diff --git a/dsLightRag/Volcengine/T2_CreateIndex.py b/dsLightRag/Volcengine/T2_CreateIndex.py index 138b4d55..e8f461f8 100644 --- a/dsLightRag/Volcengine/T2_CreateIndex.py +++ b/dsLightRag/Volcengine/T2_CreateIndex.py @@ -1,111 +1,413 @@ +import logging +import logging +import threading + +from volcengine.ApiInfo import ApiInfo +from volcengine.Credentials import Credentials +from volcengine.ServiceInfo import ServiceInfo +from volcengine.auth.SignerV4 import SignerV4 +from volcengine.base.Service import Service + import json import time -import logging -import sys -from Config.Config import VOLC_ACCESSKEY, VOLC_SECRETKEY -from VikingDBMemoryService import VikingDBMemoryService, VikingDBMemoryException +from dotenv import load_dotenv +from volcenginesdkarkruntime import Ark -# 配置日志 -logging.basicConfig(level=logging.INFO) +from Config.Config import VOLC_SECRETKEY, VOLC_API_KEY, VOLC_ACCESSKEY +from Volcengine.VikingDBMemoryService import MEMORY_COLLECTION_NAME + +# 控制日志输出 logger = logging.getLogger('CollectionMemory') +logger.setLevel(logging.INFO) -def main(): - logger.info("开始创建并等待集合就绪...") - collection_name = "dsideal_collection" - user_id = "system" - assistant_id = "system" +# 只添加一次处理器，避免重复日志 +if not logger.handlers: + handler = logging.StreamHandler() + handler.setFormatter(logging.Formatter('%(asctime)s - %(name)s - %(levelname)s - %(message)s')) + logger.addHandler(handler) - try: - # 初始化服务 - logger.info("初始化记忆库服务...") - memory_service = VikingDBMemoryService(ak=VOLC_ACCESSKEY, sk=VOLC_SECRETKEY) +class VikingDBMemoryException(Exception): + def __init__(self, code, request_id, message=None): + self.code = code + self.request_id = request_id + self.message = "{}, code:{}，request_id:{}".format(message, self.code, self.request_id) - # 检查集合是否存在，不存在则创建 - logger.info(f"检查集合 '{collection_name}' 是否存在...") + def __str__(self): + return self.message + + +class VikingDBMemoryService(Service): + _instance_lock = threading.Lock() + + def __new__(cls, *args, **kwargs): + if not hasattr(VikingDBMemoryService, "_instance"): + with VikingDBMemoryService._instance_lock: + if not hasattr(VikingDBMemoryService, "_instance"): + VikingDBMemoryService._instance = object.__new__(cls) + return VikingDBMemoryService._instance + + def __init__(self, host="api-knowledgebase.mlp.cn-beijing.volces.com", region="cn-beijing", ak="", sk="", + sts_token="", scheme='https', + connection_timeout=30, socket_timeout=30): + self.service_info = VikingDBMemoryService.get_service_info(host, region, scheme, connection_timeout, + socket_timeout) + self.api_info = VikingDBMemoryService.get_api_info() + super(VikingDBMemoryService, self).__init__(self.service_info, self.api_info) + if ak: + self.set_ak(ak) + if sk: + self.set_sk(sk) + if sts_token: + self.set_session_token(session_token=sts_token) try: - memory_service.get_collection(collection_name) - logger.info(f"集合 '{collection_name}' 已存在") + self.get_body("Ping", {}, json.dumps({})) except Exception as e: - error_message = str(e) - if "collection not exist" in error_message: - logger.info(f"集合 '{collection_name}' 不存在，正在创建...") + raise VikingDBMemoryException(1000028, "missed", "host or region is incorrect".format(str(e))) from None + + def setHeader(self, header): + api_info = VikingDBMemoryService.get_api_info() + for key in api_info: + for item in header: + api_info[key].header[item] = header[item] + self.api_info = api_info + + @staticmethod + def get_service_info(host, region, scheme, connection_timeout, socket_timeout): + service_info = ServiceInfo(host, {"Host": host}, + Credentials('', '', 'air', region), connection_timeout, socket_timeout, + scheme=scheme) + return service_info + + @staticmethod + def get_api_info(): + api_info = { + "CreateCollection": ApiInfo("POST", "/api/memory/collection/create", {}, {}, + {'Accept': 'application/json', 'Content-Type': 'application/json'}), + "GetCollection": ApiInfo("POST", "/api/memory/collection/info", {}, {}, + {'Accept': 'application/json', 'Content-Type': 'application/json'}), + "DropCollection": ApiInfo("POST", "/api/memory/collection/delete", {}, {}, + {'Accept': 