254 lines
9.2 KiB
Python
254 lines
9.2 KiB
Python
import logging
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import os
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import uuid
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import time
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import asyncio # 添加此行
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from fastapi import APIRouter, HTTPException, BackgroundTasks, Query, UploadFile, File, Form
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from pydantic import BaseModel
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from typing import Optional
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import tempfile
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from starlette.websockets import WebSocket
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from Util.ObsUtil import ObsUploader
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from Config.Config import OBS_BUCKET, OBS_SERVER, XF_APPID, XF_APISECRET, XF_APIKEY
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from fastapi.responses import StreamingResponse
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import requests
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# 导入讯飞语音评测类
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from KeDaXunFei.XunFeiAudioEvaluator import XunFeiAudioEvaluator
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# 配置日志
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logger = logging.getLogger(__name__)
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router = APIRouter(prefix="/api/xunFei", tags=["讯飞"])
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# 请求模型
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class AudioEvaluationRequest(BaseModel):
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language: str = "chinese" # chinese 或 english
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text: str # 评测文本内容
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group: Optional[str] = "adult" # 群体：adult, youth, pupil
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check_type: Optional[str] = "common" # 检错严格程度：easy, common, hard
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grade: Optional[str] = "middle" # 学段：junior, middle, senior
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# 响应模型
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class AudioEvaluationResponse(BaseModel):
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evaluation_id: str
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status: str
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results: Optional[dict] = None
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evaluation_time: Optional[float] = None
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error_message: Optional[str] = None
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# 科大讯飞API配置（需要根据实际情况配置）
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XUNFEI_CONFIG = {
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"appid": XF_APPID,
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# 修复参数名颠倒问题
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"api_key": XF_APIKEY,
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"api_secret": XF_APISECRET
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}
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@router.post("/evaluate-audio", response_model=AudioEvaluationResponse)
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async def evaluate_audio( # 添加async关键字
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background_tasks: BackgroundTasks,
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language: str = Form(..., description="语言类型: chinese/english"),
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group: str = Form("adult", description="群体类型: adult, youth, pupil"),
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check_type: str = Form("common", description="检错严格程度: easy, common, hard"),
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grade: str = Form("middle", description="学段: junior, middle, senior"),
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audio_file: UploadFile = File(...)):
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"""
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语音评测接口 - 支持中文和英文篇章朗读判分
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"""
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try:
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# 验证语言参数
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if language not in ["chinese", "english"]:
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raise HTTPException(status_code=400, detail="language参数必须是'chinese'或'english'")
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# 新增参数验证
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if check_type not in ["easy", "common", "hard"]:
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raise HTTPException(status_code=400, detail="check_type参数必须是'easy'、'common'或'hard'")
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if grade not in ["junior", "middle", "senior"]:
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raise HTTPException(status_code=400, detail="grade参数必须是'junior'、'middle'或'senior'")
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# 验证群体参数
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if group not in ["adult", "youth", "pupil"]:
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raise HTTPException(status_code=400, detail="group参数必须是'adult', 'youth'或'pupil'")
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# 创建临时文件保存上传的音频
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# 修改临时文件处理逻辑
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import os
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import uuid
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# 创建持久化保存目录
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output_dir = os.path.join(os.path.dirname(__file__), '../static/audio')
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os.makedirs(output_dir, exist_ok=True)
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# 生成唯一文件名
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temp_audio_path = os.path.join(output_dir, f"eval_audio_{uuid.uuid4()}.wav")
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with open(temp_audio_path, 'wb') as temp_audio:
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# 先读取音频内容
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audio_content = await audio_file.read()
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# 再进行格式转换
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import wave
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with wave.open(temp_audio, 'wb') as wf:
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wf.setnchannels(1)
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wf.setsampwidth(2)
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wf.setframerate(16000)
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wf.writeframes(audio_content)
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# 创建评测器实例
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evaluator = XunFeiAudioEvaluator(
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appid=XUNFEI_CONFIG["appid"],
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# 与AudioEvaluator示例用法保持一致
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api_key=XUNFEI_CONFIG["api_key"],
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api_secret=XUNFEI_CONFIG["api_secret"],
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audio_file=temp_audio_path,
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language=language # 添加语言参数
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)
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# 根据语言设置不同的评测参数
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if language == "chinese":
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# 中文评测配置
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evaluator.business_params = {
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"category": "read_chapter",
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"ent": "cn_vip",
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"group": group,
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"check_type": check_type,
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"grade": grade,
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}
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else:
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# 英文评测配置
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evaluator.business_params = {
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"category": "read_chapter",
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"ent": "en_vip",
