Update app.py

app.py

@@ -1,3 +1,4 @@
+# Import necessary libraries
 import streamlit as st
 from langchain_community.document_loaders import PyPDFLoader
 import openai
@@ -6,22 +7,19 @@ from langchain_core.output_parsers import StrOutputParser
 from langchain.chat_models import ChatOpenAI
 from fpdf import FPDF
 import os
-from datetime import datetime, timedelta
-import speech_recognition as sr
-import calendar
 
 # Set up Streamlit UI
 st.title('Educational Assistant')
 st.header('Summary, Quiz Generator, and Q&A')
-st.sidebar.title('Drop your PDF or Audio file here')
+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', 'mp3'])
+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', 'Daily Study Plan'))
+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
@@ -46,46 +44,22 @@ def generate_pdf(response, filename="response.pdf"):
     # Return the file path
     return filename
 
-# Function to handle voice-to-text conversion
-def convert_audio_to_text(audio_file):
-    recognizer = sr.Recognizer()
-    
-    with sr.AudioFile(audio_file) as source:
-        audio = recognizer.record(source)
-    
-    try:
-        text = recognizer.recognize_google(audio)
-        return text
-    except sr.UnknownValueError:
-        return "Sorry, I couldn't understand the audio."
-    except sr.RequestError:
-        return "Sorry, there was an error with the speech-to-text service."
-
 if openai_api_key:
     # Set OpenAI API key
     openai.api_key = openai_api_key
 
     if user_file_upload:
-        # Check if the file is PDF or Audio
-        if user_file_upload.type == 'application/pdf':
-            # Read the uploaded PDF file
-            pdf_data = user_file_upload.read()
-
-            # Save the uploaded PDF 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()
-
-        elif user_file_upload.type == 'audio/mpeg' or user_file_upload.type == 'audio/wav' or user_file_upload.type == 'audio/mp3':
-            # Convert audio file to text
-            text_data = convert_audio_to_text(user_file_upload)
-            data = text_data
-            st.write("Audio converted to text: ")
-            st.write(data)
-            
+        # 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(
             [
@@ -125,55 +99,35 @@ if openai_api_key:
         output_parser = StrOutputParser()
         chain_3 = prompt_3 | llm_qa | output_parser
 
-        ## Daily Study Plan
-        def generate_study_plan(data, exam_date, num_days=30):
-            today = datetime.today()
-            study_plan = []
-            day_gap = (exam_date - today).days // num_days
-            for i in range(num_days):
-                day_start = today + timedelta(days=i * day_gap)
-                study_plan.append({
-                    'day': day_start.strftime("%Y-%m-%d"),
-                    'topic': data[i % len(data)]  # Simple round-robin of topics for now
-                })
-            return study_plan
-
-        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")
+    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 == 'Daily Study Plan':
-            # Assume exam date is 30 days from today for simplicity
-            exam_date = datetime.today() + timedelta(days=30)
-            study_plan = generate_study_plan(data, exam_date)
-            for plan in study_plan:
-                st.write(f"Day: {plan['day']} - Study Topic: {plan['topic']}")
+    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.")