Update app.py

app.py

@@ -1,10 +1,9 @@
 import gradio as gr
 from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
 from datasets import load_dataset
-import random
 
 # Load the Spider dataset
-spider_dataset = load_dataset("spider", split='train')
+spider_dataset = load_dataset("spider", split='train[:5]')
 
 # Load tokenizer and model
 tokenizer = AutoTokenizer.from_pretrained("mrm8488/t5-base-finetuned-wikiSQL")
@@ -17,27 +16,15 @@ def generate_sql(query):
     sql_query = tokenizer.decode(outputs[0], skip_special_tokens=True)
     return sql_query
 
-def get_random_example():
-    example = random.choice(spider_dataset)
-    return example['question'], generate_sql(example['question'])
-
 # Create a Gradio interface
 interface = gr.Interface(
     fn=generate_sql,
     inputs=gr.Textbox(lines=2, placeholder="Enter your natural language query here..."),
     outputs="text",
     title="NL to SQL with T5",
-    description="This model converts natural language queries into SQL. Enter your query or get a random example from the Spider dataset!"
-)
-
-# Add a button to get a random example from the dataset
-interface.add_component(
-    gr.Button("Get Random Example"),
-    fn=get_random_example,
-    inputs=[],
-    outputs=[gr.Textbox(label="Random Question"), gr.Textbox(label="Generated SQL")]
+    description="This model converts natural language queries into SQL. Enter your query!"
 )
 
 # Launch the app
 if __name__ == "__main__":
-    interface.launch()
+    interface.launch()