# deep_model.py

import torch
import librosa
from transformers import AutoFeatureExtractor, AutoModelForAudioClassification

MODEL_ID = "ylacombe/accent-classifier"
feature_extractor = AutoFeatureExtractor.from_pretrained(MODEL_ID)
model = AutoModelForAudioClassification.from_pretrained(MODEL_ID)

# لاحظ أن الترتيب يعتمد على ترتيب تصنيفات النموذج نفسه
label_map = {
    4: "england",
    14: "us"
}

def predict_accent(audio_path: str) -> str:
    audio, sr = librosa.load(audio_path, sr=16000)
    inputs = feature_extractor(audio, sampling_rate=16000, return_tensors="pt")
    
    with torch.no_grad():
        logits = model(**inputs).logits
        predicted_id = torch.argmax(logits, dim=-1).item()
    
    return label_map.get(predicted_id, f"Unknown (ID: {predicted_id})")