app.py

import gradio as gr
from transformers import pipeline
import os

MODEL_NAME = os.getenv("MODEL_NAME", "distilbert-base-uncased-finetuned-sst-2-english")
analyzer = pipeline("sentiment-analysis", model=MODEL_NAME)

def analyze(message: str):
    if not isinstance(message, str) or not message.strip():
        return {"sentiment": "neutral", "score": 0.0}
    result = analyzer(message)[0]  # {'label': 'POSITIVE'|'NEGATIVE', 'score': 0.xx}
    label = result["label"].lower()
    score = float(result.get("score", 0.0))
    if label not in ("positive", "negative"):
        sentiment = "neutral"
    elif 0.48 <= score <= 0.52:
        sentiment = "neutral"
    else:
        sentiment = label
    return {"sentiment": sentiment, "score": score}

demo = gr.Interface(
    fn=analyze,
    inputs=gr.Textbox(label="Mesaj"),
    outputs=gr.JSON(label="Sonuç"),
    title="Duygu Analizi",
    allow_flagging="never"
)

if __name__ == "__main__":
    demo.launch()