Update app.py

app.py

@@ -35,12 +35,12 @@ pipe_tapas = pipeline(task="table-question-answering", model="google/tapas-large
 
 
 def process2(query, csv_data):
-    csv_data={"Actors": ["Brad Pitt", "Leonardo Di Caprio", "George Clooney"], "Number of movies": ["87", "53", "69"]}
+    # csv_data={"Actors": ["Brad Pitt", "Leonardo Di Caprio", "George Clooney"], "Number of movies": ["87", "53", "69"]}
     table = pd.DataFrame.from_dict(csv_data)
     #microsoft
     encoding = tokenizer(table=table, query=query, return_tensors="pt")
     outputs = model.generate(**encoding)
-    result_tapex=tokenizer.batch_decode(outputs, skip_special_tokens=True)
+    result_tapex=tokenizer.batch_decode(outputs, skip_special_tokens=True)[0]
     #google
     result_tapas = pipe_tapas(table=table, query=query)['cells'][0]
     return result_tapex, result_tapas
@@ -74,7 +74,7 @@ iface = gr.Interface(
     inputs=[query_text, input_data],
     outputs=[answer_text_tapex, answer_text_tapas],
     examples=[
-        
+        ["how many movies does Leonardo Di Caprio have?",{"Actors": ["Brad Pitt", "Leonardo Di Caprio", "George Clooney"], "Number of movies": ["87", "53", "69"]}]
     ],
     allow_flagging="never",
 )