更新.gitignore文件以忽略新的数据文件和测试文件，修改对话到工单处理逻辑，添加产品信息解析功能，优化API调用，移除不必要的参数，调整并发处理逻辑。

.gitignore

@@ -5,9 +5,12 @@ __pycache__/
 
 # 忽略数据文件
 data/excel/*
-rag2_0/demo/Test.py
+rag2_0/demo/Test*
+rag2_0/demo/test*
 data/excel/*.xlsx
 rag2_0/demo/ProfessionalTermAnalyzer.py
 data/logs/*
 rag2_0/dify/Test.py
 data/query_logs/*
+data/conversations/*
+data/test*

rag2_0/demo/dialogue_to_workorder.py

@@ -34,30 +34,33 @@ logging.basicConfig(
 logger = logging.getLogger("dialogue_to_workorder")
 
 human_info={
-"1116":["夏剑媛",	"储能"],
+"1116":["夏剑媛",	"新能源"],
-"1201":["曹美芳",	"配网"],
+"1201":["曹美芳",	"配网造价及清单"],
-"1202":["彭珊珊",	"主网"],
+"1202":["彭珊珊",	"主网造价及清单"],
-"1230":["龚青",	"配网"],
+"1230":["龚青",	"配网造价及清单"],
-"1544":["黄婷",	"主网"],
+"1544":["黄婷",	"主网造价及清单"],
-"1546":["严琼辉",	"配网"],
+"1546":["严琼辉",	"配网造价及清单"],
-"1552":["吴园妹",	"主网"],
+"1552":["吴园妹",	"主网造价及清单"],
-"1555":["魏怡璠",	"配网"],
+"1555":["魏怡璠",	"配网造价及清单"],
-"1789":["冷琛",	"主网"],
+"1789":["冷琛",	"主网造价及清单"],
-"2142":["余国庆",	"配网"],
+"2142":["余国庆",	"配网造价及清单"],
-"2144":["卢光辉",	"技改"],
+"2144":["卢光辉",	"技改检修"],
-"2145":["万志星",	"技改"],
+"2145":["万志星",	"技改检修"],
-"2233":["徐雨萍",	"主网"],
+"2233":["徐雨萍",	"主网造价及清单"],
-"2262":["刘雨微",	"主网"],
+"2262":["刘雨微",	"主网造价及清单"],
-"2591":["揭敏",	"主网"],
+"2591":["揭敏",	"主网造价及清单"],
-"3035":["杨玲",	"主网"],
+"3035":["杨玲",	"主网造价及清单"],
-"3416":["杨苏文",	"配网"],
+"3416":["杨苏文",	"配网造价及清单"],
-"3417":["王琴",	"配网"],
+"3417":["王琴",	"配网造价及清单"],
-"439":["赵莉",	"技改"],
+"439":["赵莉",	"技改检修"],
-"8340":["熊磊娇",	"储能"],
+"8340":["熊磊娇",	"新能源"],
-"8442":["胡月",	"配网"],
+"8442":["胡月",	"配网造价及清单"],
-"8443":["杨淑玲",	"主网"],
+"8443":["杨淑玲",	"主网造价及清单"],
-"8555":["胡青艳",	"主网"],
+"8555":["胡青艳",	"主网造价及清单"],
-"8762":["周丽华",	"主网"],
+"8762":["周丽华",	"主网造价及清单"],
+"1553":["郝中华",	"技改检修"],
+"8817":["赵雅馨",	"技改检修"],
+"2590":["李琴",	"技改检修"],
 }
 
 # ================ 模型定义 ================
@@ -65,6 +68,10 @@ class UserQuestionAndSolution(BaseModel):
     user_question: str = Field(description="用户的核心问题")
     solution: str = Field(description="坐席提供的解决方案,解决方案如果存在多个步骤，使用中文分号隔开")
 
+class ProductInfo:
+    product_line:str
+    product_name:str
+
 class UserQuestionAndSolutionList(BaseModel):
     user_question_list: list[UserQuestionAndSolution] = Field(description="客户问题列表")
 
