sample site

app.py

@@ -1,8 +1,34 @@
+import warnings
+warnings.filterwarnings("ignore", category=UserWarning, module="torchvision")
+warnings.filterwarnings("ignore", category=FutureWarning, module="transformers")
+warnings.filterwarnings("ignore")
+
+
+from transformers import pipeline
+import pandas as pd
 import streamlit as st
 
-x = st.slider('Select a value')
-st.write(x, 'squared is', x * x)
+# Initialize the pipeline
+pipe = pipeline("table-question-answering", model="google/tapas-large-finetuned-wtq")
 
+# Define the table data
+data = {
+    "year": [1896, 1900, 1904, 2004, 2008, 2012],
+    "city": ["athens", "paris", "st. louis", "athens", "beijing", "london"]
+}
+table = pd.DataFrame(data)
+table = table.astype(str)  # Ensure all values are strings
 
+# Streamlit app layout
+st.title("Table Question Answering")
+st.write("### Input Table")
+st.dataframe(table)
 
+# User query
+query = st.text_input("Ask a question about the table:", "In which year did beijing host the Olympic Games?")
 
+# Process query and display result
+if st.button("Get Answer"):
+    result = pipe(table=table, query=query)
+    st.write("### Answer")
+    st.write(result["answer"])

requirements.txt

@@ -0,0 +1,3 @@
+streamlit==1.41.1
+torch
+transformers