# app.py
import gradio as gr
from transformers import DistilBertTokenizer, DistilBertForSequenceClassification

model_name = "distilbert-base-uncased"
tokenizer = DistilBertTokenizer.from_pretrained(model_name)
model = DistilBertForSequenceClassification.from_pretrained(model_name)

def predict_sentiment(text):
    # Tokenize and predict
    inputs = tokenizer(text, return_tensors="pt")
    outputs = model(**inputs)
    logits = outputs.logits
    predicted_class = logits.argmax().item()

    # Return the predicted class
    return {"positive": logits[0][1].item(), "negative": logits[0][0].item()}

iface = gr.Interface(
    fn=predict_sentiment,
    inputs=gr.Textbox(),
    outputs="label",