app.py

import os
import requests
import gradio as gr

API_URL = "https://router.huggingface.co/hf-inference/models/cardiffnlp/twitter-roberta-base-sentiment-latest"
headers = {"Authorization": f"Bearer {os.environ.get('HF_TOKEN')}"}

def query(payload):
    return requests.post(API_URL, headers=headers, json=payload).json()

def colorize(label):
    colors = {
        "positive": "green",
        "negative": "red",
        "neutral": "orange"
    }
    return colors.get(label.lower(), "black")

def predict_sentiment(text):
    if not text.strip():
        return "⚠️ Input kosong"

    output = query({"inputs": text})
    try:
        preds = output[0]
        main = max(preds, key=lambda x: x["score"])
        c = colorize(main["label"])

        main_html = f"""
        <h3>🎯 Prediksi Utama: <span style='color:{c}'>{main['label']}</span> ({main['score']:.4f})</h3>
        """

        details = ""
        for p in preds:
            col = colorize(p["label"])
            details += f"<div><b style='color:{col}'>{p['label']}</b> → {p['score']:.4f}</div>"

        return main_html + "<br>" + details

    except:
        return str(output)

with gr.Blocks(title="Twitter Sentiment Analysis") as ui:
    gr.Markdown("## 🧠 Twitter Sentiment Analysis (RoBERTa)")
    gr.Markdown("Masukkan teks untuk dianalisis sentimennya:")

    input_box = gr.Textbox(lines=3, label="Teks")
    output_box = gr.HTML(label="Hasil Prediksi")
    btn = gr.Button("Analisis Sentimen")

    btn.click(predict_sentiment, inputs=input_box, outputs=output_box)

ui.launch()