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""" |
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translation program for simple text |
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1. detect language from langdetect |
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2. translate to target language given by user |
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Example from |
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https://www.thepythoncode.com/article/machine-translation-using-huggingface-transformers-in-python |
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user_input: |
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string: string to be translated |
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target_lang: language to be translated to |
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Returns: |
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string: translated string of text |
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""" |
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from __future__ import annotations |
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from typing import Iterable |
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import gradio as gr |
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from gradio.themes.base import Base |
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from gradio.themes.utils import colors, fonts, sizes |
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import argparse |
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import langid |
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from transformers import pipeline |
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class myTheme(Base): |
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def __init__( |
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self, |
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*, |
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primary_hue: colors.Color | str = colors.red, |
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secondary_hue: colors.Color | str = colors.blue, |
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neutral_hue: colors.Color | str = colors.orange, |
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spacing_size: sizes.Size | str = sizes.spacing_md, |
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radius_size: sizes.Size | str = sizes.radius_md, |
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text_size: sizes.Size | str = sizes.text_lg, |
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font: fonts.Font |
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| str |
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| Iterable[fonts.Font | str] = ( |
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fonts.GoogleFont("handjet"), |
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"cursive", |
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), |
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font_mono: fonts.Font |
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| str |
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| Iterable[fonts.Font | str] = ( |
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fonts.GoogleFont("IBM Plex Mono"), |
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"ui-monospace", |
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"monospace", |
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), |
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): |
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super().__init__( |
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primary_hue=primary_hue, |
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secondary_hue=secondary_hue, |
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neutral_hue=neutral_hue, |
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spacing_size=spacing_size, |
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radius_size=radius_size, |
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text_size=text_size, |
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font=font, |
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font_mono=font_mono, |
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) |
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super().set( |
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body_background_fill="repeating-linear-gradient(135deg, *primary_200, *primary_200 10px, *primary_50 10px, *primary_50 20px)", |
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body_background_fill_dark="repeating-linear-gradient(135deg, *primary_800, *primary_800 10px, *primary_900 10px, *primary_900 20px)", |
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button_primary_background_fill="linear-gradient(45deg, *primary_300, *secondary_400)", |
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button_primary_background_fill_hover="linear-gradient(45deg, *primary_200, *secondary_300)", |
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button_primary_text_color="white", |
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button_primary_background_fill_dark="linear-gradient(90deg, *primary_600, *secondary_800)", |
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slider_color="*secondary_300", |
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slider_color_dark="*secondary_600", |
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block_title_text_weight="600", |
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block_border_width="3px", |
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block_shadow="*shadow_drop_lg", |
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button_shadow="*shadow_drop_lg", |
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button_large_padding="24px", |
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) |
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def detect_lang(article): |
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""" |
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Language Detection using library langid |
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Args: |
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article (string): article that user wish to translate |
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target_lang (string): language user want to translate article into |
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Returns: |
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string: detected language short form |
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""" |
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result_lang = langid.classify(article) |
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return result_lang[0] |
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def opus_trans(article, target_language): |
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""" |
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Translation by Helsinki-NLP model |
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Args: |
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article (string): article that user wishes to translate |
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result_lang (string): detected language in short form |
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target_language (string): language that user wishes to translate article into |
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Returns: |
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string: translated piece of article based off target_language |
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""" |
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print(target_language) |
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result_lang = detect_lang(article, target_language) |
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if target_language == "English": |
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target_lang = "en" |
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elif target_language == "Chinese": |
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target_lang = "zh" |
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print(target_lang) |
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if result_lang != target_lang: |
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task_name = f"translation_{result_lang}_to_{target_lang}" |
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model_name = f"Helsinki-NLP/opus-mt-{result_lang}-{target_lang}" |
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translator = pipeline(task_name, model=model_name, tokenizer=model_name) |
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translated = translator(article)[0]["translation_text"] |
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else: |
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translated = "Error: You chose the same language as the article detected language. Please reselect target_language and try again." |
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return translated |
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myTheme = myTheme() |
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with gr.Blocks(theme=myTheme) as demo: |
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article = gr.Textbox(label="Article") |
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lang_select = gr.Radio(["English", "Chinese"], label="Select Desired Language") |
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result = gr.Textbox(label="Translated Result") |
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trans_btn = gr.Button("Translate") |
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trans_btn.click(fn=opus_trans, inputs=[article, lang_select], outputs=result) |
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demo.launch() |
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