'commit'

dsLightRag/Volcengine/T3_ChatWithMemory.py

@@ -55,12 +55,12 @@ def main():
 
         # 归档对话
         archive_conversation(
-            memory_service=memory_service,
-            collection_name=collection_name,
-            user_id=user_id,
-            assistant_id=assistant_id,
-            conversation_history=conversation_history,
-            topic_name="user_info"
+            memory_service=memory_service,  # 内存记忆服务
+            collection_name=collection_name,  # 集合名称
+            user_id=user_id,  # 用户ID
+            assistant_id=assistant_id,  # 助手ID
+            conversation_history=conversation_history,  # 对话历史
+            topic_name="user_info"  # 会话主题
         )
 
         # 等待一段时间确保索引更新
@@ -72,15 +72,16 @@ def main():
         test_conversation_history = []
 
         test_response = handle_conversation_turn(
-            memory_service=memory_service,
+            memory_service=memory_service, # 内存记忆服务
             llm_client=llm_client,
-            collection_name=collection_name,
-            user_id=user_id,
-            assistant_id=assistant_id,  # 添加这一行
-            user_message="请告诉我李明的个人信息",
-            conversation_history=test_conversation_history
+            collection_name=collection_name,# 集合名称
+            user_id=user_id, # 用户ID
+            assistant_id=assistant_id,  # 助手ID
+            user_message="请告诉我李明的个人信息",# 交流的信息
+            conversation_history=test_conversation_history # 对话历史
         )
 
+        # 这次交互就没有记录信息，看来需要根据业务来决定是不是记录到记忆体中
         logger.info(f"测试回复: {test_response}")
 
         # 检查回复中是否包含关键信息

dsLightRag/Volcengine/chat.py.backup

@@ -1,399 +0,0 @@
-import json
-import threading
-import time
-from dotenv import load_dotenv
-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
-from volcenginesdkarkruntime import Ark
-
-from Config.Config import VOLC_SECRETKEY, VOLC_API_KEY, VOLC_ACCESSKEY
-
-
-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)
-
-    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:
-            self.get_body("Ping", {}, json.dumps({}))
-        except Exception as e:
-            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)
-        print(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:
-            print(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"]
-                )
-                print(f"记忆集合 '{collection_name}' 创建成功。")
-                print("等待集合准备就绪...")
-            except Exception as create_e:
-                print(f"创建集合失败: {create_e}")
-                raise
-        else:
-            print(f"检查集合时出错: {e}")
-            raise
-
-
-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。"""
-    print(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:
-                    print("重试后搜索成功。")
-                print(f"找到 {len(memories)} 条相关记忆:")
-                for i, memory in enumerate(memories, 1):
-                    print(
-                        f"  {i}. (相关度: {memory['score']:.3f}): {json.dumps(memory['memory_info'], ensure_ascii=False, indent=2)}")
-            else:
-                print("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
-                print(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:
-                print(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。"""
-    print("\n" + "=" * 60)
-    print(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。"
-
-    print("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:
-        print(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？"
-
-    print(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:
-        print("没有对话可以归档。")
-        return False
-
-    print(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=conversation_history,
-            metadata=metadata
-        )
-        print(f"对话已成功归档，会话ID: {session_id}")
-        print("正在等待记忆索引更新...")
-        return True
-    except Exception as e:
-        print(f"归档对话失败: {e}")
-        return False
-
-
-def main():
-    print("开始端到端记忆测试...")
-
-    try:
-        memory_service, llm_client = initialize_services()
-        collection_name = "emotional_support"
-        user_id = "xiaoming"
-        assistant_id = "assistant"
-        ensure_collection_exists(memory_service, collection_name)
-    except Exception as e:
-        print(f"初始化失败: {e}")
-        return
-
-    print("\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
-    )
-
-    print("\n--- 阶段 2: 归档记忆 ---")
-    archive_conversation(
-        memory_service, collection_name, user_id, assistant_id,
-        initial_conversation_history, "study_stress_discussion"
-    )
-
-    print("\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
-    )
-
-    print("\n端到端记忆测试完成！")
-
-
-if __name__ == "__main__":
-    main()