79 lines
2.7 KiB
Python
79 lines
2.7 KiB
Python
import json
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import openai
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from colorama import init, Fore
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from loguru import logger
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import json
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from robowaiter.llm_client.tool_register import get_tools, dispatch_tool
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import requests
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import json
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import urllib3
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init(autoreset=True)
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########################################
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# 该文件实现了与大模型的通信以及工具调用
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########################################
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# 忽略https的安全性警告
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urllib3.disable_warnings(urllib3.exceptions.InsecureRequestWarning)
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base_url = "https://45.125.46.134:25344" # 本地部署的地址,或者使用你访问模型的API地址
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def get_response(**kwargs):
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data = kwargs
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response = requests.post(f"{base_url}/v1/chat/completions", json=data, stream=data["stream"], verify=False)
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decoded_line = response.json()
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return decoded_line
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functions = get_tools()
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if __name__ == "__main__":
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question = input("\n顾客：")
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data_memory = [{
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"role": "system",
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"content": "你是RoboWaiter,一个由HPCL团队开发的机器人服务员，你在咖啡厅工作。接受顾客的指令并调用工具函数来完成各种服务任务。",
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},]
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n = 1
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max_retry = 5
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params = dict(model="RoboWaiter",messages=data_memory, stream=False)
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params["functions"] = functions
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while question != 'end':
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user_dict = {"role": "user", "content": question}
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params["messages"].append(user_dict)
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# print(data_memory)
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response = get_response(**params)
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for _ in range(max_retry):
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if response["choices"][0]["message"].get("function_call"):
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function_call = response["choices"][0]["message"]["function_call"]
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logger.info(f"Function Call Response: {function_call}")
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function_args = json.loads(function_call["arguments"])
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tool_response = dispatch_tool(function_call["name"], function_args)
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logger.info(f"Tool Call Response: {tool_response}")
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return_message = response["choices"][0]["message"]
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params["messages"].append(return_message)
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t = {
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"role": "function",
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"name": function_call["name"],
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"content": tool_response, # 调用函数返回结果
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}
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params["messages"].append(t)
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response = get_response(**params)
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else:
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return_message = response["choices"][0]["message"]
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reply = return_message["content"]
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params["messages"].append(return_message)
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logger.info(f"Final Reply: \n{reply}")
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break
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question = input("\n顾客：")
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