app.py

import gradio
import transformers
import torch

tokenizer = AutoTokenizer.from_pretrained('t5-small-finetuned-wikisql-with-cols')
model = T5ForConditionalGeneration.from_pretrained('t5-small-finetuned-wikisql-with-cols')

def translate_to_sql(text):
    inputs = tokenizer(text, padding='longest', max_length=64, return_tensors='pt')
    input_ids = inputs.input_ids
    attention_mask = inputs.attention_mask
    output = model.generate(input_ids, attention_mask=attention_mask, max_length=64)
    return tokenizer.decode(output[0], skip_special_tokens=True)



#Input example: 'translate to SQL: When was Olympic games held in Rome? table ID: ID, city, year, cost, attendees'
gradio_interface = gradio.Interface(
  fn = translate_to_sql,
  inputs = "text",
  outputs = "text"
)
gradio_interface.launch()