'application/json', 'Content-Type': 'application/json'}), + "UpdateCollection": ApiInfo("POST", "/api/memory/collection/update", {}, {}, + {'Accept': 'application/json', 'Content-Type': 'application/json'}), + + "SearchMemory": ApiInfo("POST", "/api/memory/search", {}, {}, + {'Accept': 'application/json', 'Content-Type': 'application/json'}), + "AddSession": ApiInfo("POST", "/api/memory/session/add", {}, {}, + {'Accept': 'application/json', 'Content-Type': 'application/json'}), + + "Ping": ApiInfo("GET", "/api/memory/ping", {}, {}, + {'Accept': 'application/json', 'Content-Type': 'application/json'}), + } + return api_info + + def get_body(self, api, params, body): + if not (api in self.api_info): + raise Exception("no such api") + api_info = self.api_info[api] + r = self.prepare_request(api_info, params) + r.headers['Content-Type'] = 'application/json' + r.headers['Traffic-Source'] = 'SDK' + r.body = body + + SignerV4.sign(r, self.service_info.credentials) + + url = r.build() + resp = self.session.get(url, headers=r.headers, data=r.body, + timeout=(self.service_info.connection_timeout, self.service_info.socket_timeout)) + if resp.status_code == 200: + return json.dumps(resp.json()) + else: + raise Exception(resp.text.encode("utf-8")) + + def get_body_exception(self, api, params, body): + try: + res = self.get_body(api, params, body) + except Exception as e: + try: + res_json = json.loads(e.args[0].decode("utf-8")) + except: + raise VikingDBMemoryException(1000028, "missed", "json load res error, res:{}".format(str(e))) from None + code = res_json.get("code", 1000028) + request_id = res_json.get("request_id", 1000028) + message = res_json.get("message", None) + + raise VikingDBMemoryException(code, request_id, message) + + if res == '': + raise VikingDBMemoryException(1000028, "missed", + "empty response due to unknown error, please contact customer service") from None + return res + + def get_exception(self, api, params): + try: + res = self.get(api, params) + except Exception as e: + try: + res_json = json.loads(e.args[0].decode("utf-8")) + except: + raise VikingDBMemoryException(1000028, "missed", "json load res error, res:{}".format(str(e))) from None + code = res_json.get("code", 1000028) + request_id = res_json.get("request_id", 1000028) + message = res_json.get("message", None) + raise VikingDBMemoryException(code, request_id, message) + if res == '': + raise VikingDBMemoryException(1000028, "missed", + "empty response due to unknown error, please contact customer service") from None + return res + + def create_collection(self, collection_name, description="", custom_event_type_schemas=[], + custom_entity_type_schemas=[], builtin_event_types=[], builtin_entity_types=[]): + params = { + "CollectionName": collection_name, "Description": description, + "CustomEventTypeSchemas": custom_event_type_schemas, "CustomEntityTypeSchemas": custom_entity_type_schemas, + "BuiltinEventTypes": builtin_event_types, "BuiltinEntityTypes": builtin_entity_types, + } + res = self.json("CreateCollection", {}, json.dumps(params)) + return json.loads(res) + + def get_collection(self, collection_name): + params = {"CollectionName": collection_name} + res = self.json("GetCollection", {}, json.dumps(params)) + return json.loads(res) + + def drop_collection(self, collection_name): + params = {"CollectionName": collection_name} + res = self.json("DropCollection", {}, json.dumps(params)) + return json.loads(res) + + def update_collection(self, collection_name, custom_event_type_schemas=[], custom_entity_type_schemas=[], + builtin_event_types=[], builtin_entity_types=[]): + params = { + "CollectionName": collection_name, + "CustomEventTypeSchemas": custom_event_type_schemas, "CustomEntityTypeSchemas": custom_entity_type_schemas, + "BuiltinEventTypes": builtin_event_types, "BuiltinEntityTypes": builtin_entity_types, + } + res = self.json("UpdateCollection", {}, json.dumps(params)) + return json.loads(res) + + def search_memory(self, collection_name, query, filter, limit=10): + params = { + "collection_name": collection_name, + "query": query, + "limit": limit, + "filter": filter, + } + res = self.json("SearchMemory", {}, json.dumps(params)) + return json.loads(res) + + def add_session(self, collection_name, session_id, messages, metadata, entities=None): + params = { + "collection_name": collection_name, + "session_id": session_id, + "messages": messages, + "metadata": metadata, + } + if entities is not None: + params["entities"] = entities + res = self.json("AddSession", {}, json.dumps(params)) + return json.loads(res) + + + + +def initialize_services(): + load_dotenv() + ak = VOLC_ACCESSKEY + sk = VOLC_SECRETKEY + ark_api_key = VOLC_API_KEY + + if not all([ak, sk, ark_api_key]): + raise ValueError("必须在环境变量中设置 VOLC_ACCESSKEY, VOLC_SECRETKEY, 和 ARK_API_KEY。") + + memory_service = VikingDBMemoryService(ak=ak, sk=sk) + llm_client = Ark( + base_url="https://ark.cn-beijing.volces.com/api/v3", + api_key=ark_api_key, + ) + return memory_service, llm_client + + +def ensure_collection_exists(memory_service, collection_name): + """检查记忆集合是否存在，如果不存在则创建。""" + try: + memory_service.get_collection(collection_name) + logger.info(f"记忆集合 '{collection_name}' 已存在。") + except Exception as e: + error_message = str(e) + if "collection not exist" in error_message: + logger.info(f"记忆集合 '{collection_name}' 未找到，正在创建...") + try: memory_service.create_collection( collection_name=collection_name, description="中文情感陪伴场景测试", builtin_event_types=["sys_event_v1", "sys_profile_collect_v1"], builtin_entity_types=["sys_profile_v1"] ) - logger.info(f"集合 '{collection_name}' 创建成功") - else: - logger.error(f"检查集合时出错: {e}") - sys.exit(1) + logger.info(f"记忆集合 '{collection_name}' 创建成功。") + logger.info("等待集合准备就绪...") + except Exception as create_e: + logger.info(f"创建集合失败: {create_e}") + raise + else: + logger.info(f"检查集合时出错: {e}") + raise - # 添加测试数据 - logger.info("添加测试数据以初始化索引...") - session_id = f"init_session_{int(time.time())}" - test_messages = [{ - "role": "user", - "content": "初始化测试消息", - "timestamp": int(time.time() * 1000) - }] - test_metadata = { - "default_user_id": user_id, - "default_assistant_id": assistant_id, - "time": int(time.time() * 1000) - } + +def search_relevant_memories(memory_service, collection_name, user_id, query): + """搜索与用户查询相关的记忆，并在索引构建中时重试。""" + logger.info(f"正在搜索与 '{query}' 相关的记忆...") + retry_attempt = 0 + while True: + try: + filter_params = { + "user_id": [user_id], + "memory_type": ["sys_event_v1", "sys_profile_v1"] + } + response = memory_service.search_memory( + collection_name=collection_name, + query=query, + filter=filter_params, + limit=3 + ) + + memories = [] + if response.get('data', {}).get('count', 0) > 0: + for result in response['data']['result_list']: + if 'memory_info' in result and result['memory_info']: + memories.append({ + 'memory_info': result['memory_info'], + 'score': result['score'] + }) + + if memories: + if retry_attempt > 0: + logger.info("重试后搜索成功。") + logger.info(f"找到 {len(memories)} 条相关记忆:") + for i, memory in enumerate(memories, 1): + logger.info( + f" {i}. (相关度: {memory['score']:.3f}): {json.dumps(memory['memory_info'], ensure_ascii=False, indent=2)}") + else: + logger.info("未找到相关记忆。") + return memories + + except Exception as e: + error_message = str(e) + if "1000023" in error_message: + retry_attempt += 1 + logger.info(f"记忆索引正在构建中。将在60秒后重试... (尝试次数 {retry_attempt})") + time.sleep(60) + else: + logger.info(f"搜索记忆时出错 (不可重试): {e}") + return [] + + +def handle_conversation_turn(memory_service, llm_client, collection_name, user_id, user_message, conversation_history): + """处理一轮对话，包括记忆搜索和LLM响应。""" + logger.info("\n" + "=" * 60) + logger.info(f"用户: {user_message}") + + relevant_memories = search_relevant_memories(memory_service, collection_name, user_id, user_message) + + system_prompt = "你是一个富有同情心、善于倾听的AI伙伴，拥有长期记忆能力。