Create app.py

Initial write up

app.py

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+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:
+    # Read table from CSV
+    table = pd.read_csv(uploaded_file)
+
+    # Display the table
+    st.write("Uploaded Table:")
+    st.write(table)
+
+    # Get answer
+    answer = tqa(table=table, query=question)['cells'][0]
+
+    # Display the answer
+    st.write("Answer:", answer)
+
+# Instructions
+st.markdown("""
+*First, upload a CSV file containing your table data. The CSV should have headers for each column.*  
+*Then, enter a question related to the table and press Enter to see the answer.*  
+""")