Update app.py

app.py

@@ -15,22 +15,29 @@ pipe_tapex = pipeline(
     "table-question-answering", model=model_tapex, tokenizer=tokenizer_tapex
 )
 
-model_tapas = "google/tapas-large-finetuned-wtq"
-tokenizer_tapas = AutoTokenizer.from_pretrained(model_tapas)
-model_tapas = AutoModelForTableQuestionAnswering.from_pretrained(model_tapas)
-pipe_tapas = pipeline(
-    "table-question-answering", model=model_tapas, tokenizer=tokenizer_tapas
-)
+# model_tapas = "google/tapas-large-finetuned-wtq"
+# tokenizer_tapas = AutoTokenizer.from_pretrained(model_tapas)
+# model_tapas = AutoModelForTableQuestionAnswering.from_pretrained(model_tapas)
+# pipe_tapas = pipeline(
+#     "table-question-answering", model=model_tapas, tokenizer=tokenizer_tapas
+# )
 
+#new
+pipe_tapas = pipeline(task="table-question-answering", model="google/tapas-large-finetuned-wtq")
 
-def process(query, csv_data, correct_answer, rows=20):
-    # table = pd.read_csv(file.name, header=0).astype(str)
-    # table = table[:rows]
-    table = pd.DataFrame.from_dict(csv_data)
+
+def process(query, file, correct_answer, rows=20):
+    table = pd.read_csv(file.name, header=0).astype(str)
+    table = table[:rows]
     result_tapex = pipe_tapex(table=table, query=query)
-    result_tapas = pipe_tapas(table=table, query=query)
     return result_tapex["answer"], result_tapas["answer"], correct_answer
 
+def process2(query, csv_data):
+    table = pd.DataFrame.from_dict(csv_data)
+    # result_tapex = pipe_tapex(table=table, query=query)
+    result_tapas = pipe_tapas(table=table, query=query)['cells'][0]
+    return "", result_tapas, correct_answer
+
 
 # Inputs
 query_text = gr.Text(label="Enter a question")