Update app.py

app.py

@@ -0,0 +1,54 @@
+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()