Update app.py

app.py

@@ -1,32 +1,42 @@
 import gradio as gr
 from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
 from datasets import load_dataset
+from difflib import get_close_matches
 
-# Load the WikiSQL dataset (optional, not used directly in SQL generation)
-wikisql_dataset = load_dataset("wikisql", split='train')
+# Load the WikiSQL dataset
+wikisql_dataset = load_dataset("wikisql", split='train[:100]')  # Load a subset of the dataset
 
 # Load tokenizer and model
 tokenizer = AutoTokenizer.from_pretrained("mrm8488/t5-base-finetuned-wikiSQL")
 model = AutoModelForSeq2SeqLM.from_pretrained("mrm8488/t5-base-finetuned-wikiSQL")
 
+def find_closest_match(query, dataset):
+    questions = [item['question'] for item in dataset]
+    matches = get_close_matches(query, questions, n=1)
+    return matches[0] if matches else None
+
 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)
-    return query, sql_query
+    # Find the closest match in the dataset
+    matched_query = find_closest_match(query, wikisql_dataset)
+    if not matched_query:
+        return "No close match found in the dataset.", ""
+
+    # Find the corresponding SQL query in the dataset
+    for item in wikisql_dataset:
+        if item['question'] == matched_query:
+            return matched_query, item['sql']['human_readable']
+
+    return "Match found, but corresponding SQL query not found in dataset.", ""
 
 # 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="Your Query"), gr.Textbox(label="Generated SQL Query")],
+    outputs=[gr.Textbox(label="Matched Query from Dataset"), gr.Textbox(label="Corresponding SQL Query from Dataset")],
     title="NL to SQL with T5 using WikiSQL Dataset",
-    description="This model generates an SQL query for your natural language input."
+    description="This model finds the closest match in the WikiSQL dataset for your query and returns the corresponding SQL query from the dataset."
 )
 
 # Launch the app
 if __name__ == "__main__":
     interface.launch()
-