326 lines
11 KiB
Python
326 lines
11 KiB
Python
#!/usr/bin/env python3
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"""
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VoxCPM 流式 TTS 服务 —— 按句分块合成，SSE 流式推送 PCM 音频。
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使用 OpenBMB VoxCPM 模型（Whispera 同款），无需 Genie TTS。
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配合前端 Web Audio API 实现边合成边播放，无需保存音频文件。
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启动方式:
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python streaming_tts_server.py --port 8902 --model-path ./models/VoxCPM
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"""
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import os
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import sys
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import json
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import base64
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import time
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import threading
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import argparse
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import warnings
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from contextlib import asynccontextmanager
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from pathlib import Path
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# 抑制 PyTorch weight_norm 弃用警告（来自 voxcpm 内部）
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warnings.filterwarnings("ignore", message=".*weight_norm.*deprecated.*")
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# ======================== 配置区域 ========================
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BASE_DIR = os.path.dirname(os.path.abspath(__file__))
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# 启用 TF32 加速（Ampere+ GPU）
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import torch
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torch.set_float32_matmul_precision("high")
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# 确保 torchaudio 已安装（VoxCPM 参考音频需要）
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try:
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import torchaudio # noqa: F401
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except ImportError:
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pass # 无参考音频时可选
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# 默认参数（可通过命令行覆盖）
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DEFAULT_MODEL_PATH = os.path.join(BASE_DIR, "models", "VoxCPM1__5")
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DEFAULT_PORT = 8902
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# 参考音频（用于统一音色，同一人物说的一段话 + 对应文本）
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# 如果配置了这对参数，所有合成都会克隆该音色，各句音色保持一致
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DEFAULT_PROMPT_WAV = os.path.join(BASE_DIR, "reference_audio.wav")
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DEFAULT_PROMPT_TEXT = "日子缓缓前行，不必急于追赶，照顾好自己的心情，认真过好当下的每一刻就足够了。"
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# 音频质量参数
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DEFAULT_CFG_VALUE = 1.5 # 音色贴合度 (1.0~3.0)，越高越贴近参考音频但可能不自然
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DEFAULT_INFERENCE_STEPS = 15 # 推理步数 (4~30)，越高音质越好但越慢
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# =========================================================
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# 请求级取消标志
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_cancel_flags: dict[str, threading.Event] = {}
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_cancel_lock = threading.Lock()
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# 当前活跃请求 ID（新请求到达时自动取消旧请求）
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_current_request_id: str | None = None
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_current_req_lock = threading.Lock()
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# 模型锁（VoxCPM 只允许单线程使用，新请求取消旧请求后等待锁释放）
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_model_lock = threading.Lock()
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def set_cancel(request_id: str) -> None:
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with _cancel_lock:
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evt = _cancel_flags.get(request_id)
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if evt is None:
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evt = threading.Event()
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_cancel_flags[request_id] = evt
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evt.set()
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def is_cancelled(request_id: str) -> bool:
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with _cancel_lock:
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evt = _cancel_flags.get(request_id)
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return evt is not None and evt.is_set()
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def cancel_current_and_set(new_request_id: str) -> str | None:
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"""取消当前活跃请求并注册新请求 ID，返回被取消的旧请求 ID。"""
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global _current_request_id
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with _current_req_lock:
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old = _current_request_id
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_current_request_id = new_request_id
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if old and old != new_request_id:
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set_cancel(old)
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# 若旧请求持有模型锁，强制释放以让新请求立即获取
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try:
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if _model_lock.locked():
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_model_lock.release()
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except RuntimeError:
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pass
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print(f"[VoxCPM TTS] 打断旧请求 {old}，开始新请求 {new_request_id}")
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return old
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# Lazy-loaded model singleton
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_model = None
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_singleton_lock = threading.Lock()
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_model_sample_rate = 24000
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def _get_model(model_path: str):
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"""延迟加载 VoxCPM 模型（线程安全）。"""
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global _model, _model_sample_rate
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if _model is not None:
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return _model, _model_sample_rate
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with _singleton_lock:
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if _model is not None:
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return _model, _model_sample_rate
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if "voxcpm" not in sys.modules:
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try:
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from voxcpm import VoxCPM # type: ignore
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except ImportError:
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raise ImportError(
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"无法导入 voxcpm 模块。请确保 Whispera-main 项目的 "
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"voxcpm-tts-streaming-module/src 在 sys.path 中，"
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"或 pip install 了 voxcpm 包。"
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)
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from voxcpm import VoxCPM # type: ignore
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mp = _resolve_model_path(model_path)
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print(f"[VoxCPM TTS] 加载模型: {mp}")
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_model = VoxCPM(
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voxcpm_model_path=mp,
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enable_denoiser=False,
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optimize=True,
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)
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_model_sample_rate = int(_model.tts_model.sample_rate)
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print(f"[VoxCPM TTS] 模型加载成功，采样率: {_model_sample_rate} Hz")
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return _model, _model_sample_rate
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def _resolve_model_path(model_path: str) -> str:
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"""解析模型路径：支持多种命名格式。"""
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base = Path(model_path).expanduser().resolve()
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if not base.exists():
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raise FileNotFoundError(f"VoxCPM 模型路径不存在: {base}")
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# 1. 直接就是模型目录（有 config.json）
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if (base / "config.json").is_file():
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return str(base)
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# 2. 检查常见子目录名
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for sub in ["openbmb__VoxCPM2", "openbmb__VoxCPM1.5",
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"VoxCPM2", "VoxCPM1.5", "VoxCPM1__5"]:
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candidate = base / sub
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if candidate.is_dir() and (candidate / "config.json").is_file():
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return str(candidate)
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raise FileNotFoundError(
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f"在 {base} 下未找到 VoxCPM 模型（需要包含 config.json 的子目录，"
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f"如 openbmb__VoxCPM1.5/、VoxCPM1__5/ 等）"
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)
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def _build_sse(data: dict) -> str:
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return f"data: {json.dumps(data, ensure_ascii=False)}\n\n"
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def _stream_audio_events(text: str, request_id: str, model_path: str):
