app.py

import streamlit as st
import pandas as pd
from transformers import pipeline

# Initialize the table-question-answering pipeline
tqa = pipeline(task="table-question-answering", model="google/tapas-large-finetuned-wtq")

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

# File uploader for table data
uploaded_file = st.file_uploader("Upload a CSV file", type="csv")

# Text input for question
question = st.text_input("Enter your question:")

# Process table and question
if uploaded_file is not None and question:
    try:
        # Read table from CSV
        table = pd.read_csv(uploaded_file)
        

        # Display the table
        st.write("Uploaded Table:")
        st.dataframe(table)

        # Convert DataFrame to the format expected by TAPAS
        table_data = table.as_type(str)
      

        # Get answer
        answer = tqa(table=table_data, query=question)['cells'][0]

        # Display the answer
        st.write("Answer:", answer)
    except Exception as e:
        st.error(f"An error occurred: {e}")

# Instructions
st.markdown("""
*First, upload a CSV file.
""")