app.py

from pyabsa import AspectTermExtraction as ATEPC
import os

MODEL_PATH = "checkpoints/ATEPC_MULTILINGUAL_CHECKPOINT"

def fix_model_filenames(directory):
    if not os.path.exists(directory):
        return False

    for f in os.listdir(directory):
        if f.endswith(".config") and f != "atepc.config":
            os.rename(
                os.path.join(directory, f),
                os.path.join(directory, "atepc.config")
            )
    return True

# Fix filenames once
fix_model_filenames(MODEL_PATH)

# Load model ONCE
aspect_extractor = ATEPC.AspectExtractor(
    checkpoint=MODEL_PATH,
    auto_device=True
)

def predict(text):
    """
    Hugging Face inference entrypoint
    """
    if not text or not text.strip():
        return []

    result = aspect_extractor.predict(
        [text],
        print_result=False,
        pred_sentiment=True
    )

    data = result[0]

    aspects = data.get("aspect", [])
    sentiments = data.get("sentiment", [])
    confidences = data.get("confidence", [])

    output = []

    for asp, sent, conf in zip(aspects, sentiments, confidences):
        output.append({
            "aspect": asp,
            "sentiment": sent,
            "confidence": round(conf * 100, 1)
        })

    return output