@@ -133,48 +140,112 @@ class DialogueToWorkorder:
         self.is_complaint_parser = PydanticOutputParser(pydantic_object=IsComplaint)
         self.product_name_and_module_name_parser = PydanticOutputParser(pydantic_object=ProductNameAndModuleName)
         self.product_line_parser = PydanticOutputParser(pydantic_object=ProductLine)
-        
         # 初始化LLM模型
-        # self.llm_params = llm_params or {
-        #     "temperature": 0.2,
-        #     "top_p":0.95,
-        #     "model": "deepseek-ai/DeepSeek-R1",
-        #     "api_key": os.getenv("OPENAI_API_KEY"),
-        #     "base_url": os.getenv("OPENAI_API_BASE"),
-        #     "timeout": httpx.Timeout(600.0)
-        # }
-        self.api_key = "25t%Syu6I9yxX2IuTN"
         self.llm_params = llm_params or {
             "temperature": 0.2,
             "top_p":0.95,
-            "model": "deepseek-r1",
+            "model": "deepseek-ai/DeepSeek-R1",
-            "api_key": "25t%Syu6I9yxX2IuTN",
+            "api_key": os.getenv("OPENAI_API_KEY"),
-            "base_url": "http://10.1.0.154:8000/v1",
+            "base_url": os.getenv("OPENAI_API_BASE"),
             "timeout": httpx.Timeout(600.0)
         }
+        # self.llm_params = llm_params or {
+        #     "temperature": 0.2,
+        #     "top_p":0.95,
+        #     "model": "deepseek-r1",
+        #     "api_key": "25t%Syu6I9yxX2IuTN",
+        #     "base_url": "http://10.1.0.154:8000/v1",
+        #     "timeout": httpx.Timeout(600.0)
+        # }
         self.llm = self._get_llm_instance()
     
     def _get_llm_instance(self):
         """获取LLM实例"""
         return OpenAiLLM(**self.llm_params)
 
-    def parse_product_detail_excel(self, file_path):
+    def get_product_info(self, conversation_context:str, skill_group:str)->ProductInfo:
-        """解析产品详情Excel文件"""
+        product_info = ProductInfo()
-        df = pd.read_excel(file_path)
-        product_dict = {}
         
-        for _, row in df.iterrows():
+        # 默认为其他
-            product_line = str(row['产品线']).strip() if pd.notna(row['产品线']) else ''
+        product_info.product_line = "其他"
-            product_name = str(row['产品名称']).strip() if pd.notna(row['产品名称']) else ''
+        product_info.product_name = ""
-            module_name = str(row['模块名称']).strip() if pd.notna(row['模块名称']) else ''
         
-            if product_line not in product_dict:
+        # 主网造价及清单技能组
-                product_dict[product_line] = {}
+        if skill_group == "主网造价及清单":
-            if product_name not in product_dict[product_line]:
+            if "西藏" in conversation_context:
-                product_dict[product_line][product_name] = []
+                product_info.product_line = "博微西藏计价通Z1"
-            product_dict[product_line][product_name].append(module_name)
+                if "建安预算" in conversation_context or "全口径预算" in conversation_context:
+                    product_info.product_name = "施工图预算"
+                elif "招标" in conversation_context or "投标" in conversation_context:
+                    product_info.product_name = "招投标"
+                elif "清单" in conversation_context and "结算" in conversation_context:
+                    product_info.product_name = "清单结算"
+                else:
+                    product_info.product_name = "概预算"
+            elif "造价2016" in conversation_context or "造价2014" in conversation_context or "造价2008" in conversation_context:
+                product_info.product_line = "主网造价系列"
+            elif "清单2016" in conversation_context or "清单2015" in conversation_context:
+                product_info.product_line = "主网清单系列"
+            elif "大结算" in conversation_context or "结算2018" in conversation_context:
+                product_info.product_line = "管理或辅助工具软件"
+                product_info.product_name = "结算应用2018"
+            elif "清标" in conversation_context or "数字化" in conversation_context:
+                product_info.product_line = "管理或辅助工具软件"
+                product_info.product_name = "数字化清标工具"
+            else:
+                product_info.product_line = "博微电力建设计价通软件"
+                if "建安预算" in conversation_context or "全口径预算" in conversation_context:
+                    product_info.product_name = "施工图预算"
+                elif "招标" in conversation_context or "投标" in conversation_context:
+                    product_info.product_name = "招投标"
+                elif any(keyword in conversation_context for keyword in ["清单结算", "基准价", "结算条款", "结算市场价", "结算审核"]):
+                    product_info.product_name = "清单结算"
+                else:
+                    product_info.product_name = "概预算"
         
