# Import necessary libraries import streamlit as st from langchain_community.document_loaders import PyPDFLoader import openai from langchain.prompts import ChatPromptTemplate from langchain_core.output_parsers import StrOutputParser from langchain.chat_models import ChatOpenAI from fpdf import FPDF import os # Set up Streamlit UI st.title('Educational Assistant') st.header('Summary, Quiz Generator, and Q&A') st.sidebar.title('Drop your PDF here') # Input OpenAI API key from keyboard openai_api_key = st.sidebar.text_input("Enter your OpenAI API Key", type="password") user_file_upload = st.sidebar.file_uploader(label='', type='pdf') # Sidebar option selection for Summary, Quiz, or Q&A option = st.sidebar.radio("Choose an option", ('Generate Summary', 'Generate Quiz', 'Ask a Question')) # Input for asking questions (only visible when "Ask a Question" is selected) question_input = None if option == 'Ask a Question': question_input = st.text_input("Enter your question about the document:") # Function to generate a PDF and allow download def generate_pdf(response, filename="response.pdf"): pdf = FPDF() pdf.add_page() # Adding a Unicode-compatible font (like Arial Unicode MS or other compatible font) pdf.add_font('ArialUnicode', '', 'arialuni.ttf', uni=True) # Path to font, make sure this is correct for your system pdf.set_font('ArialUnicode', '', 12) # Add the response text pdf.multi_cell(0, 10, response) # Save to a temporary file pdf.output(filename) # Return the file path return filename if openai_api_key: # Set OpenAI API key openai.api_key = openai_api_key if user_file_upload: # Read the uploaded file pdf_data = user_file_upload.read() # Save the uploaded file to a temporary location with open("temp_pdf_file.pdf", "wb") as f: f.write(pdf_data) # Load the temporary PDF file loader = PyPDFLoader("temp_pdf_file.pdf") data = loader.load_and_split() ## Prompt Template for Summary prompt_1 = ChatPromptTemplate.from_messages( [ ("system", "You are a smart assistant. Give a summary of the user's PDF. Be polite."), ("user", "{data}") ] ) # Pass the OpenAI API key explicitly to the ChatOpenAI instance llm_summary = ChatOpenAI(model="gpt-4o-mini", openai_api_key=openai_api_key) # Pass the key here output_parser = StrOutputParser() chain_1 = prompt_1 | llm_summary | output_parser ## Prompt Template for Quiz prompt_2 = ChatPromptTemplate.from_messages( [ ("system", "You are a smart assistant. Generate 10 multiple-choice quiz questions with 4 options each (including correct and incorrect options) from the user's PDF. Please also include the correct answer in your response. Be polite."), ("user", "{data}") ] ) # Pass the OpenAI API key explicitly to the ChatOpenAI instance llm_quiz = ChatOpenAI(model="gpt-4o-mini", openai_api_key=openai_api_key) # Pass the key here output_parser = StrOutputParser() chain_2 = prompt_2 | llm_quiz | output_parser ## Prompt Template for Question-Answering prompt_3 = ChatPromptTemplate.from_messages( [ ("system", "You are a smart assistant. Answer the user's question based on the content of the PDF. Be polite."), ("user", "{data}\n\nUser's question: {question}") ] ) # Pass the OpenAI API key explicitly to the ChatOpenAI instance llm_qa = ChatOpenAI(model="gpt-4o-mini", openai_api_key=openai_api_key) # Pass the key here output_parser = StrOutputParser() chain_3 = prompt_3 | llm_qa | output_parser if option == 'Generate Summary': # Generate summary summary_response = chain_1.invoke({'data': data}) st.write(summary_response) # Generate PDF for the summary and offer it as a download pdf_filename = generate_pdf(summary_response, filename="summary_response.pdf") st.download_button("Download Summary as PDF", data=open(pdf_filename, "rb").read(), file_name=pdf_filename, mime="application/pdf") elif option == 'Generate Quiz': # Generate quiz quiz_response = chain_2.invoke({'data': data}) st.write(quiz_response) # Generate PDF for the quiz and offer it as a download pdf_filename = generate_pdf(quiz_response, filename="quiz_response.pdf") st.download_button("Download Quiz as PDF", data=open(pdf_filename, "rb").read(), file_name=pdf_filename, mime="application/pdf") elif option == 'Ask a Question' and question_input: # Add a "Generate Answer" button generate_answer = st.button("Generate Answer") if generate_answer: # Generate answer for the user's question question_answer_response = chain_3.invoke({'data': data, 'question': question_input}) st.write(question_answer_response) # Generate PDF for the question answer and offer it as a download pdf_filename = generate_pdf(question_answer_response, filename="question_answer_response.pdf") st.download_button("Download Answer as PDF", data=open(pdf_filename, "rb").read(), file_name=pdf_filename, mime="application/pdf") else: st.sidebar.warning("Please enter your OpenAI API Key to proceed.")