可以写一个高并发的start.py吗

[Rosemajor]

`
import concurrent.futures
import logging
import re
import threading
import sys
import torch
from flask import Flask, request, render_template, jsonify, send_from_directory
import os
from gevent.pywsgi import WSGIServer, WSGIHandler, LoggingLogAdapter
from logging.handlers import RotatingFileHandler
import warnings
from waitress import serve
warnings.filterwarnings('ignore')
import stslib
from stslib import cfg, tool
from stslib.cfg import ROOT_DIR
from faster_whisper import WhisperModel

app = Flask(name, static_folder=os.path.join(ROOT_DIR, 'static'), static_url_path='/static',
template_folder=os.path.join(ROOT_DIR, 'templates'))

配置线程池

executor = concurrent.futures.ThreadPoolExecutor(max_workers=10) # 根据服务器配置调整 max_workers
class CustomRequestHandler(WSGIHandler):
def log_request(self):
pass

def process_audio_task(audio_file, model, language, response_format):
try:
noextname, ext = os.path.splitext(audio_file.filename)
ext = ext.lower()
wav_file = os.path.join(cfg.TMP_DIR, f'{noextname}.wav')

    if not os.path.exists(wav_file) or os.path.getsize(wav_file) == 0:
        if ext in ['.mp4', '.mov', '.avi', '.mkv', '.mpeg', '.mp3', '.flac']:
            video_file = os.path.join(cfg.TMP_DIR, f'{noextname}{ext}')
            audio_file.save(video_file)
            params = ['-i', video_file]
            if ext not in ['.mp3', '.flac']:
                params.append('-vn')
            params.append(wav_file)
            rs = tool.runffmpeg(params)
            if rs != 'ok':
                return {"code": 1, "msg": rs}
        elif ext == '.wav':
            audio_file.save(wav_file)
        else:
            return {"code": 1, "msg": f"{cfg.transobj['lang3']} {ext}"}

    sets = cfg.parse_ini()

    try:
        model_instance = WhisperModel(
            model,
            device=sets.get('devtype'),
            compute_type=sets.get('cuda_com_type'),
            download_root=cfg.ROOT_DIR + "/models",
            local_files_only=False if model.find('/') > 0 else True
        )
    except Exception as e:
        err = f'从huggingface.co下载模型 {model} 失败，请检查网络连接' if model.find('/') > 0 else ''
        return {"code": 1, "msg": f"{err} {e}"}

    segments, info = model_instance.transcribe(
        wav_file,
        beam_size=sets.get('beam_size'),
        best_of=sets.get('best_of'),
        temperature=0 if sets.get('temperature') == 0 else [0.0, 0.2, 0.4, 0.6, 0.8, 1.0],
        condition_on_previous_text=sets.get('condition_on_previous_text'),
        vad_filter=sets.get('vad'),
        vad_parameters=dict(min_silence_duration_ms=300, max_speech_duration_s=10.5),
        language=language if language != 'auto' else None,
        initial_prompt=sets.get('initial_prompt_zh') if language == 'zh' else None
    )

    raw_subtitles = []
    for segment in segments:
        start = int(segment.start * 1000)
        end = int(segment.end * 1000)
        startTime = tool.ms_to_time_string(ms=start)
        endTime = tool.ms_to_time_string(ms=end)
        text = segment.text.strip().replace(''', "'")
        text = re.sub(r'&#\d+;', '', text)

        if not text or re.match(r'^[，。、？‘’“”；：（｛｝【】）:;"\'\s \d`!@#$%^&*()_+=.,?/\\-]*$', text) or len(text) <= 1:
            continue

        if response_format == 'json':
            raw_subtitles.append(
                {"line": len(raw_subtitles) + 1, "start_time": startTime, "end_time": endTime, "text": text})
        elif response_format == 'text':
            raw_subtitles.append(text)
        else:
            raw_subtitles.append(f'{len(raw_subtitles) + 1}\n{startTime} --> {endTime}\n{text}\n')

    if response_format != 'json':
        raw_subtitles = "\n".join(raw_subtitles)

    return {"code": 0, "msg": 'ok', "data": raw_subtitles}
except Exception as e:
    app.logger.error(f'[api]error: {e}')
    return {'code': 2, 'msg': str(e)}

def _is_model_exists(model):
if model.find('/')>0:
return True
if not model.startswith('distil') and not os.path.exists(os.path.join(cfg.MODEL_DIR, f'models--Systran--faster-whisper-{model}/snapshots/')):
return False
if model.startswith('distil') and not os.path.exists(os.path.join(cfg.MODEL_DIR, f'models--Systran--faster-{model}/snapshots/')):
return False

return True

@app.route('/api', methods=['GET', 'POST'])
def api():
try:
# 获取上传的文件和表单数据
audio_file = request.files['file']
model = request.form.get("model")
language = request.form.get("language")
response_format = request.form.get("response_format", 'srt')

    # 检查模型是否存在
    if _is_model_exists(model) is not True:
        return jsonify({"code": 1, "msg": f"{model} {cfg.transobj['lang4']}"})
    # 提交任务到线程池，异步处理
    future = executor.submit(process_audio_task, audio_file, model, language, response_format)
    result = future.result()  # 同步等待结果
    return jsonify(result)

except Exception as e:
    app.logger.error(f'[api]error: {e}')
    return jsonify({'code': 2, 'msg': str(e)})

if name == 'main':
# 其余代码保持不变
http_server = None
try:
threading.Thread(target=tool.checkupdate).start()
try:
if cfg.devtype == 'cpu':
print(
'\n如果设备使用英伟达显卡并且CUDA环境已正确安装，可修改set.ini中\ndevtype=cpu 为 devtype=cuda, 然后重新启动以加快识别速度\n')
host = cfg.web_address.split(':')
http_server = WSGIServer((host[0], int(host[1])), app, handler_class=CustomRequestHandler)
threading.Thread(target=tool.openweb, args=(cfg.web_address,)).start()
http_server.serve_forever()
finally:
if http_server:
http_server.stop()
except Exception as e:
if http_server:
http_server.stop()
app.logger.error(f"[app]start error:{str(e)}")
print("error:" + str(e))
`
上面是我想改成多进程的，但是失败了，还是单线程的，作者大大可以加一个并发处理的嘛，并发量可以根据自己电脑配置改动