import os
from .pipeline import ASR_Diarization


import json
import numpy as np

def load_known_embeddings(path="known_speakers.json"):
    if not os.path.exists(path):
        return {}
    with open(path, "r") as f:
        raw = json.load(f)
    return {name: np.array(emb, dtype=np.float32) for name, emb in raw.items()}

HF_TOKEN = os.environ.get("HF_TOKEN", None)
known_embeddings = load_known_embeddings()
pipe = ASR_Diarization(HF_TOKEN)

def inference(inputs):
    return pipe(inputs)

def inference_with_eval(inputs, output_dir, base_name, ref_rttm=None, ref_json=None):
    result = pipe(inputs)
    pipe.evaluate(output_dir, base_name, ref_rttm, ref_json)
    return result