import streamlit as st
from transformers import pipeline

unmasker = pipeline('fill-mask', model='dsfsi/zabantu-xlm-roberta')

sample_sentences = {
    'Zulu': "Le ndoda ithi izo____ ukudla.",  
    'Tshivenda': "Mufana uyo____ vhukuma.",  
    'Sepedi': "Mosadi o ____ pheka.",  
    'Tswana': "Monna o ____ tsamaya.",  
    'Tsonga': "N'wana wa xisati u ____ ku tsaka."  
}

def fill_mask_for_languages(sentences):
    results = {}
    for language, sentence in sentences.items():
        masked_sentence = sentence.replace('____', unmasker.tokenizer.mask_token)
        unmasked = unmasker(masked_sentence)
        results[language] = unmasked 
    return results

def replace_mask(sentence, predicted_word):
    return sentence.replace("____", predicted_word)

st.title("Fill Mask for Multiple Languages | Zabantu-XLM-Roberta")
st.write("This app predicts the missing word for sentences in Zulu, Tshivenda, Sepedi, Tswana, and Tsonga using a Zabantu BERT model.")

user_sentence = st.text_area("Enter your own sentence with a masked word (use '____'):", "\n".join(
    f"'{lang}': '{sentence}'," for lang, sentence in sample_sentences.items()
))

if st.button("Submit"):
    user_masked_sentence = user_sentence.replace('____', unmasker.tokenizer.mask_token)

    user_predictions = unmasker(user_masked_sentence)
    
    # st.write(user_predictions)  

    if len(user_predictions) > 0:
        # st.write(f"Top prediction for the masked token: {user_predictions[0]['sequence']}")

        st.write("### Predictions for Sample Sentences:")
        predictions = fill_mask_for_languages(sample_sentences)
        
        for language, language_predictions in predictions.items():
            original_sentence = sample_sentences[language]
            predicted_sentence = replace_mask(original_sentence, language_predictions[0]['token_str'])  
            st.write(language_predictions)
            st.write(f"Original sentence ({language}): {original_sentence}")
            st.write(f"Top prediction for the masked token: {predicted_sentence}\n")
            st.write("=" * 80)

css = """
<style>
footer {display:none !important}

.stButton > button {
    background-color: #17152e;
    color: white;
    border: none;
    padding: 0.75em 2em;
    text-align: center;
    text-decoration: none;
    display: inline-block;
    font-size: 16px;
    margin: 4px 2px;
    cursor: pointer;
    border-radius: 12px;
    transition: background-color 0.3s ease;
}

.stButton > button:hover {
    background-color: #3c4a6b;
}

.stTextInput, .stTextArea {
    border: 1px solid #e6e6e6;
    padding: 0.75em;
    border-radius: 10px;
    font-size: 16px;
    width: 100%;
}

.stTextInput:focus, .stTextArea:focus {
    border-color: #17152e;
    outline: none;
    box-shadow: 0px 0px 5px rgba(23, 21, 46, 0.5);
}

div[data-testid="stMarkdownContainer"] p {
    font-size: 16px;
}

.stApp {
    padding: 2em;
    font-family: 'Poppins', sans-serif;
}
</style>
"""
st.markdown(css, unsafe_allow_html=True)