app.py

import pandas as pd
import streamlit as st
from data_preprocessing import preprocess_csv
from question_answering import answer_query

# Streamlit app
st.title("Question Answering App")

# Textbox for user query
user_query = st.text_input("Enter your question:")

# File uploader for context (Hugging Face specific)
uploaded_file = st.file_uploader("Upload a CSV file from Hugging Face Hub:", type="CSV")

if uploaded_file is not None:
  # Read the CSV data using pandas
  df = pd.read_csv(uploaded_file)

  # Preprocess the CSV data
  context = preprocess_csv(df)  # Assuming preprocess_csv can handle DataFrame input

  # Display the uploaded CSV data as a table
  st.dataframe(df)

else:
  # Use default context (optional)
  context = "This is a sample context for demonstration purposes. You can upload your own text file or CSV file for context."

# Answer the query if a question is provided
if user_query:
  answer = answer_query(user_query, context)
  st.write(f"Answer: {answer}")
else:
  st.write("Please enter a question.")