Release/v0.2.3 (#281)

* feat(app and model): token consumption statistics of the cluster

* fix(web): prompt history remove pageLoading

* fix(prompt): remove hard-coded import of prompt file paths (#279)

* Fix/develop memory bug (#274)

* 遗漏的历史映射

* 遗漏的历史映射

* fix_timeline_memories

* fix(web): update retrieve_type key

* Fix/develop memory bug (#276)

* 遗漏的历史映射

* 遗漏的历史映射

* fix_timeline_memories

* fix_timeline_memories

* write_gragp/bug_fix

* write_gragp/bug_fix

* write_gragp/bug_fix

* chore(celery): disable periodic task scheduling

* fix(prompt): remove hard-coded import of prompt file paths

---------

Co-authored-by: lixinyue11 <94037597+lixinyue11@users.noreply.github.com>
Co-authored-by: zhaoying <yzhao96@best-inc.com>
Co-authored-by: yingzhao <zhaoyingyz@126.com>
Co-authored-by: Ke Sun <kesun5@illinois.edu>

---------

Co-authored-by: Timebomb2018 <18868801967@163.com>
Co-authored-by: Mark <zhuwenhui5566@163.com>
Co-authored-by: zhaoying <yzhao96@best-inc.com>
Co-authored-by: Eternity <61316157+myhMARS@users.noreply.github.com>
Co-authored-by: lixinyue11 <94037597+lixinyue11@users.noreply.github.com>
Co-authored-by: yingzhao <zhaoyingyz@126.com>

api/app/services/app_chat_service.py

@@ -427,7 +427,11 @@ class AppChatService:
             meta_data={
                 "mode": result.get("mode"),
                 "elapsed_time": result.get("elapsed_time"),
-                "sub_results": result.get("sub_results")
+                "usage": result.get("usage", {
+                            "prompt_tokens": 0,
+                            "completion_tokens": 0,
+                            "total_tokens": 0
+                        })
             }
         )
 
@@ -469,6 +473,7 @@ class AppChatService:
             yield f"event: start\ndata: {json.dumps({'conversation_id': str(conversation_id)}, ensure_ascii=False)}\n\n"
 
             full_content = ""
+            total_tokens = 0
 
             # 2. 创建编排器
             orchestrator = MultiAgentOrchestrator(self.db, config)
@@ -485,16 +490,26 @@ class AppChatService:
                     storage_type=storage_type,
                     user_rag_memory_id=user_rag_memory_id
             ):
-                yield event
+                if "sub_usage" in event:
-                # 尝试提取内容（用于保存）
+                    if "data:" in event:
-                if "data:" in event:
+                        try:
-                    try:
+                            data_line = event.split("data: ", 1)[1].strip()
-                        data_line = event.split("data: ", 1)[1].strip()
+                            data = json.loads(data_line)
-                        data = json.loads(data_line)
+                            if "total_tokens" in data:
-                        if "content" in data:
+                                total_tokens += data["total_tokens"]
-                            full_content += data["content"]
+                        except:
-                    except:
+                            pass
-                        pass
+                else:
+                    yield event
+                    # 尝试提取内容（用于保存）
+                    if "data:" in event:
+                        try:
+                            data_line = event.split("data: ", 1)[1].strip()
+                            data = json.loads(data_line)
+                            if "content" in data:
+                                full_content += data["content"]
+                        except:
+                            pass
 
             elapsed_time = time.time() - start_time
 
@@ -510,7 +525,12 @@ class AppChatService:
                 role="assistant",
                 content=full_content,
                 meta_data={
-                    "elapsed_time": elapsed_time
+                    "elapsed_time": elapsed_time,
+                    "usage": {
+                        "prompt_tokens": 0,
+                        "completion_tokens": 0,
+                        "total_tokens": total_tokens
+                    }
                 }
             )
 

api/app/services/conversation_service.py

@@ -1,4 +1,5 @@
 """会话服务"""
+import os
 import uuid
 from datetime import datetime, timedelta
 from typing import Annotated
@@ -529,12 +530,12 @@ class ConversationService:
                 takeaways=[],
                 info_score=0,
             )
-
+        prompt_path = os.path.join(os.path.dirname(os.path.abspath(__file__)), 'prompt')
-        with open('app/services/prompt/conversation_summary_system.jinja2', 'r', encoding='utf-8') as f:
+        with open(os.path.join(prompt_path, 'conversation_summary_system.jinja2'), 'r', encoding='utf-8') as f:
             system_prompt = f.read()
         rendered_system_message = Template(system_prompt).render()
 
