app.py

import gradio as gr
import sys
import os

# Add the parent directory to sys.path to import from backend
sys.path.append(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
from multi_layer_operation_predictor.operation_predictor import get_operation_definition

def predict_operation(input_text, language):
    """
    Predicts the operation based on user input and selected language
    """
    result = get_operation_definition(input_text, language.lower())
    if not result:
        return "No matching operation found"
    return result

# Create the Gradio interface
iface = gr.Interface(
    fn=predict_operation,
    inputs=[
        gr.Textbox(label="Enter your operation description"),
        gr.Dropdown(
            choices=["python", "javascript", "typescript", "php", "java"],
            label="Select Programming Language"
        )
    ],
    outputs=gr.Textbox(label="Operation Definition"),
    title="Multi-Layer Operation Predictor",
    description="Enter a description of the operation you're looking for and select the programming language. The model will find the closest matching operation.",
    examples=[
        ["def addition(a,b)", "python"],
        ["addition(a,b)", "javascript"],
    ]
)

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