import struct
import base64
import logging

import zhconv
from openai import OpenAI

logger = logging.getLogger(__name__)


def float32_to_s16le(float32_bytes: bytes) -> bytes:
    num_samples = len(float32_bytes) // 4
    floats = struct.unpack(f"<{num_samples}f", float32_bytes)
    int16_samples = [max(-32768, min(32767, int(f * 32767.0))) for f in floats]
    return struct.pack(f"<{num_samples}h", *int16_samples)


def build_display_text(accumulated: str, current: str) -> str:
    parts = [p for p in (accumulated, current) if p and p.strip()]
    return " ".join(parts)


def _to_traditional(text: str) -> str:
    if not text:
        return text
    return zhconv.convert(text, "zh-hant")


class ASRClient:
    def __init__(self, settings):
        self.settings = settings

    def transcribe_full(self, audio_bytes: bytes, language: str = "yue") -> str:
        audio_b64 = base64.b64encode(audio_bytes).decode()
        data_url = f"data:audio/wav;base64,{audio_b64}"

        client = OpenAI(
            api_key=self.settings.dashscope_api_key,
            base_url="https://dashscope-intl.aliyuncs.com/compatible-mode/v1",
        )

        asr_options: dict = {}
        if language != "auto":
            asr_options["language"] = language

        resp = client.chat.completions.create(
            model=self.settings.asr_model_name,
            messages=[{  # type: ignore[list-item]
                "role": "user",
                "content": [{
                    "type": "input_audio",
                    "input_audio": {"data": data_url},
                }],
            }],
            extra_body={"asr_options": asr_options} if asr_options else None,
        )

        result = resp.choices[0].message.content or ""
        return _to_traditional(result)