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from langchain.document_loaders import PyPDFLoader
from utils import *
import os
import google.generativeai as genai
from langchain_google_genai import ChatGoogleGenerativeAI
from dotenv import load_dotenv
import streamlit as st
st.set_page_config(layout="wide", page_title="QA Pair Generation from Documents",page_icon='deep-learning.png')
temperature = 0.3
pages = []
numPairs = 2
option = ''
optionCategory = ("Long QA Pairs", "MCQs", "Short QA Pairs")
load_dotenv()
genai.configure(api_key=os.environ.get("GOOGLE_API_KEY"))
model = ChatGoogleGenerativeAI(model="gemini-pro", temperature=temperature)
def LongQAPairs():
response = []
with st.spinner('Generating Long Question Answer Pairs...'):
response =getLongQAPairs(pages[0:len(pages) - 1], numPairs, model)
for qaPair in response:
with st.chat_message("user"):
st.write("Question : {}".format(qaPair['question']))
st.write("Answer : {}".format(qaPair['answer']))
def ShortQAPairs():
response = []
with st.spinner('Generating Short Question Answer Pairs...'):
response = getShortQAPairs(pages[0:len(pages) - 1], numPairs, model)
for qaPair in response:
with st.chat_message("user"):
st.write("Question : {}".format(qaPair['question']))
st.write("Answer : {}".format(qaPair['answer']))
def McqQAPairs():
response = []
with st.spinner('Generating MCQ Question Answer Pairs...'):
response = getMcqQAPairs(pages[0:len(pages) - 1], numPairs, model)
for qaPair in response:
with st.chat_message("user"):
st.radio(label=qaPair['question'],options=qaPair["options"],disabled=True,index=qaPair['correct_option_index'])
with st.sidebar:
st.image('Pic.png')
st.title("Final Year Project")
st.divider()
with st.container(border=True):
st.text('Model: Gemini Pro', help='Developed by Google \n')
temperature = st.slider('Temperature:', 0.0, 1.0, 0.3, 0.1)
code = '''Team Members CSE(20-37):
\nAmbuj Raj BT20CSE054 \nSrishti Pandey BT20CSE068 \nPrateek Niket BT20CSE211 \nSmriti Singh BT20CSE156'''
st.code(code, language='JAVA')
code = '''Mentored By: \nDr. Amol Bhopale'''
st.code(code, language='JAVA')
st.title('Question Answer Pair Generation From Documents')
with st.container(border=True):
col1, col2 = st.columns(2)
with col1:
st.write("Please Upload Your File")
uploaded_file = st.file_uploader("Choose a file", type='.pdf', accept_multiple_files=False)
if uploaded_file is not None:
with open("temp.pdf", "wb") as f:
f.write(uploaded_file.getbuffer())
# Get the path of the uploaded file
file_path = "temp.pdf"
pdf_loader = PyPDFLoader(file_path)
pages = pdf_loader.load_and_split()
print(len(pages))
with col2:
st.write('Please Choose your Configuration')
option = st.selectbox(
"In Which Category would you like to Generate Question Answer Pairs?",
optionCategory,
index=None,
placeholder="Select Category of Question Answer Pairs",
)
numPairs = st.number_input('Number of QA Pairs', min_value=1, max_value=20, step=2,value=2)
if st.button("Generate", type="primary"):
if option == "Long QA Pairs" and len(pages) and option in optionCategory:
LongQAPairs()
elif option == "MCQs" and len(pages) and option in optionCategory:
McqQAPairs()
elif option == "Short QA Pairs" and len(pages) and option in optionCategory:
ShortQAPairs()
elif len(pages) or option not in optionCategory or uploaded_file is None:
st.error('Required Fields are Missing!', icon="🚨")
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