app.py

import gradio as gr
from transformers import AutoTokenizer, AutoModelForSequenceClassification
import torch

MODEL_NAME = "AnasAlokla/multilingual_go_emotions"
tokenizer = AutoTokenizer.from_pretrained(MODEL_NAME)
model = AutoModelForSequenceClassification.from_pretrained(MODEL_NAME)
labels = model.config.id2label

def analyze(text):
    inputs = tokenizer(text, return_tensors="pt", truncation=True)
    outputs = model(**inputs)
    probs = torch.sigmoid(outputs.logits)[0]
    emotion_scores = {labels[i]: float(probs[i]) for i in range(len(labels))}
    sorted_emotions = dict(sorted(emotion_scores.items(), key=lambda x: x[1], reverse=True))
    return sorted_emotions

iface = gr.Interface(fn=analyze, inputs="text", outputs="json", title="GoEmotions Sentiment Analyzer", description="Enter any text and get scores for 28 emotions.")

iface.launch()