import gradio as gr
from transformers import pipeline


sentimentPipeline = pipeline("zero-shot-classification", model="typeform/distilbert-base-uncased-mnli")

def sentiment_analysis(text, labels):
    candidate_labels = labels.split(',') 
    results = sentimentPipeline(text, candidate_labels)

    total_results = ""
    index = 0

    for candidate_label in candidate_labels:
        total_results += f"Sentiment: {results.get('labels')[index]}, Score: {results.get('scores')[index]}"
        total_results += '\r\n'
        index += 1

    return total_results
    
demo = gr.Interface(fn=sentiment_analysis, 
                    inputs=[
                        gr.components.Textbox(label="Text"),
                        gr.components.Textbox(label="Label")
                    ],
                    outputs='text',
                    examples=[['I have a problem with my iphone that needs to be resolved asap!!', 'urgent, not urgent, phone, tablet, computer'], ['Last week I upgraded my iOS version and ever since then my phone has been overheating whenever I use your app.', 'mobile, website, billing, account access']],
                    title = "文本情感分析"
                    )


if __name__ == "__main__":
    demo.queue(concurrency_count=3)
    demo.launch(server_name = "0.0.0.0", server_port = 7028)