Create app.py
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app.py
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import gradio as gr
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from transformers import pipeline
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# Assuming you want to use a specific model for sentiment analysis; if not, the pipeline defaults to an English model.
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# For multilingual support including Korean, you might need to specify a model that supports Korean.
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# For this example, we'll proceed with the default model for demonstration purposes.
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sentiment_analysis = pipeline("sentiment-analysis")
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def get_sentiment(text):
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# Perform sentiment analysis on the input text
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result = sentiment_analysis(text)
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# Format the result to display it nicely
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formatted_result = f"Label: {result[0]['label']}, Score: {result[0]['score']:.4f}"
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return formatted_result
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# Define the Gradio interface
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interface = gr.Interface(
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fn=get_sentiment, # function to call
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inputs=gr.inputs.Textbox(lines=2, placeholder="์ฌ๊ธฐ์ ํ
์คํธ๋ฅผ ์
๋ ฅํ์ธ์..."), # input component
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outputs="text", # output component
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title="Text Sentiment Analysis", # title of the interface
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description="This app analyzes the sentiment of input text. Enter text to see if it's positive or negative." # description
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)
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# Launch the Gradio app
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interface.launch()
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