services/fake_news.py

from transformers import pipeline

try:
    fake_model = pipeline(
        "text-classification",
        model="mrm8488/bert-tiny-finetuned-fake-news-detection"
    )
except:
    fake_model = None


def detect_fake_news(texts):
    try:
        if fake_model is None:
            return []

        results = []

        for t in texts[:20]:
            res = fake_model(t[:512])[0]

            label = "Fake" if "fake" in res["label"].lower() else "Real"

            results.append({
                "text": t,
                "label": label,
                "score": float(res["score"])
            })

        return results

    except Exception as e:
        print("❌ fake news error:", e)
        return []