import gradio as gr
from transformers import pipeline

# Load sentiment analysis models
english_sentiment_model = pipeline("sentiment-analysis", model="nlptown/bert-base-multilingual-uncased-sentiment")
arabic_sentiment_model = pipeline("text-classification", model="CAMeL-Lab/bert-base-arabic-camelbert-da-sentiment")

# Define label meanings for Arabic sentiment analysis
arabic_labels = {
    "positive": "إيجابي",
    "negative": "سلبي",
    "neutral": "محايد" 
}

def analyze_sentiment(text, language):
    if language == "English":
        result = english_sentiment_model(text)
        return result[0]['label'], result[0]['score']
    else:
        result = arabic_sentiment_model(text)
        label = result[0]['label']
        arabic_label = arabic_labels.get(label, "غير معروف")  # Default to "Unknown" if label not found
        return arabic_label, result[0]['score']

# custom CSS
css = """
body {
    background-color: #f4f7f6;
    font-family: 'Arial', sans-serif;
}

h1, h2 {
    color: #3e606f;
}

.gradio-container {
    border-radius: 10px;
    box-shadow: 0 4px 20px rgba(0, 0, 0, 0.1);
}

button {
    background-color: #3e606f;
    color: white;
    border: none;
    border-radius: 5px;
    padding: 10px 15px;
    cursor: pointer;
}

button:hover {
    background-color: #2c4d4f;
}

.result {
    font-weight: bold;
    color: #3e606f;
}
"""

iface = gr.Interface(
    fn=analyze_sentiment,
    inputs=[
        gr.Textbox(label="Enter text", placeholder="Type your text here..."),
        gr.Radio(choices=["English", "Arabic"], label="Select Language")  # Default style retained
    ],
    outputs=[
        gr.Label(label="Sentiment"),
        gr.Number(label="Confidence Score")
    ],
    title="Sentiment Analysis",
    description="Analyze the sentiment of text in English and Arabic.",
    examples=[
        ["I love this product!", "English"],
        ["This is the worst experience I've ever had.", "English"],
        ["أنا سعيد جدًا بهذا!", "Arabic"],
        ["هذا المكان سيء للغاية.", "Arabic"]
    ],
    css=css
)

iface.launch()