diff --git a/__pycache__/mcp_elasticsearch.cpython-310.pyc b/__pycache__/mcp_elasticsearch.cpython-310.pyc
new file mode 100644
index 00000000..9e9dea52
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diff --git a/__pycache__/mcp_server.cpython-310.pyc b/__pycache__/mcp_server.cpython-310.pyc
new file mode 100644
index 00000000..fcea44c9
Binary files /dev/null and b/__pycache__/mcp_server.cpython-310.pyc differ
diff --git a/mcp_elasticsearch.py b/mcp_elasticsearch.py
index 53407f5f..53d70e3c 100644
--- a/mcp_elasticsearch.py
+++ b/mcp_elasticsearch.py
@@ -69,6 +69,8 @@ class ESClient:
},
"plan": {"type": "text"}, # 执行计划（仅 assistant）
"steps": {"type": "text"}, # 执行步骤（仅 assistant）
+ "session_title": {"type": "text"}, # 会话标题/概述（新增）
+ "is_first_message": {"type": "boolean"}, # 是否是会话首条消息（新增）
"timestamp": {"type": "date"}, # 时间戳
"created_at": {"type": "date"}, # 创建时间
}
@@ -105,6 +107,8 @@ class ESClient:
message: str,
plan: Optional[str] = None,
steps: Optional[str] = None,
+ session_title: Optional[str] = None,
+ is_first_message: bool = False,
) -> str:
"""
保存聊天消息
@@ -118,6 +122,8 @@ class ESClient:
message: 消息内容
plan: 执行计划（可选）
steps: 执行步骤（可选）
+ session_title: 会话标题（可选，通常在首条消息时设置）
+ is_first_message: 是否是会话首条消息
Returns:
文档ID
@@ -136,6 +142,8 @@ class ESClient:
"message_embedding": embedding if embedding else None,
"plan": plan,
"steps": steps,
+ "session_title": session_title,
+ "is_first_message": is_first_message,
"timestamp": datetime.now(),
"created_at": datetime.now(),
}
@@ -157,10 +165,10 @@ class ESClient:
limit: 返回数量
Returns:
- 会话列表，每个会话包含：session_id, last_message, last_timestamp
+ 会话列表，每个会话包含：session_id, title, last_message, last_timestamp
"""
try:
- # 聚合查询：按 session_id 分组，获取每个会话的最后一条消息
+ # 聚合查询：按 session_id 分组，获取每个会话的最后一条消息和标题
query = {
"query": {
"term": {"user_id": user_id}
@@ -180,7 +188,15 @@ class ESClient:
"top_hits": {
"size": 1,
"sort": [{"timestamp": {"order": "desc"}}],
- "_source": ["message", "timestamp", "message_type"]
+ "_source": ["message", "timestamp", "message_type", "session_title"]
+ }
+ },
+ # 获取首条消息（包含标题）
+ "first_message": {
+ "top_hits": {
+ "size": 1,
+ "sort": [{"timestamp": {"order": "asc"}}],
+ "_source": ["session_title", "message"]
}
}
}
@@ -193,11 +209,21 @@ class ESClient:
sessions = []
for bucket in result["aggregations"]["sessions"]["buckets"]:
- session_data = bucket["last_message_content"]["hits"]["hits"][0]["_source"]
+ last_msg = bucket["last_message_content"]["hits"]["hits"][0]["_source"]
+ first_msg = bucket["first_message"]["hits"]["hits"][0]["_source"]
+
+ # 优先使用 session_title，否则使用首条消息的前30字符
+ title = (
+ last_msg.get("session_title") or
+ first_msg.get("session_title") or
+ first_msg.get("message", "")[:30]
+ )
+
sessions.append({
"session_id": bucket["key"],
- "last_message": session_data["message"],
- "last_timestamp": session_data["timestamp"],
+ "title": title,
+ "last_message": last_msg["message"],
+ "last_timestamp": last_msg["timestamp"],
"message_count": bucket["doc_count"],
})
diff --git a/mcp_server.py b/mcp_server.py
index 6a3c043f..7e4e2494 100644
--- a/mcp_server.py
+++ b/mcp_server.py
@@ -1845,6 +1845,24 @@ class MCPAgentIntegrated:
for tool in tools
])
+ # 获取当前时间信息
+ from datetime import datetime
+ now = datetime.now()
+ current_time_info = f"""## 当前时间
