Sid26Roy commited on
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dec6df4
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1 Parent(s): 82a8738

Update app.py

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Files changed (1) hide show
  1. app.py +29 -15
app.py CHANGED
@@ -1,25 +1,39 @@
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- import gradio as gr
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  import torch
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  from transformers import T5Tokenizer, T5ForConditionalGeneration
 
 
 
 
 
 
 
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- # Load model and tokenizer from local files
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- model_path = "./"
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- tokenizer = T5Tokenizer.from_pretrained(model_path)
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- model = T5ForConditionalGeneration.from_pretrained(model_path)
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  device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
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- model = model.to(device)
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  model.eval()
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- def generate_sql(user_input):
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- inputs = tokenizer(user_input, return_tensors="pt", truncation=True, padding=True).to(device)
 
 
 
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  with torch.no_grad():
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  outputs = model.generate(**inputs, max_length=512)
 
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  return tokenizer.decode(outputs[0], skip_special_tokens=True)
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- gr.Interface(
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- fn=generate_sql,
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- inputs=gr.Textbox(lines=15, placeholder="Paste your full SQL prompt here..."),
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- outputs=gr.Textbox(label="Generated SQL Query"),
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- title="HISAB AI – Text2SQL Generator",
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- description="Paste your schema + user query + instructions. Model returns a PostgreSQL query."
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- ).launch()
 
 
 
 
 
 
 
 
 
 
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  import torch
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  from transformers import T5Tokenizer, T5ForConditionalGeneration
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+ import gradio as gr
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+
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+ # Load model from local folder
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+ model_dir = "./"
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+
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+ tokenizer = T5Tokenizer.from_pretrained(model_dir)
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+ model = T5ForConditionalGeneration.from_pretrained(model_dir)
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  device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
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+ model.to(device)
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  model.eval()
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+ # Inference function
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+ def generate_sql(schema, instructions, user_query):
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+ combined_input = f"{instructions.strip()}\n\n{schema.strip()}\n\nUser Query: \"{user_query.strip()}\"\n\nSQL Query:"
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+ inputs = tokenizer(combined_input, padding=True, truncation=True, return_tensors="pt").to(device)
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+
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  with torch.no_grad():
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  outputs = model.generate(**inputs, max_length=512)
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+
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  return tokenizer.decode(outputs[0], skip_special_tokens=True)
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+ # UI layout
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+ with gr.Blocks() as demo:
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+ gr.Markdown("# 🧠 Text-to-SQL Generator")
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+ gr.Markdown("Enter the **schema**, **prompt/instructions**, and a **user query** to get the SQL output.")
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+
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+ schema = gr.Textbox(label="Database Schema", lines=10, placeholder="CREATE TABLE students (...) ...")
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+ instructions = gr.Textbox(label="SQL Instructions / Prompt", lines=15, placeholder="Explain how to generate SQL queries...")
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+ user_query = gr.Textbox(label="User Query", placeholder="e.g., Show me students who never attended class")
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+
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+ output = gr.Textbox(label="Generated SQL Query")
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+
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+ submit = gr.Button("Generate SQL")
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+ submit.click(fn=generate_sql, inputs=[schema, instructions, user_query], outputs=output)
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+
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+ demo.launch()