streamlitapp.py

import os
import json
import pandas as pd
import traceback
import streamlit as st

from dotenv import load_dotenv
from src.mcqgenerator.utilis import read_file,get_table_data
from src.mcqgenerator.logger import logging
from src.mcqgenerator.mcqgenerator import generate_evaluate_chain
from langchain_community.callbacks import get_openai_callback
from langchain_openai import ChatOpenAI
from langchain.prompts import PromptTemplate
from langchain.chains import LLMChain
from langchain.chains import SequentialChain

with open('Response.json', 'r') as file:
    RESPONSE_JSON = json.load(file)

st.title("MCQs Creator Application with Langchain")

with st.form("user_inputs"):
    uploader_file=st.file_uploader("Upload a PDF or Txt file")

    mcq_count=st.text_input("No .of MCQS")

    subject=st.text_input("Insert subject", max_chars=20)

    tone=st.text_input("Complexity Level of Questions",max_chars=20, placeholder="Simple")

    button=st.form_submit_button("Create MCQs")

    if button and uploader_file is not None and mcq_count and subject and tone:
        with st.spinner("Loading...."):
            try:
                text=read_file(uploader_file)

                with get_openai_callback() as cb:
                        response=generate_evaluate_chain(
                            {
                                "text": text,
                                "number": mcq_count,
                                "subject":subject,
                                "tone": tone,
                                "response_json": json.dumps(RESPONSE_JSON)
                            }
                 )
                        
            except Exception as e:
                  traceback.print_exception(type(e), e,e.__traceback__)
                  st.error("ERROR")

            else:
                 print(f"Total Tokens:{cb.total_tokens}")
                 print(f"Prompt Tokens:{cb.prompt_tokens}")
                 print(f"Completion Tokens:{cb.completion_tokens}")
                 print(f"Total Cost:{cb.total_cost}")
                 if isinstance(response,dict):
                       
                       quiz=response.get("quiz",None)
                       if quiz is not None:
                            table_data=get_table_data(quiz)
                            if table_data is not None:
                                 df=pd.DataFrame(table_data)
                                 df.index=df.index+1
                                 st.table(df)

                                 st.text_area(label="Review",value=response["review"])
                            else:
                                 st.error("Error in the table date")

                       else:
                            st.write(response)