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Update app.py
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app.py
CHANGED
@@ -5,34 +5,41 @@ import json
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# Use a pipeline as a high-level helper
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from transformers import pipeline
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# Load the JSON data from the file
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with open('language.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
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gr.close_all()
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# Use a pipeline as a high-level helper
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from transformers import pipeline
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# Initialize the translation pipeline
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text_translator = pipeline("translation", model="facebook/nllb-200-distilled-600M", torch_dtype=torch.bfloat16)
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# Load the JSON data from the file
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with open('language.json', 'r') as file:
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language_data = json.load(file)
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# Extract language names from the JSON data
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language_names = [entry['Language'] for entry in language_data]
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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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if dest_code:
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translation = text_translator(text, src_lang="eng_Latn", tgt_lang=dest_code)
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return translation[0]["translation_text"]
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else:
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return "Destination language code not found."
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# Create and launch the Gradio interface
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gr.close_all()
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demo = gr.Interface(
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fn=translate_text,
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inputs=[
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gr.Textbox(label="Input text to translate", lines=6),
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gr.Dropdown(language_names, label="Select Destination Language")
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],
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outputs=[gr.Textbox(label="Translated text", lines=4)],
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title="Multi-language Translator",
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description="This application translates any English text to multiple languages."
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)
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demo.launch(auth=('user', 'test@123'))
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