+- **日期**: {now.strftime('%Y年%m月%d日')}
+- **时间**: {now.strftime('%H:%M:%S')}
+- **星期**: {['周一', '周二', '周三', '周四', '周五', '周六', '周日'][now.weekday()]}
+- **A股交易时间**: 上午 9:30-11:30，下午 13:00-15:00
+- **当前是否交易时段**: {'是' if (now.weekday() < 5 and ((now.hour == 9 and now.minute >= 30) or (10 <= now.hour < 11) or (now.hour == 11 and now.minute <= 30) or (13 <= now.hour < 15))) else '否'}
+
+**时间语义理解**：
+- "今天/当天" = {now.strftime('%Y-%m-%d')}
+- "最近/近期" = 最近 5-10 个交易日
+- "短线" = 5-20 个交易日
+- "中线" = 1-3 个月
+- "长线" = 6 个月以上
+"""
+
return f"""你是"价小前"，北京价值前沿科技公司的AI投研聊天助手。
## 你的人格特征
@@ -1854,6 +1872,8 @@ class MCPAgentIntegrated:
- **性格**: 专业、严谨、友好，擅长用简洁的语言解释复杂的金融概念
- **服务宗旨**: 帮助投资者做出更明智的投资决策，提供数据驱动的研究支持
+{current_time_info}
+
## 可用工具
{tools_desc}
@@ -1950,15 +1970,30 @@ class MCPAgentIntegrated:
只返回JSON，不要其他内容。"""
- async def create_plan(self, user_query: str, tools: List[dict]) -> ExecutionPlan:
- """阶段1: 使用 Kimi 创建执行计划（带思考过程）"""
+ async def create_plan(self, user_query: str, tools: List[dict], chat_history: List[dict] = None) -> ExecutionPlan:
+ """阶段1: 使用 Kimi 创建执行计划（带思考过程和历史上下文）"""
logger.info(f"[Planning] Kimi开始制定计划: {user_query}")
messages = [
{"role": "system", "content": self.get_planning_prompt(tools)},
- {"role": "user", "content": user_query},
]
+ # 添加会话历史（多轮对话上下文）
+ if chat_history:
+ # 限制历史消息数量，避免 context 过长
+ recent_history = chat_history[-10:] # 最近10条消息
+ for msg in recent_history:
+ role = "user" if msg.get("message_type") == "user" else "assistant"
+ content = msg.get("message", "")
+ # 截断过长的历史消息
+ if len(content) > 500:
+ content = content[:500] + "..."
+ messages.append({"role": role, "content": content})
+ logger.info(f"[Planning] 添加了 {len(recent_history)} 条历史消息到上下文")
+
+ # 添加当前用户问题
+ messages.append({"role": "user", "content": user_query})
+
# 使用 Kimi 思考模型
response = self.kimi_client.chat.completions.create(
model=self.kimi_model,
@@ -2229,13 +2264,16 @@ class MCPAgentIntegrated:
user_query: str,
tools: List[dict],
tool_handlers: Dict[str, Any],
+ chat_history: List[dict] = None,
) -> AgentResponse:
"""主流程（非流式）"""
logger.info(f"[Agent] 处理查询: {user_query}")
+ if chat_history:
+ logger.info(f"[Agent] 带有 {len(chat_history)} 条历史消息")
try:
- # 阶段1: Kimi 制定计划
- plan = await self.create_plan(user_query, tools)
+ # 阶段1: Kimi 制定计划（带历史上下文）
+ plan = await self.create_plan(user_query, tools, chat_history)
# 阶段2: 执行工具
step_results = await self.execute_plan(plan, tool_handlers)
@@ -2271,6 +2309,46 @@ class MCPAgentIntegrated:
message=f"处理失败: {str(e)}",
)
+ async def generate_session_title(self, user_message: str, assistant_response: str) -> str:
+ """生成会话标题（简短概述），使用 DeepMoney 模型"""
+ try:
+ messages = [
+ {
+ "role": "system",
+ "content": "你是一个标题生成器。根据用户问题和AI回复，生成一个简短的会话标题（10-20个字）。只返回标题文本，不要任何其他内容。"
+ },
+ {
+ "role": "user",
+ "content": f"用户问题：{user_message[:200]}\n\nAI回复：{assistant_response[:500]}\n\n请生成一个简短的会话标题："
+ }
+ ]
+
+ # 使用 DeepMoney 模型（更轻量，适合简单任务）
+ response = self.deepmoney_client.chat.completions.create(
+ model=self.deepmoney_model,
+ messages=messages,
+ temperature=0.3,
+ max_tokens=100,
+ )
+
+ title = response.choices[0].message.content.strip()
+
+ # 处理 DeepMoney 的 ... 标签，只保留 之后的内容
+ if "" in title:
+ title = title.split("")[-1].strip()
+
+ # 清理可能的引号
+ title = title.strip('"\'')
+ # 限制长度
+ if len(title) > 30:
+ title = title[:27] + "..."
