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Create app.py
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app.py
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import torch
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import gradio as gr
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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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text_translator = pipeline("translation", model="facebook/nllb-200-distilled-600M",
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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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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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# text = "Hello Friends, How are you?"
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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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demo = gr.Interface(fn=translate_text,
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inputs=[gr.Textbox(label="Zu übersetzenden Text eingeben",lines=6),
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gr.Dropdown(["German","French", "Hindi", "Romanian "],
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label="Zielsprache auswählen")],
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outputs=[gr.Textbox(label="Übersetzter Text",lines=4)],
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title="Projekt 4: Mehrsprachiger Übersetzer",
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description="DIESE ANWENDUNG WIRD VERWENDET, UM EINEN BELIEBIGEN ENGLISCHEN TEXT IN MEHRERE SPRACHEN ZU ÜBERSETZEN",
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allow_flagging="never",
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submit_btn="Übermitteln",
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clear_btn="Bereinigen")
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demo.launch()
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