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 from PIL import Image # Set up Streamlit UI st.title('Educational Assistant') img = Image.open("image.jpeg") # Ensure the file is in the correct directory st.image(img, width=300) # Adjust the size as per preference st.header('Summary, Quiz Generator, Q&A, and Study Plan') st.sidebar.title('Drop your PDF here') # Instructions in the sidebar with st.sidebar.expander("Instructions on how to use this app"): st.markdown(""" **Welcome to the Educational Assistant!** Here's how you can use the app: 1. **Enter your OpenAI API Key**: You need to enter your OpenAI API key in the sidebar (password type) to authenticate your requests. 2. **Upload a PDF file**: Click on the 'Upload PDF' button to upload the document you want to analyze. 3. **Select an Option**: Choose one of the options: - **Generate Summary**: Generate a concise summary of the content in your uploaded PDF. - **Generate Quiz**: Create a quiz with multiple-choice questions based on the content of your PDF. - **Ask a Question**: Ask a specific question about the content, and get a detailed answer. - **Generate Study Plan**: Generate a logical 7-day study plan based on the content in your PDF. 4. **Download PDF**: Once the result is generated, you will be able to download it as a PDF. Happy learning! """) # 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, Q&A, or Study Plan option = st.sidebar.radio("Choose an option", ('Generate Summary', 'Generate Quiz', 'Ask a Question', 'Generate Study Plan')) # 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 ## Prompt Template for Study Plan prompt_4 = ChatPromptTemplate.from_messages( [ ("system", "You are a smart assistant. Based on the content of the user's PDF, generate a 7-day study plan. Divide the content into 7 topics and assign each topic to a day. Please make it logical and balanced."), ("user", "{data}") ] ) # Pass the OpenAI API key explicitly to the ChatOpenAI instance llm_study_plan = ChatOpenAI(model="gpt-4o-mini", openai_api_key=openai_api_key) # Pass the key here output_parser = StrOutputParser() chain_4 = prompt_4 | llm_study_plan | 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") elif option == 'Generate Study Plan': # Generate study plan study_plan_response = chain_4.invoke({'data': data}) st.write(study_plan_response) # Generate PDF for the study plan and offer it as a download pdf_filename = generate_pdf(study_plan_response, filename="study_plan_response.pdf") st.download_button("Download Study Plan 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.")