app.py

import gradio as gr
from transformers import pipeline

# Load your fine-tuned model from Hugging Face Hub
model_id = "peterjandre/codet5-vbnet-csharp"

# Use text2text-generation pipeline (suitable for CodeT5)
generator = pipeline("text2text-generation", model=model_id)

def generate_code(prompt):
    if not prompt:
        return "Please enter a prompt."
    outputs = generator(prompt, max_length=256, num_return_sequences=1)
    return outputs[0]['generated_text']

# Build Gradio interface
iface = gr.Interface(
    fn=generate_code,
    inputs=gr.Textbox(lines=5, placeholder="Enter code prompt here..."),
    outputs="textbox",
    title="CodeT5 VBNet/C# Code Generator",
    description="Generate VB.NET or C# code from your prompt using a fine-tuned CodeT5 model."
)

if __name__ == "__main__":
    iface.launch()