-        return product_dict
+        # 技改检修技能组
+        elif skill_group == "技改检修":
+            if "技改2015" in conversation_context or "技改2016" in conversation_context:
+                product_info.product_line = "技改检修系列"
+            else:
+                product_info.product_line = "博微技改检修计价通T1软件"
+                if "T1" in conversation_context and "清单" in conversation_context:
+                    product_info.product_name = "清单"
+                else:
+                    product_info.product_name = "概预算"
+        
+        # 配网造价及清单技能组
+        elif skill_group == "配网造价及清单":
+            if "配网2017" in conversation_context or "09配网" in conversation_context or "老配网" in conversation_context:
+                product_info.product_line = "配网系列"
+            else:
+                product_info.product_line = "博微配网计价通D3"
+                if "南网" in conversation_context:
+                    product_info.product_name = "南网版"
+                elif "清单" in conversation_context and "南网" not in conversation_context:
+                    product_info.product_name = "行业清单计价"
+                else:
+                    product_info.product_name = "概预算"
+        
+        # 新能源技能组
+        elif skill_group == "新能源":
+            product_info.product_line = "新能源系列"
+            if "核电" in conversation_context:
+                product_info.product_name = "核电清单2018"
+            elif "光伏" in conversation_context and "2018" in conversation_context:
+                product_info.product_name = "光伏计价2018"
+            elif "储能" in conversation_context:
+                product_info.product_name = "新型储能电站计价通C1"
+            elif "营销" in conversation_context:
+                product_info.product_name = "陕西电力营销计价通M1"
+            elif "新能源" in conversation_context or "光伏清单" in conversation_context or "风电" in conversation_context:
+                product_info.product_name = "新能源计价通N1"
+        
+        # 经济评价及其他技能组
+        elif "经济评价" in conversation_context:
+            product_info.product_line = "经济评价系列"
+        
+        return product_info
 
     def get_workorder_dict(self, rows):
         """从会话行中提取工单基本信息"""
@@ -221,6 +292,13 @@ class DialogueToWorkorder:
             dt = datetime.strptime(create_time_str, "%Y-%m-%d %H:%M:%S")
             workorder_dict["工单编号"] = dt.strftime("%Y%m%d%H%M%S")
         
+        # 获取产品线和产品名称
+        dialogue_str = self.get_dialogue_str(rows)
+        skill_group = workorder_dict.get("处理技能组", "")
+        product_info = self.get_product_info(dialogue_str, skill_group)
+        workorder_dict["产品线"] = product_info.product_line
+        workorder_dict["产品名称"] = product_info.product_name
+
         return workorder_dict
     
     def get_dialogue_str(self, conversation_rows):
@@ -291,7 +369,7 @@ class DialogueToWorkorder:
         output_format = self.user_question_and_solution_parser.get_format_instructions()
         llm_prompt = prompt.format(output_format=output_format, dialogue_str=dialogue_str)
         
-        response = self.llm.invoke(user_prompt=llm_prompt, need_retry=False, api_key=self.api_key)
+        response = self.llm.invoke(user_prompt=llm_prompt, need_retry=False)
         clean_output = re.sub(r'<think>.*?</think>', '', response.content, flags=re.DOTALL)
         try:
             if clean_output.count('user_question') == 1:
@@ -321,75 +399,13 @@ class DialogueToWorkorder:
         except Exception as e:
             output_format = self.user_question_and_solution_list_parser.get_format_instructions()
             llm_prompt = prompt.format(output_format=output_format, dialogue_str=dialogue_str)
-            response = self.llm.invoke(user_prompt=llm_prompt, need_retry=False, api_key=self.api_key)
+            response = self.llm.invoke(user_prompt=llm_prompt, need_retry=False)
             clean_output = re.sub(r'<think>.*?</think>', '', response.content, flags=re.DOTALL)
             user_question_and_solution_temp = self.user_question_and_solution_list_parser.parse(clean_output)
             return user_question_and_solution_temp.user_question_list
 
         return [user_question_and_solution]
     