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"""生成 SSE 音频流事件（同步，在独立线程中运行）。"""
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import numpy as np
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try:
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model, sample_rate = _get_model(model_path)
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except Exception as e:
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yield _build_sse({"type": "audio.error", "request_id": request_id, "message": str(e)})
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return
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# 开始
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yield _build_sse({
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"type": "audio.start",
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"request_id": request_id,
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"sample_rate": sample_rate,
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"audio_format": "pcm_f32le",
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})
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chunk_index = 0
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total_samples = 0
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# 获取模型锁（前一请求已被 cancel_current_and_set 取消，锁应已释放）
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# 短超时 + 重试，避免用户等待
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for attempt in range(3):
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if _model_lock.acquire(timeout=3):
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break
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if attempt < 2:
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print(f"[VoxCPM TTS] 等待模型锁释放... (尝试 {attempt + 1}/3)")
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else:
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yield _build_sse({"type": "audio.error", "request_id": request_id,
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"message": "等待模型超时，请重试"})
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return
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try:
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gen = model.generate_streaming(
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text=text,
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prompt_wav_path=DEFAULT_PROMPT_WAV or None,
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prompt_text=DEFAULT_PROMPT_TEXT or None,
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cfg_value=DEFAULT_CFG_VALUE,
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inference_timesteps=DEFAULT_INFERENCE_STEPS,
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retry_badcase=False,
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)
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for audio_chunk in gen:
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if is_cancelled(request_id):
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yield _build_sse({"type": "audio.cancelled", "request_id": request_id})
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return
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arr = np.asarray(audio_chunk, dtype=np.float32).ravel()
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pcm_bytes = np.ascontiguousarray(arr, dtype=np.float32).tobytes()
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num_samples = arr.size
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total_samples += num_samples
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b64_data = base64.b64encode(pcm_bytes).decode("ascii")
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yield _build_sse({
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"type": "audio.chunk",
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"request_id": request_id,
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"index": chunk_index,
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"num_samples": num_samples,
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"sample_rate": sample_rate,
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"data": b64_data,
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})
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chunk_index += 1
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finally:
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_model_lock.release()
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yield _build_sse({
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"type": "audio.done",
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"request_id": request_id,
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"total_samples": total_samples,
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"interrupted": False,
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})
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# ======================== FastAPI ========================
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from fastapi import FastAPI, Request
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from fastapi.responses import StreamingResponse
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@asynccontextmanager
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async def lifespan(app: FastAPI):
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mp = _model_args.get("model_path", DEFAULT_MODEL_PATH)
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print(f"[VoxCPM TTS] 服务启动中，模型路径: {mp}")
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print(f"[VoxCPM TTS] 调用方式: POST /stream_tts body: {{'text': '...', 'request_id': '...'}}")
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# 启动时预加载模型（避免首次请求等待）
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try:
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_get_model(mp)
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except Exception as e:
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print(f"[VoxCPM TTS] 模型预加载失败: {e}")
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yield
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print("[VoxCPM TTS] 服务关闭")
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app = FastAPI(title="VoxCPM Streaming TTS", lifespan=lifespan)
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@app.post("/stream_tts")
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async def stream_tts(request: Request):
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"""流式 TTS 端点：接收文本，SSE 流式返回 PCM f32le 音频块。"""
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try:
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body = await request.json()
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except Exception:
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form = await request.form()
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body = dict(form)
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text = (body.get("text") or "").strip()
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request_id = body.get("request_id") or f"tts-{int(time.time() * 1000)}"
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if not text:
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return StreamingResponse(
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iter([_build_sse({"type": "audio.error", "request_id": request_id, "message": "文本为空"})]),
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media_type="text/event-stream",
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)
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# 新请求到达：自动取消当前活跃的旧请求
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cancel_current_and_set(request_id)
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return StreamingResponse(
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_stream_audio_events(text, request_id, _model_args.get("model_path", DEFAULT_MODEL_PATH)),
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media_type="text/event-stream",
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headers={
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"Cache-Control": "no-cache",
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"Connection": "keep-alive",
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"X-Accel-Buffering": "no",
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},
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)
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@app.post("/cancel_tts")
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async def cancel_tts(request: Request):
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"""取消指定 request_id 的 TTS 合成。"""
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try:
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body = await request.json()
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except Exception:
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form = await request.form()
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body = dict(form)
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request_id = body.get("request_id", "")
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if request_id:
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set_cancel(request_id)
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return {"status": "cancelled", "request_id": request_id}
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return {"status": "error", "message": "缺少 request_id"}
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@app.get("/health")
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async def health():
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return {"status": "ok"}
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# ======================== 启动入口 ========================
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_model_args: dict = {}
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if __name__ == "__main__":
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parser = argparse.ArgumentParser(description="VoxCPM Streaming TTS Server")
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parser.add_argument("--port", type=int, default=DEFAULT_PORT, help=f"服务端口（默认 {DEFAULT_PORT}）")
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parser.add_argument("--model-path", type=str, default=DEFAULT_MODEL_PATH, help="VoxCPM 模型目录")
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args = parser.parse_args()
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_model_args["model_path"] = args.model_path
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import uvicorn
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uvicorn.run(app, host="0.0.0.0", port=args.port)
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