138 lines
4.4 KiB
Python
138 lines
4.4 KiB
Python
# main.py
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import asyncio
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import uvicorn
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from fastapi import FastAPI, WebSocket, WebSocketDisconnect
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from starlette.middleware.cors import CORSMiddleware
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# 导入抽离的消息管理模块
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from ws_message_manager import ws_queue_manager, ServerMsgType
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import logging
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from frontend_ws import frontend_websocket_handler
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from asr_client import init_asr_pool, close_asr_pool
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from contextlib import asynccontextmanager
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# 初始化日志配置（全局生效）
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logging.basicConfig(
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level=logging.INFO, # 日志级别：DEBUG/INFO/WARNING/ERROR
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format="%(asctime)s - %(name)s - %(levelname)s - %(message)s", # 日志格式
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handlers=[
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logging.StreamHandler(), # 输出到控制台
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logging.FileHandler("ws_server.log", encoding="utf-8") # 输出到文件（可选）
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]
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)
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# 创建日志实例（后续所有logger调用都用这个实例）
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logger = logging.getLogger(__name__) # __name__ 是当前模块名，便于区分日志来源
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# FastAPI 启动时初始化 ASR 连接池
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@asynccontextmanager
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async def lifespan(app: FastAPI):
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# 启动时执行（原 startup 逻辑）
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print(' FastAPI 启动时初始化 ASR 连接池')
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await init_asr_pool()
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yield # 应用运行中
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# 关闭时执行（可选，比如清理连接池）
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print("应用关闭，开始清理 ASR 连接池...")
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await close_asr_pool()
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# 这里可以添加连接池关闭逻辑（如关闭所有 ASR 连接）
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# 初始化FastAPI应用
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app = FastAPI(
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title="语音交互网关",
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description="整合前端/ASR/大模型/TTS的异步网关服务",
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version="1.0",
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lifespan=lifespan # 绑定生命周期
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)
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# 跨域配置
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app.add_middleware(
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CORSMiddleware,
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allow_origins=["*"],
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allow_credentials=True,
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allow_methods=["*"],
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allow_headers=["*"],
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)
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async def process_audio(websocket: WebSocket, audio_data: bytes):
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"""处理音频数据，生成多类型消息并推送"""
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try:
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# 1. 模拟ASR识别（生成文字）
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text_result = f"识别结果：音频长度 {len(audio_data)} bytes"
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await ws_queue_manager.send_message(websocket, ServerMsgType.TEXT, text_result)
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# 2. 模拟TTS生成语音（二进制数据）
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voice_data = b"xx" # 替换为真实TTS输出
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await ws_queue_manager.send_message(websocket, ServerMsgType.VOICE, voice_data)
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# 3. 模拟数字人动画信息
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animation_data = {
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"action": "mouth_move",
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"speed": 1.2,
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"duration": 1000
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}
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await ws_queue_manager.send_message(websocket, ServerMsgType.ANIMATION, animation_data)
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# 4. 模拟前端动作指令
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action_data = {
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"type": "show_loading",
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"status": False
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}
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await ws_queue_manager.send_message(websocket, ServerMsgType.ACTION, action_data)
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except Exception as e:
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# 推送错误信息
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await ws_queue_manager.send_message(websocket, ServerMsgType.ERROR, str(e))
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@app.websocket("/ws/audio")
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async def websocket_audio(websocket: WebSocket):
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# 完全委托给frontend_websocket_handler处理
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await frontend_websocket_handler(websocket)
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# 前端WebSocket路由
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# @app.websocket("/ws/audio")
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# async def websocket_audio(websocket: WebSocket):
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# # 1. 接受连接并创建专属队列
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# await websocket.accept()
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# await ws_queue_manager.create_queue(websocket)
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#
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# try:
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# # 2. 循环接收前端音频数据
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# while True:
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# # 接收二进制音频数据（前端发送的麦克风数据）
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# audio_data = await websocket.receive_bytes()
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# # 异步处理音频（不阻塞接收）
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# asyncio.create_task(process_audio(websocket, audio_data))
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#
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# except WebSocketDisconnect:
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# logger.info(f"连接 {id(websocket)} 主动断开")
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# except Exception as e:
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# logger.error(f"连接异常: {e}")
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# finally:
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# # 3. 清理队列和协程
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# await ws_queue_manager.close_queue(websocket)
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# 健康检查接口
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@app.get("/health")
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async def health_check():
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return {
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"status": "ok",
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"service": "voice_gateway",
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"active_connections": len(ws_queue_manager.queue_map)
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}
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if __name__ == "__main__":
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uvicorn.run(
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"main:app",
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host="0.0.0.0",
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port=8000,
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reload=True, # 生产环境关闭
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workers=1 # 异步框架单worker足够，多worker需分布式队列
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)
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