import logging import time from zhipuai import ZhipuAI from app.services.ai_service_interface import AIServiceInterface from app.utils.prompt_repository import PromptRepository logger = logging.getLogger(__name__) class ZhipuService(AIServiceInterface): def __init__(self): self.model_name = "glm-4" self.app_secret_key = "d54f764a1d67c17d857bd3983b772016.GRjowY0fyiMNurLc" self.client = ZhipuAI(api_key=self.app_secret_key) logger.info("ZhipuService initialized with model: %s", self.model_name) def generate_response(self, prompt): logger.info("Starting generate_response call") start_time = time.time() try: response = self.client.chat.completions.create( model=self.model_name, messages=[ {"role": "user", "content": prompt}, ], stream=False, temperature=0.01, top_p=0.1, ) result = response.choices[0].message.content end_time = time.time() logger.info("generate_response call completed in %.2f seconds", end_time - start_time) return result except Exception as e: logger.error("Error in generate_response: %s", str(e)) raise def generate_response_sse(self, prompt): logger.info("Starting generate_response_sse call") start_time = time.time() try: response = self.client.chat.completions.create( model=self.model_name, messages=[ {"role": "user", "content": prompt}, ], stream=True, temperature=0.01, top_p=0.1, ) for chunk in response: yield chunk.choices[0].delta.content end_time = time.time() logger.info("generate_response_sse call completed in %.2f seconds", end_time - start_time) except Exception as e: logger.error("Error in generate_response_sse: %s", str(e)) raise def retrive(self, message, knowledge_id, prompt_template): logger.info("Starting retrive call with knowledge_id: %s", knowledge_id) start_time = time.time() default_prompt = "从文档\n\"\"\"\n{{knowledge}}\n\"\"\"\n中找问题\n\"\"\"\n{{question}}\n\"\"\"\n的答案,找到答案就仅使用文档语句回答问题,找不到答案就用自身知识回答并且告诉用户该信息不是来自文档。\n不要复述问题,直接开始回答。" if prompt_template is None or prompt_template == "": prompt_template = default_prompt try: response = self.client.chat.completions.create( model="glm-4", messages=[ {"role": "user", "content": message}, ], tools=[ { "type": "retrieval", "retrieval": { "knowledge_id": knowledge_id, "prompt_template": prompt_template } } ], stream=False, temperature=0.01, top_p=0.1, ) result = response.choices[0].message.content end_time = time.time() logger.info("retrive call completed in %.2f seconds", end_time - start_time) return result except Exception as e: logger.error("Error in retrive: %s", str(e)) raise def retrive_sse(self, message, knowledge_id, prompt_template=None,system_prompt=None): logger.info("Starting retrive_sse call with knowledge_id: %s, message:%s", knowledge_id, message) start_time = time.time() default_prompt = "从文档\n\"\"\"\n{{knowledge}}\n\"\"\"\n中找问题\n\"\"\"\n{{question}}\n\"\"\"\n的答案,找到答案就仅使用文档语句回答问题,找不到答案就告诉用户知识库中没有该信息。\n不要复述问题,直接开始回答。" messages = [{"role": "user", "content": message}] # if system_prompt != None: # messages.append({"role": "system", "content": system_prompt}) if prompt_template is None or prompt_template == "": prompt_template = default_prompt try: response = self.client.chat.completions.create( model="glm-4", messages=messages, tools=[ { "type": "retrieval", "retrieval": { "knowledge_id": knowledge_id, "prompt_template": prompt_template } } ], stream=True, temperature=0.01, top_p=0.1, ) for chunk in response: yield chunk.choices[0].delta.content end_time = time.time() logger.info("retrive_sse call completed in %.2f seconds", end_time - start_time) except Exception as e: logger.error("Error in retrive_sse: %s", str(e)) raise def check_report_missing_info(self, message): logger.info("Starting check_report_missing_info call") #1. 日志模版 prompt_report_template = PromptRepository().get_prompt("report_template") prompt_report_missing_check = f"""{prompt_report_template} 请检查以下日志信息是否完整,如果信息缺失则提示要求用户需要补充的信息要点,如果信息完整请直接返回"上述日志信息为全部信息"。日志信息如下:\n\"\"\"\n{message}\n\"\"\"\n""" try: response = self.client.chat.completions.create( model="glm-4-flash", messages=[ {"role": "user", "content": prompt_report_missing_check}, ], stream=True, temperature=0.01, top_p=0.1, ) for chunk in response: yield chunk.choices[0].delta.content end_time = time.time() logger.info("check_report_missing_info call completed in %.2f seconds", end_time - start_time) except Exception as e: logger.error("Error in check_report_missing_info: %s", str(e)) raise