-    @retry_llm_call(max_retries=3, delay=2)
-    def get_product_name_and_module_name(self, product_line, conversation_rows, product_detail_dict, user_question_str, solution_str):
-        """分析产品名称和模块名称"""
-        if product_line == '':
-            return '', ''
-             
-        json_str = json.dumps(product_detail_dict[product_line])
-        dialogue_str = self.get_dialogue_str(conversation_rows)
-        
-        prompt = f"""
-请根据以下对话内容分析所属产品名称和模块名称，按优先级找出最相关的1-3个分类标签及置信度（0-1），最后返回置信度最高的分类标签。
-
-要求：
-1. 如果对话记录中存在多个产品名称和模块名称，则根据"{user_question_str}"和"{solution_str}"判断最可能的产品名称和模块名称。
-2. 如果对话记录中只存在一个产品名称和模块名称，则直接返回该产品名称和模块名称。
-
-输出格式：
-{self.product_name_and_module_name_parser.get_format_instructions()}
-
-产品名称列表及模块名称列表：
-{json_str}
-
-对话记录：
-{dialogue_str}
-        """
-        
-        response = self.llm.invoke(user_prompt=prompt, need_retry=False, api_key=self.api_key)
-        clean_output = re.sub(r'<think>.*?</think>', '', response.content, flags=re.DOTALL)
-        product_name_and_module_name = self.product_name_and_module_name_parser.parse(clean_output)
-        
-        return product_name_and_module_name.product_name, product_name_and_module_name.module_name
-    
-    @retry_llm_call(max_retries=3, delay=2)
-    def get_product_line(self, conversation_rows, product_detail_dict, user_question_str, solution_str):
-        """分析产品线"""
-        dialogue_str = self.get_dialogue_str(conversation_rows)
-        product_line_list = list(product_detail_dict.keys())
-        
-        prompt = f"""
-请根据以下对话内容分析所属产品线，按优先级找出最相关的1-3个分类标签及置信度（0-1），最后返回置信度最高的分类标签。
-无法判断时，返回空字符串。即product_line=""
-
-要求：
-1. 如果对话记录中存在多个产品线，则根据"{user_question_str}"和"{solution_str}"判断最可能的产品线。
-2. 如果对话记录中只存在一个产品线，则直接返回该产品线。
-
-输出格式：
-{self.product_line_parser.get_format_instructions()}
-
-产品线列表：
-{product_line_list}
-
-对话记录：
-{dialogue_str}
-        """
-        
-        response = self.llm.invoke(user_prompt=prompt, need_retry=False, api_key=self.api_key)
-        clean_output = re.sub(r'<think>.*?</think>', '', response.content, flags=re.DOTALL)
-        product_line = self.product_line_parser.parse(clean_output)
-        
-        return product_line.product_line
-    
     @retry_llm_call(max_retries=3, delay=2)
     def get_problem_type(self, conversation_rows, user_question_str, solution_str):
         """分析问题类型"""
@@ -421,7 +437,7 @@ class DialogueToWorkorder:
 {dialogue_str}
         """
         
-        response = self.llm.invoke(user_prompt=prompt, need_retry=False, api_key=self.api_key)
+        response = self.llm.invoke(user_prompt=prompt, need_retry=False)
         clean_output = re.sub(r'<think>.*?</think>', '', response.content, flags=re.DOTALL)
         question_type = self.question_type_parser.parse(clean_output)
         
@@ -458,7 +474,7 @@ class DialogueToWorkorder:
 
         """
         
-        response = self.llm.invoke(user_prompt=prompt, need_retry=False, api_key=self.api_key)
+        response = self.llm.invoke(user_prompt=prompt, need_retry=False)
         clean_output = re.sub(r'<think>.*?</think>', '', response.content, flags=re.DOTALL)
         is_complaint = self.is_complaint_parser.parse(clean_output)
         
@@ -467,7 +483,7 @@ class DialogueToWorkorder:
                 is_complaint.dissatisfaction_reasoning, 
                 is_complaint.is_complaint)
     
-    def process_conversation(self, conversation_id, conversation_rows, product_detail_dict):
+    def process_conversation(self, conversation_id, conversation_rows):
         """处理单个会话的函数，用于多线程并发"""
         # if conversation_id!="b157aa91-3acb-11f0-a191-4fb224ef4b40":
         #     return []
@@ -494,34 +510,9 @@ class DialogueToWorkorder:
             # 分析问题类型
             problem_type = self.get_problem_type(conversation_rows, user_question_str, solution_str)
             
-            # 分析产品线
-            product_line = self.get_product_line(conversation_rows, product_detail_dict, user_question_str, solution_str)
-            # 分析产品名称和模块名称
-            if product_line != '':
-                product_name, module_name = self.get_product_name_and_module_name(
-                    product_line, conversation_rows, product_detail_dict, user_question_str, solution_str)
-            else:
-                product_name = ''
-                module_name = ''
-            
             # 创建工单列表
             workorder_list = []
             