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"group": group, # 添加缺失参数
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"check_type": check_type, # 添加缺失参数
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"grade": grade, # 添加缺失参数
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}
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# 运行评测
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from concurrent.futures import ThreadPoolExecutor
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executor = ThreadPoolExecutor(max_workers=4)
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results, eval_time = await asyncio.get_event_loop().run_in_executor(
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executor, evaluator.run_evaluation
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)
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# 清理临时文件 - 注释掉此行以便保留文件
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# os.unlink(temp_audio_path)
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# 生成评测ID
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evaluation_id = str(uuid.uuid4())
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return AudioEvaluationResponse(
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evaluation_id=evaluation_id,
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status="success",
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results=results,
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evaluation_time=eval_time.total_seconds() if eval_time else None
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)
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except Exception as e:
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logger.error(f"语音评测失败: {str(e)}")
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# 确保临时文件被清理
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if 'temp_audio_path' in locals() and os.path.exists(temp_audio_path):
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os.unlink(temp_audio_path)
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return AudioEvaluationResponse(
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evaluation_id=str(uuid.uuid4()),
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status="error",
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error_message=f"评测失败: {str(e)}"
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)
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@router.get("/evaluation-result/{evaluation_id}")
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async def get_evaluation_result(evaluation_id: str):
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"""
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获取评测结果（示例接口，实际需要实现结果存储）
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"""
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# 这里需要实现从数据库或缓存中获取评测结果
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# 目前返回示例数据
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return {
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"evaluation_id": evaluation_id,
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"status": "completed",
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"message": "请实现结果存储逻辑"
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}
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@router.websocket("/xunfei/streaming-evaluate")
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async def streaming_evaluate(websocket: WebSocket):
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await websocket.accept()
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logger.info("讯飞语音评测WebSocket连接已建立")
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# 生成唯一音频文件名
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output_dir = os.path.join(os.path.dirname(__file__), '../static/audio')
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os.makedirs(output_dir, exist_ok=True)
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temp_audio_path = os.path.join(output_dir, f"eval_audio_{uuid.uuid4()}.wav")
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try:
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# 初始化WAV文件
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with wave.open(temp_audio_path, 'wb') as wf:
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wf.setnchannels(1)
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wf.setsampwidth(2)
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wf.setframerate(16000)
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# 持续接收音频流
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while True:
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data = await websocket.receive_bytes()
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if not data: # 结束标记
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break
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wf.writeframes(data)
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# 执行评测（复用现有逻辑）
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evaluator = XunFeiAudioEvaluator(
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appid=XUNFEI_CONFIG["appid"],
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api_key=XUNFEI_CONFIG["api_key"],
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api_secret=XUNFEI_CONFIG["api_secret"],
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audio_file=temp_audio_path,
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language=await websocket.receive_json().get("language", "chinese")
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)
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# 根据语言设置不同的评测参数
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if language == "chinese":
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# 中文评测配置
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evaluator.business_params = {
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"category": "read_chapter",
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"ent": "cn_vip",
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"group": group,
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"check_type": check_type,
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"grade": grade,
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}
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else:
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# 英文评测配置
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evaluator.business_params = {
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"category": "read_chapter",
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"ent": "en_vip",
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"group": group, # 添加缺失参数
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"check_type": check_type, # 添加缺失参数
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"grade": grade, # 添加缺失参数
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}
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# 运行评测
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from concurrent.futures import ThreadPoolExecutor
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executor = ThreadPoolExecutor(max_workers=4)
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results, eval_time = await asyncio.get_event_loop().run_in_executor(
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executor, evaluator.run_evaluation
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)
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# 清理临时文件 - 注释掉此行以便保留文件
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# os.unlink(temp_audio_path)
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# 生成评测ID
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evaluation_id = str(uuid.uuid4())
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return AudioEvaluationResponse(
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evaluation_id=evaluation_id,
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status="success",
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results=results,
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evaluation_time=eval_time.total_seconds() if eval_time else None
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)
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except Exception as e:
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logger.error(f"评测失败: {str(e)}")
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await websocket.send_json({
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"status": "error",
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"message": str(e)
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})
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await websocket.close()
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