import gradio as gr
from transformers import pipeline

model_id = "Subhajit01/distilbert-base-uncased-finetuned-emotion"
classifier = pipeline("text-classification", model=model_id)
labels = ['sadness', 'joy', 'love', 'anger', 'fear', 'surprise']

def predict(text):
    max_prob_id = 0
    max_prob = 0
    preds = classifier(text, return_all_scores=True)
    for i in range(len(preds[0])):
        if (preds[0][i]["score"] > max_prob):
            max_prob = preds[0][i]["score"]
            max_prob_id = i
    return labels[max_prob_id]

iface = gr.Interface(fn=predict, 
                     inputs="text", 
                     outputs="text",
                     title="Sentiment Analyzer",
                     description="Enter text to analyze its sentiment.")

iface.launch(share= True)