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- 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.AudioProcessorObject import AudioProcessor
- from Object.WsParam.WsParamRecognizeObject import WsParamRecognize
- from Object.WsParam.WsParamSynthesizeObject import WsParamSynthesize
- from django.http import FileResponse
- 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):
- app_id = "fcff8f4b"
- api_key = "037571e7285e64e8dc321fa5b937fea2"
- api_secret = "ZTU3NWMyNTI1MTI4NTU5ZGUxMDZhNmQ5"
- gpt_url = "wss://spark-api.xf-yun.com/v3.5/chat"
- domain = "generalv3.5"
- try:
- system = request_dict.get('system', None)
- audio = request.FILES.get('audio', None)
- history = request_dict.get('history', None)
- if audio is None:
- return response.json(444)
- save_directory = 'static/demo_files/'
- os.makedirs(save_directory, exist_ok=True)
- original_audio_path = os.path.join(save_directory, audio.name)
- with open(original_audio_path, 'wb') as destination:
- for chunk in audio.chunks():
- destination.write(chunk)
- # 转码
- pcm_audio_path = os.path.splitext(original_audio_path)[0] + '.pcm'
- audio_processor = AudioProcessor()
- audio_processor.convert_audio(original_audio_path, pcm_audio_path)
- # 传入语音 -> 转文字 APPID, APISecret, APIKey, AudioFile
- start = time.time()
- audio_file = pcm_audio_path
- wsParamRecognize = WsParamRecognize(app_id, api_secret, api_key, audio_file)
- query = wsParamRecognize.start()
- end = time.time()
- LOGGER.info(f"********smart_reply语音转文字所需时间为{end - start}秒,内容为{query}********")
- # 删除文件 pcm_audio_path 和 original_audio_path
- os.remove(pcm_audio_path)
- os.remove(original_audio_path)
- # 大语言模型 APPID, APIKey, APISecret, gpt_url, domain, query, history=None, system=None
- start = time.time()
- chat = ChatClient(app_id, api_key, api_secret, 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}********")
- # 文字转音频 APPID, APIKey, APISecret, Text, AudioName="demo"
- start = time.time()
- audio_name = f"{os.path.splitext(audio.name)[0]}_answer"
- wsParamSynthesize = WsParamSynthesize(app_id, api_key, api_secret, answer, audio_name)
- wsParamSynthesize.start()
- answer_audio_path = os.path.splitext(original_audio_path)[0] + '_answer.mp3'
- g711a_audio_path = os.path.splitext(answer_audio_path)[0] + '.g711a'
- print(answer_audio_path, g711a_audio_path)
- # 如果有旧文件就删掉
- if os.path.exists(g711a_audio_path):
- os.remove(g711a_audio_path)
- audio_processor.convert_audio(answer_audio_path, g711a_audio_path)
- os.remove(answer_audio_path)
- end = time.time()
- LOGGER.info(f"********smartReply文字转编码所需时间为{end - start}秒********")
- return FileResponse(open(g711a_audio_path, 'rb'), as_attachment=True,
- filename=os.path.basename(g711a_audio_path))
- except Exception as e:
- LOGGER.error('*****WsParamService.smart_reply:errLine:{}, errMsg:{}'
- .format(e.__traceback__.tb_lineno, repr(e)))
- return response.json(500, 'error_line:{}, error_msg:{}'.format(e.__traceback__.tb_lineno, repr(e)))
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