from fastai.text.all import*
import gradio as gr

learn = load_learner('nlp_model.pkl')

labels = learn.dls.vocab

examples = ["I can't believe you lied to me again! This is unacceptable!",
            "Got a surprise gift today, feeling overjoyed!"]



def classify_text(text):
    pred,pred_idx,probs = learn.predict(text)
    return {labels[i]: float(probs[i]) for i in range(len(labels))}


interface = gr.Interface(fn=classify_text,
                        inputs = gr.inputs.Texbox(placeholder="Enter Text here", label='Input text',lines=5)),
                        outputs=gr.outputs.Label(num_top_classes=4, label='Emotion inthe Text'),
                        verbose=True,
                        title="Emotion Classifier",
                        theme='soft')

interface.launch()