code: #!/usr/bin/env python
  # -*- coding: utf-8 -*-
  # @Time    : 2023/2/24 16:23
  # @Author  : Jack
  # @File    : main.py
  # @Software: PyCharm
  import asyncio
  import logging
  import socket
  import sys
  
  import consul
  import langchain
  import os
  import grpc
  from langchain import PromptTemplate, LLMChain
  from langchain.chat_models import ChatOpenAI
  from proto import chatgpt_pb2_grpc, chatgpt_pb2
  
  from callback import StreamingLLMCallbackHandler
  
  default_port = 8099
  
  
  def get_host_ip():
      """
      查询本机ip地址
      :return: ip
      """
      s = socket.socket(socket.AF_INET, socket.SOCK_DGRAM)
      try:
          s.connect(('8.8.8.8', 80))
          ip = s.getsockname()[0]
      finally:
          s.close()
  
      return ip
  
  
  def register_service(consul_addr: str, consul_port: int, srv_port: int) -> consul.Consul:
      local_ip = get_host_ip()
      client = consul.Consul(host=consul_addr, port=consul_port, verify=False)
      client.agent.service.register(
          name="chatgpt",
          address=local_ip,
          port=srv_port,
          service_id=f"chatgpt-{local_ip}",
          timeout=10
      )
      return client
  
  
  def init_chatgpt() -> langchain.LLMChain:
      llm = ChatOpenAI(streaming=True, verbose=True, temperature=0.6)
      # Get prompt template
      template = ("""Assistant is a large language model trained by OpenAI.
      Assistant is designed to be able to assist with a wide range of tasks, from answering simple questions to providing in-depth explanations and discussions on a wide range of topics. As a language model, Assistant is able to generate human-like text based on the input it receives, allowing it to engage in natural-sounding conversations and provide responses that are coherent and relevant to the topic at hand.
      Assistant is constantly learning and improving, and its capabilities are constantly evolving. It is able to process and understand large amounts of text, and can use this knowledge to provide accurate and informative responses to a wide range of questions. Additionally, Assistant is able to generate its own text based on the input it receives, allowing it to engage in discussions and provide explanations and descriptions on a wide range of topics.
      Overall, Assistant is a powerful tool that can help with a wide range of tasks and provide valuable insights and information on a wide range of topics. Whether you need help with a specific question or just want to have a conversation about a particular topic, Assistant is here to assist.
          {human_input}
          Assistant:""")
      chat_prompt = PromptTemplate(
          input_variables=["human_input"],
          template=template
      )
      # Construct Chain
      chain = LLMChain(llm=llm, prompt=chat_prompt, callbacks=[], verbose=True)
      return chain
  
  # Fill your openai api key.
  os.environ["OPENAI_API_KEY"] = ""
  
  
  class ChatgptService(chatgpt_pb2_grpc.ChatgptServicer):
      def __init__(self, chain):
          self.chain = chain
  
      async def Send(self, request: chatgpt_pb2.Message, context: grpc.aio.ServicerContext):
          stream_handler = StreamingLLMCallbackHandler(context, chatgpt_pb2)
          await self.chain.acall(
              {"human_input": request.content},
              callbacks=[stream_handler]
          )
  
  
  async def serve() -> None:
      """
      Run grpc service
      """
      server = grpc.aio.server()
      chain = init_chatgpt()
      chatgpt_pb2_grpc.add_ChatgptServicer_to_server(ChatgptService(chain), server=server)
      server.add_insecure_port(f"[::]:{default_port}")
      await server.start()
      print(f"Server started, listening on {default_port}")
      await server.wait_for_termination()
  
  
  if __name__ == '__main__':
      logging.basicConfig(level=logging.INFO)
      # Fill your consul service address and port.
      client = register_service("127.0.0.1", 8500, default_port)
      try:
          asyncio.get_event_loop().run_until_complete(serve())
      except KeyboardInterrupt:
          client.agent.service.deregister(f"chatgpt-{get_host_ip()}")
          print("\nExiting...")
          sys.exit()
  
apis: langchain.LLMChain langchain.chat_models.ChatOpenAI langchain.PromptTemplate
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