st.session_state:
+#     st.session_state.show_answer = False
+
+# # ---------------------------
+# # Process PDF Upload
+# # ---------------------------
+# if uploaded_pdf is not None:
+#     with tempfile.NamedTemporaryFile(delete=False, suffix=".pdf") as tmp:
+#         tmp.write(uploaded_pdf.read())
+#         st.session_state.pdf_file_path = tmp.name
+#     st.session_state.pdf_text = extract_text(uploaded_pdf)
+#     st.sidebar.success("PDF uploaded and processed successfully!")
+
+# # ---------------------------
+# # Main Area: Mode-Based Display
+# # ---------------------------
+# st.title("Study Companion: PDF-based Learning")
+
+# if st.session_state.pdf_text is None:
+#     st.info("Please upload a PDF from the sidebar to begin.")
+# else:
+#     if mode == "Summary":
+#         st.header("Summary & Key Points")
+#         if st.session_state.summary is None:
+#             with st.spinner("Generating summary..."):
+#                 st.session_state.summary = generate_summary_from_text(st.session_state.pdf_text)
+#         st.write(st.session_state.summary)
+
+#     elif mode == "Chat":
+#         st.header("Chat with Your Study Companion")
+#         for msg in st.session_state.chat_history:
+#             st.chat_message(msg["role"]).write(msg["content"])
+#         user_question = st.chat_input("Ask a question about the document:")
+#         if user_question:
+#             st.session_state.chat_history.append({"role": "user", "content": user_question})
+#             st.chat_message("user").write(user_question)
+#             with st.spinner("Processing your question..."):
+#                 response = chat_with_document(st.session_state.pdf_text, st.session_state.chat_history, user_question)
+#             st.session_state.chat_history.append({"role": "assistant", "content": response})
+#             st.chat_message("assistant").write(response)
+
+#     elif mode == "Flashcards":
+#         st.header("Practice Flashcards")
+#         if st.button("Generate Flashcards"):
+#             with st.spinner("Generating flashcards..."):
+#                 flashcards = generate_flashcards_from_text(st.session_state.pdf_text, num_flashcards)
+#             st.session_state.flashcards = flashcards
+#             st.session_state.current_card = 0
+#             st.session_state.score = 0
+#             st.session_state.show_answer = False
+#             st.success("Flashcards generated successfully!")
+        
+#         if not st.session_state.flashcards:
+#             st.info("No flashcards available. Click the button above to generate flashcards.")
+#         else:
+#             total_cards = len(st.session_state.flashcards)
+#             if st.session_state.current_card >= total_cards:
+#                 st.success(f"You've completed all flashcards! Final Score: {st.session_state.score} / {total_cards}")
+#                 st.info("Restart the session or generate new flashcards from the sidebar.")
+#             else:
+#                 flashcards = st.session_state.flashcards
+#                 current_keys = list(flashcards.keys())
+#                 current_question = current_keys[st.session_state.current_card]
+#                 current_answer = flashcards[current_question]
+#                 st.write(f"**Question:** {current_question}")
+#                 if st.button("Show Answer"):
+#                     st.session_state.show_answer = True
+#                 if st.session_state.show_answer:
+#                     st.write(f"**Answer:** {current_answer}")
+#                     col1, col2 = st.columns(2)
+#                     with col1:
+#                         if st.button("Correct"):
+#                             st.session_state.score += 1
+#                             st.success("Correct!")
+#                     with col2:
+#                         if st.button("Wrong"):
+#                             st.error("Incorrect!")
+#                     if st.button("Next Card"):
+#                         st.session_state.current_card += 1
+#                         st.session_state.show_answer = False
+#                         st.rerun()
+#                 st.write(f"**Current Score:** {st.session_state.score} / {total_cards}")
+
+
+
+
 # # ---------------------------
 # # Helper Function: Extract text from PDF
 # # ---------------------------