Create app.py

app.py

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+import torch
+import pandas as pd # pandas for datafrang
+
+# we import pipeline using transfromer library
+from transformers import pipeline
+
+
+# we creates a pipeline specifically designed for answering questions based on a table using a pre-trained model. 
+pipe = pipeline(task="table-question-answering",model="google/tapas-base-finetuned-wtq")
+
+#uploading csv 
+table=pd.read_csv(input("input the CSV file link: "))
+
+# converts the data types of all elements in a pandas DataFrame (table) to strings
+table = table.astype(str)
+table
+
+#The code you provided combines user input and table-based question answering
+query=input("type the Question: ")
+print(pipe(table=table,query=query)["answer"])