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import gradio as gr
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
# Public model fine-tuned on WikiSQL
model_name = "mrm8488/t5-base-finetuned-wikiSQL"
# 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(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)
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()
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