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import streamlit as st |
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from transformers import AutoTokenizer, AutoModelForSeq2SeqLM |
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from configs.download_files import FileDownloader |
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from configs.db_configs import add_one_item |
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from streamlit.components.v1 import html |
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from configs.html_features import set_image |
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from sacrebleu.compat import corpus_bleu |
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import pandas as pd |
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def translate_text_to_text(text, target_lang): |
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prefix = f'translate to {target_lang}: ' |
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text = prefix + text |
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tokenizer = AutoTokenizer.from_pretrained('CohereForAI/aya-101') |
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inputs = tokenizer(text, return_tensors='pt') |
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model = AutoModelForSeq2SeqLM.from_pretrained('CohereForAI/aya-101') |
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outputs = model.generate(inputs, max_new_tokens=len(inputs.input_ids[0]) * 3, do_sample=False) |
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translated_text = tokenizer.decode(outputs[0], skip_special_tokens=True) |
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return translated_text |
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def validate_translation(original_text, translated_text): |
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return corpus_bleu(translated_text, [original_text]) |
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def main(): |
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st.title('Text Translator') |
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im1, im2, im3 = st.columns([1, 5.3, 1]) |
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with im1: |
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pass |
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with im2: |
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url = "https://i.postimg.cc/jdF1hPng/combined.png" |
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html(set_image(url), height=500, width=500) |
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with im3: |
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pass |
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languages = ['Afrikaans', 'Amharic', 'Arabic', 'Azerbaijani', 'Belarusian', |
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'Bengali', 'Bulgarian', 'Catalan', 'Cebuano', 'Czech', 'Welsh', |
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'Danish', 'German', 'Greek', 'English', 'Esperanto', 'Estonian', |
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'Basque', 'Finnish', 'Filipino', 'French', 'Western Frisian', |
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'Scottish Gaelic', 'Irish', 'Galician', 'Gujarati', 'Haitian', |
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'Hausa', 'Hebrew', 'Hindi', 'Hungarian', 'Armenian', 'Igbo', |
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'Indonesian', 'Icelandic', 'Italian', 'Javanese', 'Japanese', |
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'Kannada', 'Georgian', 'Kazakh', 'Khmer', 'Kirghiz', 'Korean', |
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'Kurdish', 'Lao', 'Latvian', 'Latin', 'Lithuanian', 'Luxembourgish', |
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'Malayalam', 'Marathi', 'Macedonian', 'Malagasy', 'Maltese', |
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'Mongolian', 'Maori', 'Malay', 'Burmese', 'Nepali', 'Dutch', |
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'Norwegian', 'Pedi', 'Nyanja', 'Odia', 'Panjabi', 'Persian', |
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'Polish', 'Portuguese', 'Pushto', 'Romanian', 'Russian', 'Sinhala', |
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'Slovak', 'Slovenian', 'Samoan', 'Shona', 'Sindhi', 'Somali', |
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'Southern Sotho', 'Spanish', 'Albanian', 'Serbian', 'Sundanese', |
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'Swahili', 'Swedish', 'Tamil', 'Telugu', 'Tajik', 'Thai', 'Turkish', |
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'Twi', 'Ukrainian', 'Urdu', 'Uzbek', 'Vietnamese', 'Xhosa', 'Yiddish', |
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'Yoruba', 'Chinese','Zulu' |
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] |
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target_lang = st.sidebar.selectbox('Target Language', languages, index=1) |
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text = st.text_area('Text Translator', placeholder='Enter your input text here ...', height=200, label_visibility='hidden') |
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if st.button('translate it'): |
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if text != '': |
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with st.expander('Original Text'): |
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st.write(text) |
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add_one_item(text, 'Text Translator') |
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with st.expander('Translated Text'): |
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translated_text = translate_text_to_text(text, target_lang) |
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st.write(translated_text) |
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col1, col2 = st.columns(2) |
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with col1: |
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with st.expander('Download Translated Text'): |
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FileDownloader(translated_text, 'txt').download() |
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with col2: |
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with st.expander('Translated Text Validation'): |
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bleu_score = validate_translation(text, translated_text) |
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df = pd.DataFrame({ |
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'Brevity Penalty' : bleu_score.bp, |
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'the length of the original text' : bleu_score.ref_len, |
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'the length of the translated text' : bleu_score.sys_len, |
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'Ratio' : bleu_score.ratio |
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}, index=1) |
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st.dataframe(df) |
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else: |
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st.error('Please enter a non-empty text.') |
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if __name__ == '__main__': |
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main() |