68 lines
2.3 KiB
Python
68 lines
2.3 KiB
Python
import base64
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import json
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import os
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import tempfile
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from fastapi import APIRouter, WebSocket, WebSocketDisconnect
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from .agent_service import AvatarAgentService
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from .speech import SpeechService
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from .ws_messages import send_audio_message, send_text_message
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router = APIRouter()
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speech_service = SpeechService()
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agent_service = AvatarAgentService()
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def _save_audio_to_temp_file(audio_b64: str) -> str:
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temp_file = tempfile.NamedTemporaryFile(delete=False, suffix=".webm")
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try:
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temp_file.write(base64.b64decode(audio_b64))
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return temp_file.name
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finally:
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temp_file.close()
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@router.websocket("/ws")
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async def websocket_endpoint(websocket: WebSocket) -> None:
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await websocket.accept()
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print("✅ WebSocket 连接成功！准备就绪。")
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try:
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while True:
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message_text = await websocket.receive_text()
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data = json.loads(message_text)
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if data.get("type") != "user_input":
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continue
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audio_b64 = data["audio"].split(",")[-1]
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image_b64 = data["image"].split(",")[-1]
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audio_path = _save_audio_to_temp_file(audio_b64)
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try:
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await send_text_message(websocket, "<i>[👂 正在辨识语音...]</i><br>")
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user_text = speech_service.transcribe(audio_path)
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finally:
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if os.path.exists(audio_path):
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os.remove(audio_path)
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if not user_text.strip():
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await send_text_message(websocket, "<i>[没听清你说什么...]</i><br>")
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continue
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await send_text_message(websocket, f"<b>你说：</b>{user_text}<br>")
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await send_text_message(websocket, "<i>[🧠 正在看图思考...]</i><br>")
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ai_response = await agent_service.reply(user_text, image_b64)
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await send_text_message(websocket, f"<b>AI主播：</b>{ai_response}<br><br>")
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await send_text_message(websocket, "<i>[🗣️ 正在生成语音...]</i><br>")
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audio_data_url = await speech_service.synthesize_audio_data_url(ai_response)
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await send_audio_message(websocket, audio_data_url)
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except WebSocketDisconnect:
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print("❌ 前端页面已关闭或断开连接")
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except Exception as exc:
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print(f"⚠️ 发生错误: {exc}")
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