import openai import json import langchain import pandas as pd from openai import OpenAI from langchain_openai import OpenAI, ChatOpenAI import os from dotenv import load_dotenv from src.mcqgen.utils import read_file, get_table_data from src.mcqgen.logger import logging from src.mcqgen.mcqgenerator import generate_evaluate_chain import streamlit as st from langchain.llms import openai from langchain.prompts import PromptTemplate from langchain.chains import LLMChain, SequentialChain from langchain.callbacks import get_openai_callback import traceback with open('response.json', 'r') as file: response_json=json.load(file) st.title("MCQ Creator App with Langchain:") with st.form("user_input"): uploaded_file=st.file_uploader("Upload a PDF or txt file") mcq_count=st.number_input("No. of MCQs", min_value=3, max_value=50) subject=st.text_input("Insert a subject", max_chars=20) tone=st.text_input("Difficulty level", max_chars=20, placeholder="Simple") button=st.form_submit_button("Create MCQs") if button and uploaded_file is not None and mcq_count and subject and tone: with st.spinner("loading..."): try: text=read_file(uploaded_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") if quiz is not None: print('About to execute probalematic function') 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.write(response.get("review")) else: st.error("Error in the table data") else: st.write(response)