-
-            # 更新工单字典
-            # base_workorder_dict.update({
-            #         "产品线": product_line,
-            #         "产品名称": product_name,
-            #         "模块名称": module_name,
-            #         "客户问题": user_question_str,
-            #         "问题类型": problem_type,
-            #         "是否抱怨": "是" if is_dissatisfaction else '否',
-            #         "抱怨内容": dissatisfaction_reasoning if is_dissatisfaction else '',
-            #         "抱怨级别": dissatisfaction_level if is_dissatisfaction else '',
-            #         "是否投诉": "是" if is_complaint else '否',
-            #         "解决方案": solution_str
-            #     })
-            # workorder_list.append(base_workorder_dict)
             for user_question in user_question_list:
                 user_question_str = user_question.user_question
                 solution_str = user_question.solution
@@ -531,9 +522,6 @@ class DialogueToWorkorder:
 
                 # 更新工单字典
                 workorder_dict.update({
-                    "产品线": product_line,
-                    "产品名称": product_name,
-                    "模块名称": module_name,
                     "客户问题": user_question_str,
                     "问题类型": problem_type,
                     "是否抱怨": "是" if is_dissatisfaction else '否',
@@ -551,7 +539,7 @@ class DialogueToWorkorder:
             logger.error(f"处理会话ID: {conversation_id} 时发生错误: {e}")
             return []
     
-    def analyze_conversation_data(self, conversation_excel_path, product_detail_excel_path, max_workers=10, start_date=None, end_date=None):
+    def analyze_conversation_data(self, conversation_excel_path, max_workers=10, start_date=None, end_date=None):
         """分析会话数据主流程，使用多线程并发处理"""
         # 读取Excel文件
         df = pd.read_excel(conversation_excel_path)
@@ -560,9 +548,6 @@ class DialogueToWorkorder:
         logger.info(f"Excel文件列名: {df.columns.tolist()}")
         logger.info(f"数据总行数: {len(df)}")
         
-        # 解析产品详情
-        product_detail_dict = self.parse_product_detail_excel(product_detail_excel_path)
-        
         # 按会话ID分组
         conversation_dict = self.group_conversations_by_id(df)
 
@@ -596,7 +581,7 @@ class DialogueToWorkorder:
         with concurrent.futures.ThreadPoolExecutor(max_workers=max_workers) as executor:
             # 创建任务
             future_to_conversation = {
-                executor.submit(self.process_conversation, conversation_id, conversation_rows, product_detail_dict): conversation_id
+                executor.submit(self.process_conversation, conversation_id, conversation_rows): conversation_id
                 for conversation_id, conversation_rows in conversation_dict.items()
             }
             
@@ -694,13 +679,11 @@ def parse_arguments():
     
     parser.add_argument('--conversation_file', type=str, required=False,
                         help='会话内容Excel文件路径')
-    parser.add_argument('--product_detail_file', type=str, required=False,
+    parser.add_argument('--max_workers', type=int, default=40,
-                        help='产品详情Excel文件路径')
-    parser.add_argument('--max_workers', type=int, default=6,
                         help='并发处理线程数，默认为16')
-    parser.add_argument('--start_date', type=str, required=False,default="2025-06-10 16:08:00",
+    parser.add_argument('--start_date', type=str, required=False,default=None,
                         help='开始日期，格式为YYYY-MM-DD')
-    parser.add_argument('--end_date', type=str, required=False,default="2025-06-30 23:59:59",
+    parser.add_argument('--end_date', type=str, required=False,default=None,
                         help='结束日期，格式为YYYY-MM-DD')
     
     return parser.parse_args()
@@ -712,8 +695,7 @@ def main():
     args = parse_arguments()
     
     # 设置默认文件路径
-    conversation_excel_path = args.conversation_file or os.path.join('data', 'excel', '2025年1月到6月所有对话记录.xlsx')
+    conversation_excel_path = args.conversation_file or os.path.join('data', 'excel', '客服对话记录7.1-7.22.xlsx')
-    product_detail_excel_path = args.product_detail_file or os.path.join('data', 'excel', '产品详情_工单.xlsx')
     
     # 创建处理实例
     processor = DialogueToWorkorder()
@@ -721,7 +703,6 @@ def main():
     # 分析会话数据
     workorder_dict_list = processor.analyze_conversation_data(
         conversation_excel_path, 
-        product_detail_excel_path, 
         max_workers=args.max_workers,
         start_date=args.start_date,
         end_date=args.end_date