import gradio as gr
from transformers import pipeline

# Load models
base_model = pipeline('translation_en_to_fr', model='Helsinki-NLP/opus-mt-en-fr')
fine_tuned_model_1 = pipeline('translation_en_to_fr', model='path/to/fine-tuned-model-1')
fine_tuned_model_2 = pipeline('translation_en_to_fr', model='path/to/fine-tuned-model-2')
fine_tuned_model_3 = pipeline('translation_en_to_fr', model='path/to/fine-tuned-model-3')

# Define translation functions
def translate_base(text):
    return base_model(text)[0]['translation_text']

def translate_fine_tuned(text, model):
    if model == 'model1':
        return fine_tuned_model_1(text)[0]['translation_text']
    elif model == 'model2':
        return fine_tuned_model_2(text)[0]['translation_text']
    elif model == 'model3':
        return fine_tuned_model_3(text)[0]['translation_text']
    else:
        return "Invalid model selected"

# Create Gradio interface
with gr.Blocks() as demo:
    gr.Markdown("### Translation Models")

    with gr.Row():
        with gr.Column():
            gr.Markdown("#### Base Model")
            base_input = gr.Textbox(placeholder="Enter text to translate", label="Input")
            base_output = gr.Textbox(label="Translation")
            base_translate_btn = gr.Button("Translate")
            base_translate_btn.click(translate_base, inputs=base_input, outputs=base_output)

        with gr.Column():
            gr.Markdown("#### Fine-tuned Models")
            fine_tuned_input = gr.Textbox(placeholder="Enter text to translate", label="Input")
            model_select = gr.Dropdown(choices=["model1", "model2", "model3"], label="Select Model")
            fine_tuned_output = gr.Textbox(label="Translation")
            fine_tuned_translate_btn = gr.Button("Translate")
            fine_tuned_translate_btn.click(translate_fine_tuned, inputs=[fine_tuned_input, model_select], outputs=fine_tuned_output)

demo.launch()