app.py

import gradio as gr
from transformers import pipeline

## Load Pipeline
sentiment_pipeline = pipeline("sentiment-analysis",
                              model="AfroLogicInsect/sentiment-analysis-model_v2")

def predict_sentiment(text):
    if not text.strip():
        return "Please enter some text", 0.0

    result = sentiment_pipeline(text)[0]
    
    # Fixed label interpretation
    if result['label'] == 'POSITIVE':
        label = "😊 Positive"
    elif result['label'] == 'NEGATIVE':
        label = "😞 Negative"
    else:
        # Fallback for LABEL_0/LABEL_1
        label = "😊 Positive" if result['label'] == 'LABEL_1' else "😞 Negative"
    
    return label, round(result['score'], 3)

iface = gr.Interface(
    fn = predict_sentiment,
    inputs=gr.Textbox(label="Enter text"),
    outputs=[gr.Text(label="Sentiment"),
            gr.Number(label="Confidence")]
)

iface.launch(share=True)