| 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, Q&A, and Study Plan') | |
| 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, 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.") |