+ return title
+
+ except Exception as e:
+ logger.error(f"[Title] 生成标题失败: {e}")
+ # 降级：使用用户消息的前20个字符
+ return user_message[:20] + "..." if len(user_message) > 20 else user_message
+
async def process_query_stream(
self,
user_query: str,
@@ -2282,9 +2360,15 @@ class MCPAgentIntegrated:
user_avatar: str = None,
cookies: dict = None,
model_config: dict = None, # 新增：动态模型配置
+ chat_history: List[dict] = None, # 新增：历史对话记录
+ is_new_session: bool = False, # 新增：是否是新会话（用于生成标题）
) -> AsyncGenerator[str, None]:
"""主流程（流式输出）- 逐步返回执行结果"""
logger.info(f"[Agent Stream] 处理查询: {user_query}")
+ if chat_history:
+ logger.info(f"[Agent Stream] 带有 {len(chat_history)} 条历史消息")
+ if is_new_session:
+ logger.info(f"[Agent Stream] 这是新会话，将在完成后生成标题")
# 将 cookies 存储为实例属性，供工具调用时使用
self.cookies = cookies or {}
@@ -2309,11 +2393,26 @@ class MCPAgentIntegrated:
# 阶段1: 使用选中的模型制定计划（流式，带 DeepMoney 备选）
yield self._format_sse("status", {"stage": "planning", "message": "正在制定执行计划..."})
+ # 构建消息列表（包含历史对话上下文）
messages = [
{"role": "system", "content": self.get_planning_prompt(tools)},
- {"role": "user", "content": user_query},
]
+ # 添加历史对话（最近 10 轮，避免上下文过长）
+ if chat_history:
+ recent_history = chat_history[-10:] # 最近 10 条消息
+ for msg in recent_history:
+ role = "user" if msg.get("message_type") == "user" else "assistant"
+ content = msg.get("message", "")
+ # 截断过长的历史消息
+ if len(content) > 500:
+ content = content[:500] + "..."
+ messages.append({"role": role, "content": content})
+ logger.info(f"[Agent Stream] 已添加 {len(recent_history)} 条历史消息到上下文")
+
+ # 添加当前用户查询
+ messages.append({"role": "user", "content": user_query})
+
reasoning_content = ""
plan_content = ""
use_fallback = False
@@ -2650,6 +2749,17 @@ class MCPAgentIntegrated:
"steps": [{"tool": step.tool, "arguments": step.arguments, "reason": step.reason} for step in plan.steps]
}, ensure_ascii=False)
+ # 如果是新会话，生成会话标题
+ session_title = None
+ if is_new_session:
+ try:
+ session_title = await self.generate_session_title(user_query, final_summary)
+ logger.info(f"[Title] 新会话标题: {session_title}")
+ except Exception as title_error:
+ logger.error(f"[Title] 生成标题失败: {title_error}")
+ # 降级：使用用户消息的前 20 个字符
+ session_title = user_query[:20] + "..." if len(user_query) > 20 else user_query
+
es_client.save_chat_message(
session_id=session_id,
user_id=user_id,
@@ -2659,8 +2769,13 @@ class MCPAgentIntegrated:
message=final_summary,
plan=plan_json,
steps=steps_json,
+ session_title=session_title, # 新会话时保存标题
)
logger.info(f"[ES] Agent 回复已保存到会话 {session_id}")
+
+ # 如果生成了标题，通过 SSE 发送给前端
+ if session_title:
+ yield self._format_sse("session_title", {"title": session_title})
except Exception as e:
logger.error(f"[ES] 保存 Agent 回复失败: {e}", exc_info=True)
@@ -2751,6 +2866,17 @@ async def agent_chat(request: AgentChatRequest):
# ==================== 会话管理 ====================
# 如果没有提供 session_id，创建新会话
session_id = request.session_id or str(uuid.uuid4())
+ is_new_session = not request.session_id
+
+ # 获取会话历史（用于多轮对话）
+ chat_history = []
+ if not is_new_session:
+ try:
+ history = es_client.get_chat_history(session_id, limit=20) # 最近20条
+ chat_history = history
+ logger.info(f"加载会话历史: {len(chat_history)} 条消息")
+ except Exception as e:
+ logger.error(f"获取会话历史失败: {e}")
# 保存用户消息到 ES
try:
@@ -2761,6 +2887,7 @@ async def agent_chat(request: AgentChatRequest):
user_avatar=request.user_avatar or "",
message_type="user",
message=request.message,
+ is_first_message=is_new_session,
)
except Exception as e:
logger.error(f"保存用户消息失败: {e}")
@@ -2796,14 +2923,16 @@ async def agent_chat(request: AgentChatRequest):
}
})
- # 处理查询
+ # 处理查询（传入会话历史实现多轮对话）
