app.py

import gradio as gr
from transformers import pipeline
#from flask import jsonify

# Load pre-trained model and tokenizer from Hugging Face
#model_name = "aubmindlab/bert-base-arabertv02-twitter"
model_name = "CAMeL-Lab/bert-base-arabic-camelbert-msa-sentiment"
sentiment_analysis = pipeline("sentiment-analysis", model=model_name, tokenizer="CAMeL-Lab/bert-base-arabic-camelbert-msa-sentiment")

def analyze_sentiment(text):
    #result = sentiment_analysis(text)
    #return result
    result = sentiment_analysis(text)[0]
    """return jsonify({
        "sentiment": result['label'],
        "confidence": result['score']
    })"""
    return f"sentiment: {result['label']}, confidence: {result['score']}"

# Define Gradio interface
iface = gr.Interface(fn=analyze_sentiment, inputs="text", outputs="text", title="Arabic Sentiment Analysis")
iface.launch(share=True)