import gradio as gr
from transformers import M2M100ForConditionalGeneration, M2M100Tokenizer

model_name = "dsfsi/nso-en-m2m100-gov"
tokenizer = M2M100Tokenizer.from_pretrained(model_name)
model = M2M100ForConditionalGeneration.from_pretrained(model_name)

tokenizer.src_lang = "ns"
model.config.forced_bos_token_id = tokenizer.get_lang_id("en")

def translate(inp):
    inputs = tokenizer(inp, return_tensors="pt")
    translated_tokens = model.generate(**inputs, max_length=512, forced_bos_token_id=tokenizer.get_lang_id("en"))
    translated_text = tokenizer.decode(translated_tokens[0], skip_special_tokens=True)
    return translated_text

with gr.Blocks() as demo:
    with gr.Row():
        with gr.Column(scale=1):  
            pass
        with gr.Column(scale=4, min_width=1000): 
            gr.Image("logo_transparent_small.png", elem_id="logo", show_label=False, width=500)
            gr.Markdown("""
            <h1 style='text-align: center;'>Northern Sotho to English Translation</h1>
            <p style='text-align: center;'>This space provides a translation service from Northern Sotho to English using the M2M100 model, fine-tuned for low-resource languages. It supports researchers, linguists, and users working with Northern Sotho texts.</p>
            """)
        with gr.Column(scale=1):  
            pass
    
    with gr.Column(variant="panel"):
        inp_text = gr.Textbox(lines=5, placeholder="Enter Northern Sotho text (maximum 5 lines)", label="Input", elem_id="centered-input")
        output_text = gr.Textbox(label="Output", elem_id="centered-output")
        translate_button = gr.Button("Translate", elem_id="centered-button")
        translate_button.click(translate, inputs=inp_text, outputs=output_text)
    
    gr.Markdown("""
    <div style='text-align: center;'>
        <a href='https://github.com/dsfsi/nso-en-m2m100-gov' target='_blank'>GitHub</a> |
        <a href='https://docs.google.com/forms/d/e/1FAIpQLSf7S36dyAUPx2egmXbFpnTBuzoRulhL5Elu-N1eoMhaO7v10w/viewform' target='_blank'>Feedback Form</a> |
        <a href='https://arxiv.org/abs/2303.03750' target='_blank'>Arxiv</a>
    </div>
    <br/>
    """)
    
    with gr.Accordion("More Information", open=False):
        gr.Markdown("""
        <h4 style="text-align: center;">Model Description</h4>
        <p style='text-align: center;'>This is a variant of the M2M100 model, fine-tuned on a multilingual dataset to support translation from Northern Sotho (Sepedi) to English. The model was trained with a focus on improving translation accuracy for low-resource languages.</p>
        """)
        gr.Markdown("""
        <h4 style="text-align: center;">Authors</h4>
        <div style='text-align: center;'>
            Vukosi Marivate, Matimba Shingange, Richard Lastrucci, 
            Isheanesu Joseph Dzingirai, Jenalea Rajab
        </div>
        """)
        gr.Markdown("""
        <h4 style="text-align: center;">Citation</h4>
        <pre style="text-align: center; white-space: pre-wrap;">
        @inproceedings{lastrucci-etal-2023-preparing,
            title = "Preparing the Vuk{'}uzenzele and {ZA}-gov-multilingual {S}outh {A}frican multilingual corpora",
            author = "Richard Lastrucci and Isheanesu Dzingirai and Jenalea Rajab 
                      and Andani Madodonga and Matimba Shingange and Daniel Njini and Vukosi Marivate",
            booktitle = "Proceedings of the Fourth workshop on Resources for African Indigenous Languages (RAIL 2023)",
            month = may,
            year = "2023",
            address = "Dubrovnik, Croatia",
            publisher = "Association for Computational Linguistics",
            url = "https://aclanthology.org/2023.rail-1.3",
            pages = "18--25"
        }
        </pre>
        """)
        gr.Markdown("""
        <h4 style="text-align: center;">DOI</h4>
        <div style='text-align: center;'>
            <a href="https://doi.org/10.48550/arXiv.2303.03750" target="_blank">10.48550/arXiv.2303.03750</a>
        </div>
        """)

demo.launch()