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import torch |
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import gradio as gr |
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import json |
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from transformers import pipeline |
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text_translator = pipeline("translation", model="facebook/nllb-200-distilled-600M", |
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torch_dtype=torch.bfloat16) |
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with open('languages.json', 'r') as file: |
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language_data = json.load(file) |
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def get_FLORES_code_from_language(language): |
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for entry in language_data: |
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if entry['Language'].lower() == language.lower(): |
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return entry['FLORES-200 code'] |
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return None |
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def translate_text(text, destination_language): |
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dest_code= get_FLORES_code_from_language(destination_language) |
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translation = text_translator(text, |
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src_lang="eng_Latn", |
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tgt_lang=dest_code) |
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return translation[0]["translation_text"] |
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gr.close_all() |
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app = gr.Interface(fn=translate_text, |
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inputs=[gr.Textbox(label="Input text to translate",lines=6), gr.Dropdown(["Telugu","Tamil", "Kannada", "Malayalam","Hindi"], label="Select Destination Language")], |
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outputs=[gr.Textbox(label="Translated text",lines=4)], |
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title="Multi language translator") |
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app.launch() |
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