import gradio as gr
from transformers import pipeline

# Load the emotion classification model from Hugging Face
classifier = pipeline("text-classification", model="j-hartmann/emotion-english-distilroberta-base")

# Define a dictionary to map emotions to emojis
emotion_to_emoji = {
    "anger": "😠",
    "disgust": "🤢",
    "fear": "😨",
    "joy": "😊",
    "neutral": "😐",
    "sadness": "😢",
    "surprise": "😲"
}

def classify_emotion(text):
    # Use the classifier to predict the emotion
    result = classifier(text)[0]
    emotion = result['label'].lower()
    # Get the corresponding emoji
    emoji = emotion_to_emoji.get(emotion, "❓")
    return emoji

# Create a Gradio interface
iface = gr.Interface(
    fn=classify_emotion,
    inputs="text",
    outputs="text",
    title="Emotion Classifier",
    description="Enter a sentence to classify its emotion and get an emoji response."
)

# Launch the Gradio app
if __name__ == "__main__":
    iface.launch()