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| import os | |
| import json | |
| import pandas as pd | |
| import traceback | |
| import streamlit as st | |
| 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 | |
| from weasyprint import HTML | |
| with open('Response.json', 'r') as file: | |
| RESPONSE_JSON = json.load(file) | |
| st.title("MCQs Creator Application") | |
| 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") | |
| df = None # Declare df at a broader scope | |
| 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) | |
| # Count tokens and the cost of the API call | |
| 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): | |
| # Extract the quiz data from the response | |
| 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) | |
| # Display the review in a text box as well | |
| st.text_area(label="Review", value=response["review"]) | |
| # Call the download function | |
| else: | |
| st.error("Error in the table data") | |
| else: | |
| st.write(response) | |
| def download(df): | |
| col1, col2 = st.columns(2) | |
| html_content = df.to_html(index=False) | |
| pdf_path = "generated_mcqs.pdf" | |
| if button: | |
| # Download CSV | |
| col1.download_button( | |
| label="Download CSV", | |
| data=df.to_csv(index=False).encode("utf-8"), | |
| file_name="generated_mcqs.csv", | |
| key="csv-download", | |
| help="Click to download as CSV", | |
| ) | |
| # Now you can use df outside the form if needed | |
| if df is not None: | |
| download(df) | |