Update app.py

app.py

@@ -3,9 +3,9 @@ import pandas as pd
 from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
 import sqlite3
 
-# Load model
+# Load model with slow tokenizer explicitly
 model_name = "mrm8488/t5-base-finetuned-wikiSQL"
-tokenizer = AutoTokenizer.from_pretrained(model_name, use_fast=False)  # <-- use slow tokenizer
+tokenizer = AutoTokenizer.from_pretrained(model_name, use_fast=False, local_files_only=False)  # Force slow tokenizer
 model = AutoModelForSeq2SeqLM.from_pretrained(model_name)
 
 def nl_to_sql(question, file):
@@ -18,15 +18,14 @@ def nl_to_sql(question, file):
     conn = sqlite3.connect(":memory:")
     df.to_sql("data_table", conn, index=False, if_exists="replace")
 
-    # Schema description
     schema = ", ".join(df.columns)
     text = f"translate English to SQL: {question} | table columns: {schema}"
 
+    # Tokenize with slow tokenizer
     inputs = tokenizer(text, return_tensors="pt")
     outputs = model.generate(**inputs, max_length=256)
     sql_query = tokenizer.decode(outputs[0], skip_special_tokens=True)
 
-    # Execute SQL query
     try:
         result = pd.read_sql_query(sql_query, conn)
     except Exception as e:
@@ -45,8 +44,8 @@ iface = gr.Interface(
         gr.Textbox(label="Generated SQL Query"),
         gr.Dataframe(label="Result Preview")
     ],
-    title="🧠 Natural Language to SQL Generator",
-    description="Upload a CSV and ask questions in plain English. Generates SQL and shows results instantly."
+    title="🧠 NL to SQL Generator",
+    description="Upload a CSV and ask questions in plain English. Generates SQL and shows results."
 )
 
 if __name__ == "__main__":