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

model = AutoModelForSequenceClassification.from_pretrained("gsar78/Greek_Sentiment")
tokenizer = AutoTokenizer.from_pretrained("gsar78/Greek_Sentiment")

def predict(text):
    inputs = tokenizer(text, return_tensors="pt")
    outputs = model(**inputs)
    scores = torch.nn.functional.softmax(outputs.logits, dim=1)
    return {"Positive": scores[:, 1].item(), "Negative": scores[:, 0].item()}

iface = gr.Interface(
    fn=predict,
    inputs="text",
    outputs="label",
    title="Hellenic Sentiment AI",
    description=None,
    article=None,
    theme="default",
    flagging_dir=None,
    share=True,
    favicon_path=None,
    css=None,
    analytics_script=None,
    allow_flagging="never",
    allow_screenshot=True,
    enable_queue=True,
    show_input=True,
    show_output=True,
    footer="Development by Geo Sar"
)

iface.launch()