From 1ba6d0a7f380abe83a84e47fcf7527f44a6465bc Mon Sep 17 00:00:00 2001
From: HuangHai <10402852@qq.com>
Date: Sun, 7 Sep 2025 12:59:40 +0800
Subject: [PATCH] 'commit'

---
 dsLightRag/Volcengine/T2_CreateIndex.py       | 114 +-----------------
 .../__pycache__/chat.cpython-310.pyc          | Bin 0 -> 12779 bytes
 2 files changed, 1 insertion(+), 113 deletions(-)
 create mode 100644 dsLightRag/Volcengine/__pycache__/chat.cpython-310.pyc

diff --git a/dsLightRag/Volcengine/T2_CreateIndex.py b/dsLightRag/Volcengine/T2_CreateIndex.py
index 468cd7a7..4a21eb6b 100644
--- a/dsLightRag/Volcengine/T2_CreateIndex.py
+++ b/dsLightRag/Volcengine/T2_CreateIndex.py
@@ -16,6 +16,7 @@ from volcenginesdkarkruntime import Ark
 from Config.Config import VOLC_SECRETKEY, VOLC_API_KEY, VOLC_ACCESSKEY
 from Volcengine.VikingDBMemoryService import MEMORY_COLLECTION_NAME, VikingDBMemoryException, VikingDBMemoryService, \
     initialize_services, ensure_collection_exists
+from Volcengine.chat import handle_conversation_turn, archive_conversation
 
 # 控制日志输出
 logger = logging.getLogger('CollectionMemory')
@@ -29,119 +30,6 @@ if not logger.handlers:
 
 
 
-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("开始端到端记忆测试...")
 
diff --git a/dsLightRag/Volcengine/__pycache__/chat.cpython-310.pyc b/dsLightRag/Volcengine/__pycache__/chat.cpython-310.pyc
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