Study_guide / app.py
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import streamlit as st
import tempfile
import json
import random
from pathlib import Path
from PyPDF2 import PdfReader
from openai import OpenAI
import os
from ast import literal_eval
# Initialize the OpenAI client
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 + "\n"
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_questions_from_text(text, num_questions):
prompt = (
f"Generate up to {num_questions} study questions with answers based on the following document.\n"
f"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}\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."
)
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:
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 (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 == "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
# ---------------------------
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 "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:
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:
st.session_state.pdf_text = extract_text(uploaded_pdf)
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 (all functions via side menu)
# ---------------------------
st.title("Study Companion 📚")
if st.session_state.pdf_text is None:
st.info("Please upload a PDF from the sidebar to begin.")
else:
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:")
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 == "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"):
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}")
# # Import the CrewAI flashcard module (modified below to remove page range)
# from crewai_flashcard import generate_flashcards
# # ---------------------------
# # Helper Function: Extract text from PDF
# # ---------------------------
# def extract_text(uploaded_file):
# # Ensure file size is less than 10MB
# uploaded_file.seek(0, os.SEEK_END)
# if uploaded_file.tell() > 10 * 1024 * 1024:
# st.error("File exceeds 10MB limit.")
# return ""
# uploaded_file.seek(0)
# pdf_reader = PdfReader(uploaded_file)
# text = ""
# for page in pdf_reader.pages:
# page_text = page.extract_text()
# if page_text:
# text += page_text + "\n"
# return text
# # ---------------------------
# # OpenAI Response Functions
# # ---------------------------
# 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_questions_from_text(text, num_questions):
# prompt = (
# f"Generate {num_questions} study questions with answers based on the following document. "
# "Return the output as a table in CSV format 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
# )
# # Expecting CSV output (with header: Question,Answer)
# return completion.choices[0].message.content.strip()
# # ---------------------------
# # Sidebar: File Upload & Mode Selection
# # ---------------------------
# st.sidebar.title("Study Companion Setup")
# 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: number of questions (max 50)
# num_questions = None
# 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)
# if st.sidebar.button("Generate Questions"):
# st.session_state.gen_questions = True
# # For Flashcards: number of flashcards (max 5)
# num_flashcards = None
# if 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)
# if st.sidebar.button("Generate Flashcards"):
# st.session_state.gen_flashcards = True
# # ---------------------------
# # 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 "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:
# 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)
# if st.session_state.pdf_text:
# st.sidebar.success("PDF uploaded and processed successfully!")
# else:
# st.sidebar.error("Failed to extract text from the PDF.")
# # ---------------------------
# # Main Area: Mode-Based Display (using 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 == "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 == "Test Your Knowledge":
# st.header("Test Your Knowledge")
# if num_questions is None or not st.session_state.get("gen_questions", False):
# st.info("Enter the number of questions and press 'Generate Questions' from the sidebar.")
# else:
# with st.spinner("Generating questions..."):
# questions_csv = generate_questions_from_text(st.session_state.pdf_text, num_questions)
# # Convert CSV output into a table (assuming header row "Question,Answer")
# try:
# lines = questions_csv.splitlines()
# if len(lines) < 2:
# st.error("Failed to generate questions properly.")
# else:
# header = lines[0].split(",")
# data = [line.split(",") for line in lines[1:]]
# st.table(data, headers=header)
# st.session_state.questions_table = data
# except Exception as e:
# st.error(f"Error processing questions: {e}")
# elif mode == "Flashcards":
# st.header("Practice Flashcards")
# if not st.session_state.get("gen_flashcards", False):
# st.info("Enter the number of flashcards and press 'Generate Flashcards' from the sidebar.")
# else:
# if st.button("Reset Flashcards"):
# st.session_state.flashcards = {}
# st.session_state.current_card = 0
# st.session_state.score = 0
# st.session_state.show_answer = False
# st.session_state.gen_flashcards = False
# if st.session_state.get("gen_flashcards", False):
# # Generate flashcards using the CrewAI module (which returns a Python dictionary)
# flashcards = generate_flashcards(st.session_state.pdf_file_path, 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!")
# st.session_state.gen_flashcards = False # reset flag after generation
# if not st.session_state.flashcards:
# st.info("No flashcards available. Click the 'Generate Flashcards' button in the sidebar.")
# 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
# # ---------------------------
# 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
# # ---------------------------
# 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):
# # Build a message list that includes the conversation history plus the new query with context.
# 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. "
# "Return a Python dictionary (in valid JSON format) where each key is a flashcard question and its value is the corresponding answer. "
# f"Document:\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:
# flashcards = json.loads(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"))
# # For Flashcards, allow user to input number of 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())
# pdf_file_path = tmp.name
# # Extract text from the PDF (all pages)
# st.session_state.pdf_text = extract_text(pdf_file_path)
# 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")
# # 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:")
# 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")
# # Provide a button to generate flashcards on demand.
# 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
# # Get the current flashcard key-value pair.
# current_keys = list(flashcards.keys())
# current_key = current_keys[st.session_state.current_card]
# current_answer = flashcards[current_key]
# st.write(f"**Question:** {current_key}")
# 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}")