import numpy as np
from scipy.signal import resample_poly
from math import gcd


def pcm_bytes_to_float32(pcm_bytes: bytes, dtype=np.int16) -> np.ndarray:
    """Convert raw PCM bytes (16-bit signed int) to float32 in [-1, 1]."""
    audio = np.frombuffer(pcm_bytes, dtype=dtype)
    return audio.astype(np.float32) / 32768.0


def float32_to_pcm_bytes(audio) -> bytes:
    """Convert float32 audio in [-1, 1] to 16-bit PCM bytes.

    Accepts numpy arrays or PyTorch tensors.
    """
    if not isinstance(audio, np.ndarray):
        audio = audio.detach().cpu().numpy()
    clamped = np.clip(audio, -1.0, 1.0)
    return (clamped * 32767).astype(np.int16).tobytes()


def resample(audio: np.ndarray, orig_sr: int, target_sr: int) -> np.ndarray:
    """Resample audio from orig_sr to target_sr using polyphase filtering."""
    if orig_sr == target_sr:
        return audio
    divisor = gcd(orig_sr, target_sr)
    up = target_sr // divisor
    down = orig_sr // divisor
    return resample_poly(audio, up, down).astype(audio.dtype)


def split_sentences(text: str) -> tuple[list[str], str]:
    """Split text into completed sentences and a remaining buffer.

    Returns (sentences, remaining_buffer).
    Splits on sentence-ending punctuation followed by whitespace.
    """
    sentences = []
    buffer = text
    terminators = ".!?"

    i = 0
    start = 0
    while i < len(buffer):
        if buffer[i] in terminators:
            # Look ahead for whitespace or end of string
            end = i + 1
            while end < len(buffer) and buffer[end] in terminators:
                end += 1
            if end >= len(buffer) or buffer[end] == " " or buffer[end] == "\n":
                sentence = buffer[start:end].strip()
                if sentence:
                    sentences.append(sentence)
                start = end
                i = end
            else:
                i += 1
        else:
            i += 1

    remaining = buffer[start:].strip()
    return sentences, remaining