diff --git a/dsLightRag/Volcengine/T3_ChatWithMemory.py b/dsLightRag/Volcengine/T3_ChatWithMemory.py new file mode 100644 index 00000000..f3be793a --- /dev/null +++ b/dsLightRag/Volcengine/T3_ChatWithMemory.py @@ -0,0 +1,248 @@ +import logging +import sys +import time +import json + +from Config.Config import VOLC_ACCESSKEY, VOLC_SECRETKEY, VOLC_API_KEY +from Volcengine.Kit.VikingDBMemoryService import VikingDBMemoryService, MEMORY_COLLECTION_NAME +from volcenginesdkarkruntime import Ark + +# 控制日志输出 +logger = logging.getLogger('ChatWithMemory') +logger.setLevel(logging.INFO) + +# 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) + + +def initialize_services(): + """初始化服务和LLM客户端""" + 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, + host="api-knowledgebase.mlp.cn-beijing.volces.com", + region="cn-beijing" + ) + llm_client = Ark( + base_url="https://ark.cn-beijing.volces.com/api/v3", + api_key=ark_api_key, + ) + return memory_service, llm_client + + +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=conversation_history, + metadata=metadata + ) + 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.info(f"归档对话失败: {e}") + return False + + +def main(): + logger.info("开始测试大模型记忆功能...") + + try: + # 使用initialize_services函数初始化服务和LLM客户端 + memory_service, llm_client = initialize_services() + + collection_name = MEMORY_COLLECTION_NAME + user_id = "liming" + assistant_id = "assistant" + + # 告知大模型用户信息 + logger.info("告知大模型用户信息...") + user_info = "李明，男生，15岁，家住长春" + + # 记录信息到记忆体 + logger.info("记录用户信息到记忆体...") + + # 准备对话历史 + conversation_history = [] + + # 使用正确的handle_conversation_turn方法参数 + response = handle_conversation_turn( + memory_service=memory_service, + llm_client=llm_client, + collection_name=collection_name, + user_id=user_id, + user_message=f"请记住以下用户信息：{user_info}", + conversation_history=conversation_history + ) + + logger.info(f"模型回复: {response}") + + # 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" + ) + + # 等待一段时间确保索引更新 + logger.info("等待索引更新...") + time.sleep(5) + + # 验证大模型是否记住个人信息 + logger.info("验证大模型是否记住个人信息...") + test_conversation_history = [] + + test_response = handle_conversation_turn( + memory_service=memory_service, + llm_client=llm_client, + collection_name=collection_name, + user_id=user_id, + user_message="请告诉我李明的个人信息", + conversation_history=test_conversation_history + ) + + logger.info(f"测试回复: {test_response}") + + # 检查回复中是否包含关键信息 + keywords = ["李明", "男", "15", "长春"] + found_keywords = [kw for kw in keywords if kw in test_response] + + if len(found_keywords) == len(keywords): + logger.info("✅ 大模型成功记住了用户信息！") + else: + logger.info(f"❌ 大模型可能没有完全记住用户信息。找到的关键词: {found_keywords}") + + # 尝试直接搜索记忆 + logger.info("尝试直接搜索记忆...") + filter_params = { + "user_id": [user_id], + "memory_type": ["sys_event_v1", "sys_profile_v1"] + } + search_result = memory_service.search_memory( + collection_name=collection_name, + query="李明 15岁 长春 男生", + filter=filter_params, + limit=5 + ) + + logger.info(f"搜索结果: {search_result}") + + except Exception as e: + logger.error(f"操作失败: {e}") + sys.exit(1) + + +if __name__ == "__main__": + main() \ No newline at end of file