import gradio as gr
from transformers import pipeline
import base64
from PIL import Image
import io

model = pipeline("image-classification", model="dima806/facial_emotions_image_detection")

def predict_emotion(image_b64: str):
    image_data = base64.b64decode(image_b64.split(",")[1] if "," in image_b64 else image_b64)
    image = Image.open(io.BytesIO(image_data)).convert("RGB")
    predictions = model(image)
    return [[{"label": p["label"], "score": p["score"]} for p in predictions]]

demo = gr.Interface(
    fn=predict_emotion,
    inputs=gr.Textbox(),
    outputs="json",
    api_name="predict"
)
demo.launch()