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Parent(s):
da2923b
Create app.py
Browse filesPlatzi Project
app.py
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from transformers import pipeline
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import gradio as gr
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trans = pipeline("automatic-speech-recognition", model ="facebook/wav2vec2-large-xlsr-53-spanish")
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traductor = pipeline("translation", model = "Helsinki-NLP/opus-mt-es-en")
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ner = pipeline("ner", model = "d4data/biomedical-ner-all")
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def audio2text(audio):
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text = trans(audio)["text"]
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return text
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def text2eng(text):
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return traductor(text)[0]["translation_text"]
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def eng2ner(text):
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output = ner(text)
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return {"text": text, "entities": output}
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demo = gr.Blocks()
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with demo:
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gr.Markdown("Demo sobre historia clínica en español a entidades en ingles")
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audio = gr.Audio(sources="microphone", type="filepath")
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texto = gr.Textbox()
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b_text = gr.Button("Transcribir")
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b_text.click(audio2text, inputs=audio, outputs=texto)
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transcripcion = gr.Textbox()
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b_trans = gr.Button("Traducir historia")
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b_trans.click(text2eng, inputs=texto, outputs=transcripcion)
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entidades = gr.HighlightedText()
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b_ner =gr.Button("Search entities")
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b_ner.click(eng2ner, inputs=transcripcion, outputs=entidades)
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demo.launch()
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