ASJServer/Controller/SmartReplyController.py

import json
import os
from Ansjer.config import LOGGER
from Object.ResponseObject import ResponseObject
from django.views import View
import time
from Object.WsParam.AIChatObject import ChatClient
from Object.WsParam.WsParamRecognizeObject import WsParamRecognize
from Object.WsParam.WsParamSynthesizeObject import WsParamSynthesize


class WsParamService(View):
    def get(self, request, *args, **kwargs):
        request.encoding = 'utf-8'
        operation = kwargs.get('operation')
        request_dict = request.GET
        return self.validation(request, request_dict, operation)

    def post(self, request, *args, **kwargs):
        request.encoding = 'utf-8'
        operation = kwargs.get('operation')
        request_dict = request.POST
        return self.validation(request, request_dict, operation)

    def validation(self, request, request_dict, operation):
        language = request_dict.get('language', 'en')
        response = ResponseObject(language)
        if operation == 'smartReply':
            return self.smart_reply(request, request_dict, response)
        else:
            return response.json(414)

    def smart_reply(self, request, request_dict, response):
        try:
            audio = request.FILES.get('audio', None)
            system = request_dict.get('system', None)
            history = request_dict.get('history', None)
            audio_type = request_dict.get('audioType', 'pcm')
            save_directory = 'static/demo_files/'
            if not os.path.exists(save_directory):
                os.makedirs(save_directory)

            start = time.time()
            audio_path = os.path.join(save_directory, audio.name)
            with open(audio_path, 'wb') as destination:
                for chunk in audio.chunks():
                    destination.write(chunk)
            end = time.time()
            LOGGER.info(f"********smartReply保存文件所需时间为{end-start}秒********")
            APPID = "fcff8f4b"
            APIKey = "037571e7285e64e8dc321fa5b937fea2"
            APISecret = "ZTU3NWMyNTI1MTI4NTU5ZGUxMDZhNmQ5"
            gpt_url = 'wss://spark-api.xf-yun.com/v3.5/chat'
            domain = 'generalv3.5'
            AudioFile = audio_path

            start = time.time()
            # 传入语音 -> 转文字 APPID, APISecret, APIKey
            wsParamRecognize = WsParamRecognize(APPID, APISecret, APIKey, AudioFile)
            query = wsParamRecognize.start()
            end = time.time()
            LOGGER.info(f"********smartReply语音转文字所需时间为{end - start}秒,内容为{query}********")

            start = time.time()
            # 大语言模型 APPID, APIKey, APISecret, gpt_url, domain, query, history=None, system=None
            chat = ChatClient(APPID, APIKey, APISecret, gpt_url, domain, query, history, system)
            answer = chat.start()
            end = time.time()
            LOGGER.info(f"********smartReplyAI回复所需时间为{end - start}秒,内容为{answer}********")

            start = time.time()
            # 文字转编码 self, APPID, APIKey, APISecret, Text, AudioType = "pcm"
            wsParamSynthesize = WsParamSynthesize(APPID, APIKey, APISecret, answer, audio_type)
            answer_base = wsParamSynthesize.start()
            end = time.time()
            LOGGER.info(f"********文字转编码所需时间为{end - start}秒********")
            return response.json(0, answer_base)
        except Exception as e:
            LOGGER.error('*****WsParamService.smart_reply:errLine:{}, errMsg:{}'
                         .format(e.__traceback__.tb_lineno, repr(e)))