diff --git a/dsLightRag/Volcengine/__pycache__/VikingDBMemoryService.cpython-310.pyc b/dsLightRag/Volcengine/__pycache__/VikingDBMemoryService.cpython-310.pyc index 2c87295c..2ed7c6fe 100644 Binary files a/dsLightRag/Volcengine/__pycache__/VikingDBMemoryService.cpython-310.pyc and b/dsLightRag/Volcengine/__pycache__/VikingDBMemoryService.cpython-310.pyc differ diff --git a/dsLightRag/Volcengine/chat.py b/dsLightRag/Volcengine/chat.py index 0c5b1fed..a750856f 100644 --- a/dsLightRag/Volcengine/chat.py +++ b/dsLightRag/Volcengine/chat.py @@ -1,3 +1,4 @@ +import logging import os import time @@ -14,11 +15,16 @@ AI 就能用刚写入的记忆来回答。 import json import time from VikingDBMemoryService import initialize_services, ensure_collection_exists, search_relevant_memories - +# 控制日志输出 +logger = logging.getLogger('CollectionMemory') +logger.setLevel(logging.INFO) +handler = logging.StreamHandler() +handler.setFormatter(logging.Formatter('%(asctime)s - %(name)s - %(levelname)s - %(message)s')) +logger.addHandler(handler) 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}") + logger.info("\n" + "=" * 60) + logger.info(f"用户: {user_message}") relevant_memories = search_relevant_memories(memory_service, collection_name, user_id, user_message) @@ -28,7 +34,7 @@ def handle_conversation_turn(memory_service, llm_client, collection_name, user_i [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...") + logger.info("AI正在思考...") try: messages = [{"role": "system", "content": system_prompt}] + conversation_history + [ @@ -39,10 +45,10 @@ def handle_conversation_turn(memory_service, llm_client, collection_name, user_i ) assistant_reply = completion.choices[0].message.content except Exception as e: - print(f"LLM调用失败: {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？" - print(f"伙伴: {assistant_reply}") + logger.info(f"伙伴: {assistant_reply}") conversation_history.extend([ {"role": "user", "content": user_message}, @@ -53,10 +59,10 @@ def handle_conversation_turn(memory_service, llm_client, collection_name, user_i 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。") + logger.info("没有对话可以归档。") return False - print(f"\n正在归档关于 '{topic_name}' 的对话...") + 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, @@ -71,11 +77,11 @@ def archive_conversation(memory_service, collection_name, user_id, assistant_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...") + 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: - print(f"归档对话失败: {e}") + logger.info(f"归档对话失败: {e}") return False def setup_memory_collection(collection_name="emotional_support"): @@ -83,18 +89,18 @@ def setup_memory_collection(collection_name="emotional_support"): try: memory_service, _ = initialize_services() ensure_collection_exists(memory_service, collection_name) - print(f"记忆体 '{collection_name}' 创建/验证成功") + logger.info(f"记忆体 '{collection_name}' 创建/验证成功") # 添加集合就绪等待 - print("等待集合准备就绪...") + logger.info("等待集合准备就绪...") if wait_for_collection_ready(memory_service, collection_name): - print(f"集合 '{collection_name}' 已就绪") + logger.info(f"集合 '{collection_name}' 已就绪") return memory_service else: - print(f"集合 '{collection_name}' 未能就绪") + logger.info(f"集合 '{collection_name}' 未能就绪") return None except Exception as e: - print(f"记忆体创建失败: {e}") + logger.info(f"记忆体创建失败: {e}") return None def wait_for_collection_ready(memory_service, collection_name, timeout=300, interval=10): @@ -112,18 +118,18 @@ def wait_for_collection_ready(memory_service, collection_name, timeout=300, inte collection_info = memory_service.get_collection(collection_name) # 根据Volcengine API文档，状态可能在Status字段中，值可能为"READY"、"CREATING"等 status = collection_info.get("Status", "UNKNOWN") - print(f"集合 '{collection_name}' 当前状态: {status}") + logger.info(f"集合 '{collection_name}' 当前状态: {status}") if status == "READY": return True time.sleep(interval) except Exception as e: - print(f"检查集合状态失败: {e}") + logger.info(f"检查集合状态失败: {e}") time.sleep(interval) - print(f"集合 '{collection_name}' 在{timeout}秒内未就绪") + logger.info(f"集合 '{collection_name}' 在{timeout}秒内未就绪") return False def main(): - print("开始端到端记忆测试...") + logger.info("开始端到端记忆测试...") collection_name="emotional_support" try: @@ -138,10 +144,10 @@ def main(): user_id = "xiaoming" # 用户ID:小明 assistant_id = "assistant1" # 助手ID:助手1 except Exception as e: - print(f"初始化失败: {e}") + logger.info(f"初始化失败: {e}") return - print("\n--- 阶段 1: 初始对话 ---") + logger.info("\n--- 阶段 1: 初始对话 ---") initial_conversation_history = [] handle_conversation_turn( memory_service, llm_client, collection_name, user_id, @@ -154,13 +160,13 @@ def main(): initial_conversation_history ) - print("\n--- 阶段 2: 归档记忆 ---") + 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" ) - print("\n--- 阶段 3: 验证记忆 ---") + logger.info("\n--- 阶段 3: 验证记忆 ---") verification_conversation_history = [] handle_conversation_turn( memory_service, llm_client, collection_name, user_id, @@ -168,7 +174,7 @@ def main(): verification_conversation_history ) - print("\n端到端记忆测试完成！") + logger.info("\n端到端记忆测试完成！") if __name__ == "__main__": setup_memory_collection()