-        with open('app/services/prompt/conversation_summary_user.jinja2', 'r', encoding='utf-8') as f:
+        with open(os.path.join(prompt_path, 'conversation_summary_user.jinja2'), 'r', encoding='utf-8') as f:
             user_prompt = f.read()
         rendered_user_message = Template(user_prompt).render(
             language=language,

api/app/services/draft_run_service.py

@@ -678,6 +678,11 @@ class DraftRunService:
 
             elapsed_time = time.time() - start_time
 
+            if sub_agent:
+                yield self._format_sse_event("sub_usage", {
+                        "total_tokens": total_tokens
+                    })
+
             # 10. 保存会话消息
             if not sub_agent and agent_config.memory and agent_config.memory.get("enabled"):
                 await self._save_conversation_message(

api/app/services/handoffs_service.py

@@ -4,7 +4,7 @@ import uuid
 from typing import List, Dict, Any, Optional, AsyncGenerator, Annotated
 from typing_extensions import TypedDict
 
-from langchain_core.messages import HumanMessage, AIMessage, BaseMessage
+from langchain_core.messages import HumanMessage, AIMessage, BaseMessage, AIMessageChunk
 from langgraph.graph import StateGraph, START, END
 from langgraph.types import Command
 from langgraph.checkpoint.memory import MemorySaver
@@ -727,9 +727,12 @@ class HandoffsService:
         
         # 提取响应
         response_content = ""
+        total_tokens = 0
         for msg in result.get("messages", []):
             if isinstance(msg, AIMessage):
                 response_content = msg.content
+                response_meta = msg.response_metadata if hasattr(msg, 'response_metadata') else None
+                total_tokens = response_meta.get("token_usage", {}).get("total_tokens", 0) if response_meta else 0
                 break
         
         return {
@@ -737,7 +740,12 @@ class HandoffsService:
             "active_agent": result.get("active_agent"),
             "response": response_content,
             "message_count": len(result.get("messages", [])),
-            "handoff_count": result.get("handoff_count", 0)
+            "handoff_count": result.get("handoff_count", 0),
+            "usage": {
+                    "prompt_tokens": 0,
+                    "completion_tokens": 0,
+                    "total_tokens": total_tokens
+                }
         }
     
     async def chat_stream(
@@ -830,6 +838,12 @@ class HandoffsService:
                 
                 # 捕获 LLM 结束事件，输出收集到的工具调用
                 elif kind == "on_chat_model_end":
+                    output_message = event.get("data", {}).get("output", {})
+                    if isinstance(output_message, AIMessageChunk):
+                        response_meta = output_message.response_metadata if hasattr(output_message, 'response_metadata') else None
+                        total_tokens = response_meta.get("token_usage", {}).get("total_tokens",
+                                                                                0) if response_meta else 0
+                        yield f"event: sub_usage\ndata: {json.dumps({"total_tokens": total_tokens}, ensure_ascii=False)}\n\n"
                     if collected_tool_calls:
                         # 找到参数最完整的 transfer 工具调用
                         best_tc = None

api/app/services/multi_agent_orchestrator.py

@@ -280,14 +280,22 @@ class MultiAgentOrchestrator:
 
