增加分类器和是非器的voting机制
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@ -33,9 +33,10 @@ def retrive_stream():
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logger.info(f'/zhipu/retrive/stream v2: {message}')
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classify_rule = "只有当输入明确表示需要搜索互联网时，才返回web_search"
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classification_result_str = zhipu_alltool_service.func_call_classify(message, additional_desc=classify_rule)
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classification_result_str = zhipu_alltool_service.func_call_classify_with_voting(message, additional_desc=classify_rule)
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print(f'classification_result: {classification_result_str}')
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classification_result = json.loads(classification_result_str)
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# classification_result = json.loads(classification_result_str)
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classification_result = classification_result_str
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if classification_result.get('category') == 'web_search':
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logger.info(f'question classify: web_search')
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@ -52,15 +53,15 @@ def retrive_stream():
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logger.info(f'question classify: retrive_knowledge')
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message = message.replace("我", "我（徐春峰）")
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ask_for_project = zhipu_alltool_service.func_call_yes_or_no(message, "输入问题是否在查询负责的项目信息")
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ask_for_project = json.loads(ask_for_project)
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ask_for_project = zhipu_alltool_service.func_call_yes_or_no_with_voting(message, "输入问题是否在查询负责的项目信息")
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# ask_for_project = json.loads(ask_for_project)
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if ask_for_project.get('answer') == 'yes':
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message += " 用markdown表格形式输出，输出字段:客户名称， 商机名称， Sales stage, 预估 ACV, 预计签单时间"
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message += " ，用markdown表格形式输出，输出字段:客户名称， 商机名称， Sales stage, 预估 ACV, 预计签单时间"
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else:
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ask_for_project = zhipu_alltool_service.func_call_yes_or_no(message, "输入问题是否在询问项目的销售阶段或销售信息")
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ask_for_project = json.loads(ask_for_project)
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ask_for_project = zhipu_alltool_service.func_call_yes_or_no_with_voting(message, "输入问题是否在询问项目的销售阶段或销售信息")
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# ask_for_project = json.loads(ask_for_project)
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if ask_for_project.get('answer') == 'yes':
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message += " 用markdown表格形式输出，输出字段:客户名称， 商机名称， Sales stage, 预测类型，Timing 风险， 预估 ACV, 预计签单时间"
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message += " ，用markdown表格形式输出，输出字段:客户名称， 商机名称， Sales stage, 预测类型，Timing 风险， 预估 ACV, 预计签单时间"
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def event_stream_retrive():
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@ -148,9 +149,10 @@ def analysis_stream():
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intent_categories =["analyze_sales","provide_sales_update_info"]
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classification_result_str = zhipu_alltool_service.func_call_classify(message, intent_categories)
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classification_result_str = zhipu_alltool_service.func_call_classify_with_voting(message, intent_categories)
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print(f'classification_result: {classification_result_str}')
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classification_result = json.loads(classification_result_str)
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classification_result = classification_result_str
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# classification_result = json.loads(classification_result_str)
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additional_business_info = ""
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@ -160,9 +162,9 @@ def analysis_stream():
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pass
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elif classification_result.get('category') == 'provide_sales_update_info':
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logger.info(f'question classify: provide_sales_update_info')
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contain_project_info = zhipu_alltool_service.func_call_yes_or_no(message, "是否包含项目信息")
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contain_project_info = zhipu_alltool_service.func_call_yes_or_no_with_voting(message, "是否包含项目信息")
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logger.info(f'contain_project_info: {contain_project_info}')
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contain_project_info = json.loads(contain_project_info)
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# contain_project_info = json.loads(contain_project_info)
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if contain_project_info.get('answer') == 'yes':
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additional_business_info = message
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else:
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@ -1,6 +1,8 @@
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import logging
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import time
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import json
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from zhipuai import ZhipuAI
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from collections import Counter
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logger = logging.getLogger(__name__)
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@ -10,9 +12,36 @@ class ZhipuAlltoolService:
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self.app_secret_key = "d54f764a1d67c17d857bd3983b772016.GRjowY0fyiMNurLc"
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logger.info("ZhipuAlltoolService initialized with model: %s", self.model_name)
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def func_call_classify(self, message, categories:list=None, additional_desc = None):
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def func_call_classify_with_voting(self, message, categories:list=None, additional_desc=None):
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logger.info("Starting func_call_classify_with_voting call")
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models = ["glm-4-plus", "glm-4-air", "glm-4-plus"]
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votes = []
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for model in models:
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try:
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result = self.func_call_classify(message, categories, additional_desc, model_name=model)
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category = json.loads(result).get('category')
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# category = result.get('category')
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if category:
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votes.append(category)
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except Exception as e:
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logger.error(f"Error in func_call_classify with model {model}: {str(e)}")
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if not votes:
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raise Exception("All classification attempts failed")
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most_common = Counter(votes).most_common(1)
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final_category = most_common[0][0]
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logger.info(f"Voting results: {votes}, Final category: {final_category}")
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return {"category": final_category}
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def func_call_classify(self, message, categories:list=None, additional_desc = None, model_name=None):
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logger.info("Starting func_call_classify call")
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start_time = time.time()
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default_model_name = "glm-4-flash"
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if model_name is None:
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model_name = default_model_name
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default_categories = ["web_search", "retrive_knowledge", "generate_report", "update_report", "clear_report"]
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categories = categories if categories else default_categories
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client = ZhipuAI(api_key=self.app_secret_key)
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@ -44,7 +73,7 @@ class ZhipuAlltoolService:
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]
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try:
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response = client.chat.completions.create(
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model="glm-4-flash", # 填写需要调用的模型名称
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model=model_name, # 填写需要调用的模型名称
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messages= messages,
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tools= tools,
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tool_choice="auto"
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@ -55,9 +84,34 @@ class ZhipuAlltoolService:
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logger.error("Error in web_search call: %s", str(e))
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raise e
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def func_call_yes_or_no(self, message, question):
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logger.info("Starting func_call_yes_or_no call")
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def func_call_yes_or_no_with_voting(self, message, question):
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logger.info("Starting func_call_yes_or_no_with_voting call")
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models = ["glm-4-plus", "glm-4-air", "glm-4-plus"]
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votes = []
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for model in models:
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try:
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result = self.func_call_yes_or_no(message, question, model_name=model)
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answer =json.loads(result).get('answer')
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if answer:
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votes.append(answer.lower())
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except Exception as e:
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logger.error(f"Error in func_call_yes_or_no with model {model}: {str(e)}")
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if not votes:
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raise Exception("All yes/no classification attempts failed")
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most_common = Counter(votes).most_common(1)
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final_answer = most_common[0][0]
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logger.info(f"Voting results: {votes}, Final answer: {final_answer}")
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return {"answer": final_answer}
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def func_call_yes_or_no(self, message, question, model_name=None):
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logger.info("Starting func_call_yes_or_no call")
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default_model_name = "glm-4-flash"
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if model_name is None:
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model_name = default_model_name
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client = ZhipuAI(api_key=self.app_secret_key)
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tools = [
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{
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@ -86,7 +140,7 @@ class ZhipuAlltoolService:
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]
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try:
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response = client.chat.completions.create(
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model="glm-4-flash", # 填写需要调用的模型名称
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model=model_name, # 填写需要调用的模型名称
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messages= messages,
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tools= tools,
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tool_choice="auto"
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@ -131,4 +185,4 @@ class ZhipuAlltoolService:
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yield chunk.choices[0].delta.content
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except Exception as e:
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logger.error("Error in web_search_sse call: %s", str(e))
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raise e
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raise e
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