# -*- coding: utf-8 -*-
"""s2s 实时语音栈（VAD 本地 + 云 ASR/LLM/TTS）桥接

在 DPM 进程内以后台线程运行 s2s 的 RealtimeServer（默认 :8765 /v1/realtime）。
- 复用 live-avatar 云化栈（speech-to-speech v0.2.11 + cloud-migration 补丁）。
- 依赖已并入 backend/pyproject.toml；本模块负责按 DPM Settings 组装并启动。
- 前端语音对话页通过 WS 直连 ws://<host>:<S2S_PORT>/v1/realtime。
"""

import logging
import threading
import time

from .config import settings

log = logging.getLogger("dpm.s2s")


def _build_pool(stop_event: threading.Event):
    """按 DPM 配置构建 s2s 管线池（含 VAD/silero 加载 + LLM warmup，耗时约 30~60s）。"""
    import sys

    from speech_to_speech.api.openai_realtime.websocket_router import create_app
    from speech_to_speech.s2s_pipeline import (
        _build_realtime_pipeline_unit,
        parse_arguments,
        prepare_all_args,
    )

    # 与 start_backend.sh 等价的参数（api_key 留空 → handler 从 env DASHSCOPE_API_KEY 读取）
    sys.argv = [
        "dpm-s2s",
        "--mode", "realtime",
        "--stt", "dashscope-asr",
        "--llm_backend", "chat-completions",
        "--tts", "qwen3-cloud",
        "--model_name", settings.S2S_LLM_MODEL,
        "--responses_api_base_url", settings.LLM_BASE_URL,
        "--responses_api_api_key", settings.DASHSCOPE_API_KEY,
        "--dashscope_asr_model", settings.S2S_STT_MODEL,
        "--qwen3_cloud_model", settings.S2S_TTS_MODEL,
        "--qwen3_cloud_voice", settings.S2S_TTS_VOICE,
        "--enable_live_transcription", "false",
        "--thresh", "0.6",
        "--min_silence_ms", "500",
        "--min_speech_ms", "500",
        "--log_level", settings.S2S_LOG_LEVEL,
    ]
    args = parse_arguments()
    prepare_all_args(
        args.module_kwargs,
        args.whisper_stt_handler_kwargs,
        args.paraformer_stt_handler_kwargs,
        args.faster_whisper_stt_handler_kwargs,
        args.mlx_audio_whisper_stt_handler_kwargs,
        args.parakeet_tdt_stt_handler_kwargs,
        args.dashscope_asr_stt_handler_kwargs,
        args.language_model_handler_kwargs,
        args.responses_api_language_model_handler_kwargs,
        args.chat_tts_handler_kwargs,
        args.facebook_mms_tts_handler_kwargs,
        args.pocket_tts_handler_kwargs,
        args.kokoro_tts_handler_kwargs,
        args.qwen3_tts_handler_kwargs,
        args.qwen3_cloud_tts_handler_kwargs,
    )

    pool = [
        _build_realtime_pipeline_unit(
            index=i,
            stop_event=stop_event,
            module_kwargs=args.module_kwargs,
            vad_handler_kwargs=args.vad_handler_kwargs,
            whisper_stt_handler_kwargs=args.whisper_stt_handler_kwargs,
            faster_whisper_stt_handler_kwargs=args.faster_whisper_stt_handler_kwargs,
            paraformer_stt_handler_kwargs=args.paraformer_stt_handler_kwargs,
            mlx_audio_whisper_stt_handler_kwargs=args.mlx_audio_whisper_stt_handler_kwargs,
            parakeet_tdt_stt_handler_kwargs=args.parakeet_tdt_stt_handler_kwargs,
            dashscope_asr_stt_handler_kwargs=args.dashscope_asr_stt_handler_kwargs,
            language_model_handler_kwargs=args.language_model_handler_kwargs,
            responses_api_language_model_handler_kwargs=args.responses_api_language_model_handler_kwargs,
            chat_tts_handler_kwargs=args.chat_tts_handler_kwargs,
            facebook_mms_tts_handler_kwargs=args.facebook_mms_tts_handler_kwargs,
            pocket_tts_handler_kwargs=args.pocket_tts_handler_kwargs,
            kokoro_tts_handler_kwargs=args.kokoro_tts_handler_kwargs,
            qwen3_tts_handler_kwargs=args.qwen3_tts_handler_kwargs,
            qwen3_cloud_tts_handler_kwargs=args.qwen3_cloud_tts_handler_kwargs,
        )
        for i in range(settings.S2S_NUM_PIPELINES)
    ]

    app = create_app(pool=pool, stop_event=stop_event)
    return app, pool


def start_s2s_backend(stop_event: threading.Event) -> None:
    """后台线程构建管线并启动 RealtimeServer（阻塞调用，放线程里跑）。"""

    def _run() -> None:
        from speech_to_speech.api.openai_realtime.server import RealtimeServer

        # LLM warmup / 云 ASR/TTS 连接在弱网下会瞬断：整个池构建重试几次
        last_exc: Exception | None = None
        log.info(
            "s2s: 启动配置 STT=%s LLM=%s TTS=%s(%s) pipelines=%d ws://%s:%d/v1/realtime retries=%d",
            settings.S2S_STT_MODEL, settings.S2S_LLM_MODEL, settings.S2S_TTS_MODEL,
            settings.S2S_TTS_VOICE, settings.S2S_NUM_PIPELINES,
            settings.S2S_HOST, settings.S2S_PORT, settings.S2S_BUILD_RETRIES,
        )
        for attempt in range(settings.S2S_BUILD_RETRIES):
            try:
                log.info(
                    "s2s: 构建语音管线池（%d 路，尝试 %d/%d，首次约 30~60s）…",
                    settings.S2S_NUM_PIPELINES,
                    attempt + 1,
                    settings.S2S_BUILD_RETRIES,
                )
                app, pool = _build_pool(stop_event)
                server = RealtimeServer(
                    stop_event=stop_event,
                    pool=pool,
                    host=settings.S2S_HOST,
                    port=settings.S2S_PORT,
                )
                # 关键：与 s2s_pipeline.main() 的 realtime 分支一致——用 ThreadManager
                # 启动 RealtimeServer + 全部 handler 线程（VAD/STT/LLM/TTS）。
                # 只跑 server 不启动 handler 线程会导致管线不处理任何音频。
                from speech_to_speech.utils.thread_manager import ThreadManager

                all_handlers = [server] + [h for unit in pool for h in unit.handlers]
                thread_manager = ThreadManager(all_handlers)
                thread_manager.start()
                log.info("s2s: 实时语音服务 ws://%s:%d/v1/realtime", settings.S2S_HOST, settings.S2S_PORT)
                thread_manager.wait()
                return
            except Exception as e:  # noqa: BLE001
                last_exc = e
                log.warning("s2s: 构建尝试 %d/%d 失败：%s", attempt + 1, settings.S2S_BUILD_RETRIES, e)
                if attempt + 1 < settings.S2S_BUILD_RETRIES:
                    time.sleep(settings.S2S_BUILD_RETRY_DELAY)
        log.error("s2s: 启动失败（DPM_S2S_ENABLED=0 可关闭）：%s", last_exc)

    threading.Thread(target=_run, daemon=True).start()