你的目标是为用户提供情感支持和温暖的陪伴。" + if relevant_memories: + memory_context = "\n".join( + [f"- {json.dumps(mem['memory_info'], ensure_ascii=False)}" for mem in relevant_memories]) + system_prompt += f"\n\n这是我们过去的一些对话记忆，请参考：\n{memory_context}\n\n请利用这些信息来更好地理解和回应用户。" + + logger.info("AI正在思考...") + + try: + messages = [{"role": "system", "content": system_prompt}] + conversation_history + [ + {"role": "user", "content": user_message}] + completion = llm_client.chat.completions.create( + model="doubao-seed-1-6-flash-250715", + messages=messages + ) + assistant_reply = completion.choices[0].message.content + except Exception as e: + logger.info(f"LLM调用失败: {e}") + assistant_reply = "抱歉，我现在有点混乱，无法回应。我们可以稍后再聊吗？" + + logger.info(f"伙伴: {assistant_reply}") + + conversation_history.extend([ + {"role": "user", "content": user_message}, + {"role": "assistant", "content": assistant_reply} + ]) + return assistant_reply + + +def archive_conversation(memory_service, collection_name, user_id, assistant_id, conversation_history, topic_name): + """将对话历史归档到记忆数据库。""" + if not conversation_history: + logger.info("没有对话可以归档。") + return False + + logger.info(f"\n正在归档关于 '{topic_name}' 的对话...") + session_id = f"{topic_name}_{int(time.time())}" + metadata = { + "default_user_id": user_id, + "default_assistant_id": assistant_id, + "time": int(time.time() * 1000) + } + + try: memory_service.add_session( collection_name=collection_name, session_id=session_id, - messages=test_messages, - metadata=test_metadata + messages=conversation_history, + metadata=metadata ) - - # 等待索引就绪 - logger.info("开始等待索引构建完成...") - max_retries = 30 - retry_interval = 10 - retry_count = 0 - - while retry_count < max_retries: - try: - filter_params = {"user_id": [user_id], "memory_type": ["sys_event_v1"]} - memory_service.search_memory( - collection_name=collection_name, - query="测试", - filter=filter_params, - limit=1 - ) - logger.info(f"集合 '{collection_name}' 索引构建完成，已就绪") - sys.exit(0) - except VikingDBMemoryException as e: - error_msg = str(e) - # 修复点：正确处理"index not ready"错误，进行重试 - if "index not ready" in error_msg or "index not exist" in error_msg or "need to add messages" in error_msg: - retry_count += 1 - remaining = max_retries - retry_count - logger.info(f"索引尚未就绪，将重试({retry_count}/{max_retries})，剩余{remaining}次...") - time.sleep(retry_interval) - else: - logger.error(f"检查索引状态时发生错误: {str(e)}") - sys.exit(1) - except Exception as e: - # 修复点：捕获所有异常，包括非VikingDBMemoryException异常 - error_msg = str(e) - if "index not ready" in error_msg or "index not exist" in error_msg or "need to add messages" in error_msg: - retry_count += 1 - remaining = max_retries - retry_count - logger.info(f"索引尚未就绪，将重试({retry_count}/{max_retries})，剩余{remaining}次...") - time.sleep(retry_interval) - else: - logger.error(f"检查索引状态时发生未知错误: {str(e)}") - sys.exit(1) - - logger.error(f"达到最大重试次数({max_retries})，索引仍未就绪") - sys.exit(1) - + logger.info(f"对话已成功归档，会话ID: {session_id}") + logger.info("正在等待记忆索引更新...") + return True except Exception as e: - logger.error(f"系统异常: {str(e)}") - sys.exit(1) + logger.info(f"归档对话失败: {e}") + return False + + +def main(): + logger.info("开始端到端记忆测试...") + + try: + memory_service, llm_client = initialize_services() + collection_name = MEMORY_COLLECTION_NAME + user_id = "system" + assistant_id = "assistant" + ensure_collection_exists(memory_service, collection_name) + except Exception as e: + logger.info(f"初始化失败: {e}") + return + + logger.info("\n--- 阶段 1: 初始对话 ---") + initial_conversation_history = [] + handle_conversation_turn( + memory_service, llm_client, collection_name, user_id, + "你好，我是小明，今年18岁，但压力好大。", + initial_conversation_history + ) + handle_conversation_turn( + memory_service, llm_client, collection_name, user_id, + "马上就要高考了，家里人的期待好高。", + initial_conversation_history + ) + + logger.info("\n--- 阶段 2: 归档记忆 ---") + archive_conversation( + memory_service, collection_name, user_id, assistant_id, + initial_conversation_history, "study_stress_discussion" + ) + + logger.info("\n--- 阶段 3: 验证记忆 ---") + verification_conversation_history = [] + handle_conversation_turn( + memory_service, llm_client, collection_name, user_id, + "我最近很焦虑，不知道该怎么办。", + verification_conversation_history + ) + + logger.info("\n端到端记忆测试完成！") + if __name__ == "__main__": main() \ No newline at end of file