Update app.py

app.py

@@ -1,54 +0,0 @@
-import gradio as gr
-from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
-from datasets import load_dataset
-
-# Load the WikiSQL dataset
-wikisql_dataset = load_dataset("wikisql", split='train[:100]')  # Load a subset of the dataset
-
-# Extract schema information from the dataset
-table_names = set()
-column_names = set()
-for item in wikisql_dataset:
-    table_names.add(item['table']['name'])
-    for column in item['table']['header']:
-        column_names.add(column)
-
-# Load tokenizer and model
-tokenizer = AutoTokenizer.from_pretrained("mrm8488/t5-base-finetuned-wikiSQL")
-model = AutoModelForSeq2SeqLM.from_pretrained("mrm8488/t5-base-finetuned-wikiSQL")
-
-def post_process_sql_query(sql_query):
-    # Modify the SQL query to match the dataset's schema
-    # This is just an example and might need to be adapted based on the dataset and model output
-    for table_name in table_names:
-        if "TABLE" in sql_query:
-            sql_query = sql_query.replace("TABLE", table_name)
-            break  # Assuming only one table is referenced in the query
-    for column_name in column_names:
-        if "COLUMN" in sql_query:
-            sql_query = sql_query.replace("COLUMN", column_name, 1)
-    return sql_query
-
-def generate_sql_from_user_input(query):
-    # Generate SQL for the user's query
-    input_text = "translate English to SQL: " + query
-    inputs = tokenizer(input_text, return_tensors="pt", padding=True)
-    outputs = model.generate(**inputs, max_length=512)
-    sql_query = tokenizer.decode(outputs[0], skip_special_tokens=True)
-
-    # Post-process the SQL query to match the dataset's schema
-    sql_query = post_process_sql_query(sql_query)
-    return sql_query
-
-# Create a Gradio interface
-interface = gr.Interface(
-    fn=generate_sql_from_user_input,
-    inputs=gr.Textbox(label="Enter your natural language query"),
-    outputs=gr.Textbox(label="Generated SQL Query"),
-    title="NL to SQL with T5 using WikiSQL Dataset",
-    description="This model generates an SQL query for your natural language input based on the WikiSQL dataset."
-)
-
-# Launch the app
-if __name__ == "__main__":
-    interface.launch()