backup_selectmodel

from transformers import MarianMTModel, MarianTokenizer
import gradio as gr
import torch

# Define available models and BLEU scores
MODEL_OPTIONS = {
    "Version v1 (EN→RU BLEU: 35.93 | RU→EN BLEU: 41.11)": {
        "key": "v1",
        "en_ru": "kafarasi/marian-en-ru-finetuned",
        "ru_en": "kafarasi/marian-ru-en-finetuned"
    },
    "Version v2 (EN→RU BLEU: 36.61 | RU→EN BLEU: 50.00)": {
        "key": "v2",
        "en_ru": "kafarasi/marian-en-ru-finetunedv2",
        "ru_en": "kafarasi/marian-ru-en-finetunedv2"
    },
    "Version v3 (EN→RU BLEU: 37.52 | RU→EN BLEU: 47.06)": {
        "key": "v3",
        "en_ru": "kafarasi/marian-en-ru-finetunedv4",
        "ru_en": "kafarasi/marian-ru-en-finetunedv4"
    }
}

# Select device (CPU for Hugging Face Spaces)
device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
use_float16 = device.type == "cuda"
loaded_models = {}

# Load and cache models
def get_model_and_tokenizer(display_label, direction):
    version_info = MODEL_OPTIONS[display_label]
    version_key = version_info["key"]
    cache_key = f"{version_key}_{direction}"

    if cache_key in loaded_models:
        return loaded_models[cache_key]

    model_name = version_info["en_ru"] if direction == "English → Runyankore" else version_info["ru_en"]
    tokenizer = MarianTokenizer.from_pretrained(model_name)
    model = MarianMTModel.from_pretrained(
        model_name,
        torch_dtype=torch.float16 if use_float16 else torch.float32
    ).to(device)

    loaded_models[cache_key] = (tokenizer, model)
    return tokenizer, model

# Translation function (no splitting)
def translate_text(text, direction, version_label):
    tokenizer, model = get_model_and_tokenizer(version_label, direction)
    text = text.strip()
    if not text:
        return ""
    inputs = tokenizer([text], return_tensors="pt", padding=True, truncation=True).to(device)
    with torch.no_grad():
        outputs = model.generate(**inputs, max_length=128, num_beams=1)
    return tokenizer.decode(outputs[0], skip_special_tokens=True)

# Clear inputs
def clear_fields():
    return "", ""

# UI Styling
custom_css = """
body {
    background: linear-gradient(to right, #e3f2fd, #fce4ec);
    font-family: 'Segoe UI', sans-serif;
}
h1 {
    color: #2c3e50;
    font-size: 32px;
    text-align: center;
    margin-bottom: 10px;
}
p {
    text-align: center;
    font-size: 16px;
    color: #4e4e4e;
}
.gradio-container {
    max-width: 900px;
    margin: auto;
    padding: 30px;
    background: #ffffff;
    box-shadow: 0 4px 15px rgba(0, 0, 0, 0.1);
    border-radius: 16px;
}
textarea, input {
    font-size: 16px !important;
    border: 2px solid #2980b9;
    border-radius: 8px !important;
}
.gr-button {
    background-color: #3498db !important;
    color: white !important;
    border-radius: 8px !important;
    font-size: 16px !important;
    padding: 10px 20px !important;
    transition: background-color 0.3s ease;
}
.gr-button:hover {
    background-color: #2c81ba !important;
}
"""

# Gradio Interface
with gr.Blocks(css=custom_css) as iface:
    gr.Markdown("<h1>Runyankore ↔ English Translator</h1>")
    gr.Markdown(
        "<p>Select a model version and translation direction. Input text will be translated efficiently even on CPU.</p>"
    )

    with gr.Row():
        with gr.Column(scale=1):
            model_selector = gr.Dropdown(list(MODEL_OPTIONS.keys()), label="Model Version", value=list(MODEL_OPTIONS.keys())[1])
            text_input = gr.Textbox(lines=5, label="Input Text", placeholder="Enter text...", interactive=True, show_copy_button=True)
            direction = gr.Radio(["English → Runyankore", "Runyankore → English"], label="Translation Direction")
            with gr.Row():
                translate_btn = gr.Button("🔄 Translate")
                clear_btn = gr.Button("🗑️ Clear")

        with gr.Column(scale=1):
            output_text = gr.Textbox(lines=5, label="Translated Output", interactive=False, show_copy_button=True)

    translate_btn.click(fn=translate_text, inputs=[text_input, direction, model_selector], outputs=output_text)
    clear_btn.click(fn=clear_fields, outputs=[text_input, output_text])

    gr.Markdown(
        "<p style='text-align: center;'>💬 Feedback? "
        "<a href='https://forms.gle/WD1sFUD6JHSxrr3u6' target='_blank' style='color: #2980b9;'>Click here to help improve</a></p>"
    )

# Launch
iface.launch()