Update app.py

app.py

@@ -1,13 +1,39 @@
-from app_tapex import execute_query
+from transformers import TapexTokenizer, BartForConditionalGeneration
+import pandas as pd
+import datetime
+import torch
 import gradio as gr
 
+def execute_query(query, csv_file):
+    a = datetime.datetime.now()
+
+    table = pd.read_csv(csv_file.name, delimiter=",")
+    table = table.astype(str)
+
+    model_name = "microsoft/tapex-large-finetuned-wtq"
+    model = BartForConditionalGeneration.from_pretrained(model_name)
+    tokenizer = TapexTokenizer.from_pretrained(model_name)
+
+    queries = [query]
+
+    encoding = tokenizer(table=table, query=queries, padding=True, return_tensors="pt", truncation=True)
+    outputs = model.generate(**encoding)
+    ans = tokenizer.batch_decode(outputs, skip_special_tokens=True)
+
+    query_result = {
+        "query": query,
+        "answer": ans[0]
+    }
+
+    b = datetime.datetime.now()
+    print(b - a)
+
+    return query_result, table
 
 def main():
-    description = "Querying a csv using TAPEX model. You can ask a question about tabular data. TAPAS model " \
-                  "will produce the result. Finetuned TAPEX model runs on max 5000 rows and 20 columns data. " \
-                  "A sample data of shopify store sales is provided"
+    description = "Querying a CSV using the TAPEX model. You can ask a question about tabular data, and the TAPEX model will produce the result. The finetuned TAPEX model runs on data with a maximum of 5000 rows and 20 columns. A sample dataset of Shopify store sales is provided."
 
-    article = "<p style='text-align: center'><a href='https://unscrambl.com/' target='_blank'>Unscrambl</a> | <a href='https://huggingface.co/google/tapas-base-finetuned-wtq' target='_blank'>TAPAS Model</a></p><center><img src='https://visitor-badge.glitch.me/badge?page_id=abaranovskij_tablequery' alt='visitor badge'></center>"
+    article = "<p style='text-align: center'><a href='https://unscrambl.com/' target='_blank'>Unscrambl</a> | <a href='https://huggingface.co/microsoft/tapex-large-finetuned-wtq' target='_blank'>TAPEX Model</a></p><center><img src='https://visitor-badge.glitch.me/badge?page_id=abaranovskij_tablequery' alt='visitor badge'></center>"
 
     iface = gr.Interface(fn=execute_query,
                          inputs=[gr.Textbox(label="Search query"),
@@ -22,6 +48,5 @@ def main():
     # iface.launch(server_name="0.0.0.0", server_port=7000)
     iface.launch(enable_queue=True)
 
-
 if __name__ == "__main__":
-    main()
+    main()