response = await agent.process_query(
user_query=request.message,
tools=tools,
tool_handlers=TOOL_HANDLERS,
+ chat_history=chat_history,
)
# 保存 Agent 回复到 ES
+ session_title = None
try:
# 将执行步骤转换为JSON字符串
steps_json = json.dumps(
@@ -2814,6 +2943,11 @@ async def agent_chat(request: AgentChatRequest):
# 将 plan 转换为 JSON 字符串（ES 中 plan 字段是 text 类型）
plan_json = json.dumps(response.plan.dict(), ensure_ascii=False) if response.plan else None
+ # 如果是新会话，生成会话标题
+ if is_new_session:
+ session_title = await agent.generate_session_title(request.message, response.final_summary)
+ logger.info(f"生成会话标题: {session_title}")
+
es_client.save_chat_message(
session_id=session_id,
user_id=request.user_id or "anonymous",
@@ -2823,13 +2957,15 @@ async def agent_chat(request: AgentChatRequest):
message=response.final_summary, # 使用 final_summary 而不是 final_answer
plan=plan_json, # 传递 JSON 字符串而不是字典
steps=steps_json,
+ session_title=session_title,
)
except Exception as e:
logger.error(f"保存 Agent 回复失败: {e}", exc_info=True)
- # 在响应中返回 session_id
+ # 在响应中返回 session_id 和 title
response_dict = response.dict()
response_dict["session_id"] = session_id
+ response_dict["session_title"] = session_title
return response_dict
@app.post("/agent/chat/stream")
@@ -2872,9 +3008,21 @@ async def agent_chat_stream(chat_request: AgentChatRequest, request: Request):
f"subscription_type: {user_subscription}"
)
- # 如果没有提供 session_id，创建新会话
+ # 判断是否是新会话
+ is_new_session = not chat_request.session_id
session_id = chat_request.session_id or str(uuid.uuid4())
+ # ==================== 加载历史对话（多轮对话记忆）====================
+ chat_history = []
+ if not is_new_session:
+ try:
+ # 加载该会话的历史消息（最近 20 条）
+ history = es_client.get_chat_history(session_id, limit=20)
+ chat_history = history
+ logger.info(f"[Stream] 已加载 {len(chat_history)} 条历史消息")
+ except Exception as e:
+ logger.error(f"[Stream] 加载历史消息失败: {e}")
+
# 保存用户消息到 ES
try:
es_client.save_chat_message(
@@ -2884,6 +3032,7 @@ async def agent_chat_stream(chat_request: AgentChatRequest, request: Request):
user_avatar=chat_request.user_avatar or "",
message_type="user",
message=chat_request.message,
+ is_first_message=is_new_session, # 标记是否为首条消息
)
logger.info(f"[ES] 用户消息已保存到会话 {session_id}")
except Exception as e:
@@ -2940,6 +3089,8 @@ async def agent_chat_stream(chat_request: AgentChatRequest, request: Request):
user_avatar=chat_request.user_avatar,
cookies=cookies, # 传递 cookies 用于认证 API 调用
model_config=model_config, # 传递选中的模型配置
+ chat_history=chat_history, # 传递历史对话（多轮对话记忆）
+ is_new_session=is_new_session, # 传递是否是新会话（用于生成标题）
),
media_type="text/event-stream",
headers={
diff --git a/src/views/AgentChat/components/LeftSidebar/SessionCard.js b/src/views/AgentChat/components/LeftSidebar/SessionCard.js
index 63a4ef23..4e3f4d6c 100644
--- a/src/views/AgentChat/components/LeftSidebar/SessionCard.js
+++ b/src/views/AgentChat/components/LeftSidebar/SessionCard.js
@@ -40,16 +40,22 @@ const SessionCard = ({ session, isActive, onPress }) => {
-
- {session.title || '新对话'}
+
+ {session.title || session.last_message?.substring(0, 30) || '新对话'}
- {new Date(session.created_at || session.timestamp).toLocaleString('zh-CN', {
- month: 'numeric',
- day: 'numeric',
- hour: '2-digit',
- minute: '2-digit',
- })}
+ {(() => {
+ const dateStr = session.created_at || session.last_timestamp || session.timestamp;
+ if (!dateStr) return '刚刚';
+ const date = new Date(dateStr);
+ if (isNaN(date.getTime())) return '刚刚';
+ return date.toLocaleString('zh-CN', {
+ month: 'numeric',
+ day: 'numeric',
+ hour: '2-digit',
+ minute: '2-digit',
+ });
+ })()}
{session.message_count && (