import fasttext
from transformers import pipeline


class FastTextClassifierPipeline(pipeline):
    def __init__(self, model_path):
        self.model = fasttext.load_model(model_path)

    def __call__(self, texts):
        if isinstance(texts, str):
            texts = [texts]

        results = []
        for text in texts:
            prediction = self.model.predict(text)
            label = prediction[0][0].replace("__label__", "")
            score = prediction[1][0]
            results.append({"label": label, "score": score})

        return results


classifier = FastTextClassifierPipeline("fasttext_news_classifier.bin")