Create abc.txt

abc.txt

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+# 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')
+
+summary_clicked = st.button('Generate Summary')
+quiz_clicked = st.button('Generate Quiz')
+
+# Input for asking questions
+question_input = st.text_input("Enter your question about the document:")
+
+# Button to trigger question answering, placed after the input
+ask_question_clicked = st.button('Ask a Question')
+
+# 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 summary_clicked:
+        # 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 quiz_clicked:
+        # 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 ask_question_clicked and question_input:
+        # 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.")