Update app.py

app.py

@@ -1,56 +1,28 @@
 import gradio as gr
-import pandas as pd
-from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
-import sqlite3
-
 from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
 
+# Public model fine-tuned on WikiSQL
 model_name = "mrm8488/t5-base-finetuned-wikiSQL"
 
-# Force slow tokenizer
+# Force slow tokenizer to avoid tiktoken issues
 tokenizer = AutoTokenizer.from_pretrained(model_name, use_fast=False)
 model = AutoModelForSeq2SeqLM.from_pretrained(model_name)
 
-
-def nl_to_sql(question, file):
-    try:
-        df = pd.read_csv(file.name)
-    except Exception as e:
-        return f"Error reading CSV: {e}", pd.DataFrame()
-    
-    # Create SQLite DB
-    conn = sqlite3.connect(":memory:")
-    df.to_sql("data_table", conn, index=False, if_exists="replace")
-
-    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)
+def nl_to_sql(nl_query):
+    # Add prefix required for this model
+    input_text = "translate English to SQL: " + nl_query
+    inputs = tokenizer.encode(input_text, return_tensors="pt")
+    outputs = model.generate(inputs, max_length=512)
     sql_query = tokenizer.decode(outputs[0], skip_special_tokens=True)
-
-    try:
-        result = pd.read_sql_query(sql_query, conn)
-    except Exception as e:
-        result = pd.DataFrame({"Error": [str(e)]})
-
-    conn.close()
-    return sql_query, result.head()
-
-iface = gr.Interface(
-    fn=nl_to_sql,
-    inputs=[
-        gr.Textbox(label="Ask your question (Natural Language)", placeholder="e.g., Show customers older than 30"),
-        gr.File(label="Upload your CSV file")
-    ],
-    outputs=[
-        gr.Textbox(label="Generated SQL Query"),
-        gr.Dataframe(label="Result Preview")
-    ],
-    title="🧠 NL to SQL Generator",
-    description="Upload a CSV and ask questions in plain English. Generates SQL and shows results."
-)
-
-if __name__ == "__main__":
-    iface.launch()
+    return sql_query
+
+# Gradio UI
+with gr.Blocks() as demo:
+    gr.Markdown("## 🧠 Natural Language to SQL Generator")
+    with gr.Row():
+        nl_input = gr.Textbox(label="Enter your query in English")
+        sql_output = gr.Textbox(label="Generated SQL")
+    btn = gr.Button("Generate SQL")
+    btn.click(nl_to_sql, inputs=nl_input, outputs=sql_output)
+
+demo.launch()