             # 4. 提取子 Agent 的 conversation_id（用于多轮对话）
             sub_conversation_id = None
+            total_tokens = 0
+            
             if isinstance(results, dict):
                 sub_conversation_id = results.get("conversation_id") or results.get("result", {}).get("conversation_id")
+                # 提取 token 信息
+                usage = results.get("usage", {}) or results.get("result", {}).get("usage", {})
+                total_tokens += usage.get("total_tokens", 0)
             elif isinstance(results, list) and results:
                 for item in results:
                     if "result" in item:
                         sub_conversation_id = item["result"].get("conversation_id")
                         if sub_conversation_id:
                             break
+                    # 累加每个子 Agent 的 token
+                    usage = item.get("usage", {}) or item.get("result", {}).get("usage", {})
+                    total_tokens += usage.get("total_tokens", 0)
 
             logger.info(
                 "多 Agent 任务完成",
@@ -301,9 +309,15 @@ class MultiAgentOrchestrator:
             return {
                 "message": final_result,
                 "conversation_id": sub_conversation_id,
+                "mode": OrchestrationMode.SUPERVISOR,
                 "elapsed_time": elapsed_time,
                 "strategy": routing_decision.get("collaboration_strategy", "single"),
-                "sub_results": results
+                "sub_results": results,
+                "usage": {
+                    "prompt_tokens": 0,
+                    "completion_tokens": 0,
+                    "total_tokens": total_tokens
+                }
             }
 
         except Exception as e:
@@ -1552,10 +1566,12 @@ class MultiAgentOrchestrator:
             return {
                 "message": result.get("response", ""),
                 "conversation_id": result.get("conversation_id"),
+                "mode": OrchestrationMode.COLLABORATION,
                 "elapsed_time": elapsed_time,
                 "strategy": "collaboration",
                 "active_agent": result.get("active_agent"),
-                "sub_results": result
+                "sub_results": result,
+                "usage": result.get("usage")
             }
 
         except Exception as e:

api/app/services/multi_agent_service.py

@@ -1,5 +1,6 @@
 """多 Agent 配置管理服务"""
 import uuid
+import json
 from typing import Optional, List, Tuple, Any, Annotated
 
 from fastapi import Depends
@@ -427,6 +428,23 @@ class MultiAgentService:
             memory=getattr(request, 'memory', True)  # 记忆功能参数
         )
 
+        await self._save_conversation_message(
+            conversation_id=request.conversation_id,
+            user_message=request.message,
+            assistant_message=result.get("message", ""),
+            app_id=app_id,
+            user_id=request.user_id,
+            meta_data={
+                "mode": result.get("mode"),
+                "elapsed_time": result.get("elapsed_time"),
+                "usage": result.get("usage", {
+                    "prompt_tokens": 0,
+                    "completion_tokens": 0,
+                    "total_tokens": 0
+                })
+            }
+        )
+
         return result
 
     async def run_stream(
@@ -451,11 +469,14 @@ class MultiAgentService:
             raise ResourceNotFoundException("多 Agent 配置", str(app_id))
 
         if not config.is_active:
-            raise BusinessException("多 Agent 配置已禁用", BizCode.RESOURCE_DISABLED)
+            raise BusinessException("多 Agent 配置已禁用", BizCode.NOT_FOUND)
 
         # 2. 创建编排器
         orchestrator = MultiAgentOrchestrator(self.db, config)
 
+        full_content = ""
+        total_tokens = 0
+
         # 3. 流式执行任务
         async for event in orchestrator.execute_stream(
             message=request.message,
@@ -468,7 +489,88 @@ class MultiAgentService:
             storage_type=storage_type,
             user_rag_memory_id=user_rag_memory_id
         ):
-            yield event
+            if "sub_usage" in event:
+                if "data:" in event:
+                    try:
+                        data_line = event.split("data: ", 1)[1].strip()
+                        data = json.loads(data_line)
+                        if "total_tokens" in data:
+                            total_tokens += data["total_tokens"]
+                    except:
+                        pass
+            else:
+                yield event
+                if "data:" in event:
+                    try:
+                        data_line = event.split("data: ", 1)[1].strip()
+                        data = json.loads(data_line)
+                        if "content" in data:
+                            full_content += data["content"]
+                    except:
+                        pass
+
+        await self._save_conversation_message(
+            conversation_id=request.conversation_id,
+            user_message=request.message,
+            assistant_message=full_content,
+            app_id=app_id,
+            user_id=request.user_id,
+            meta_data={
+                "usage": {
+                    "prompt_tokens": 0,
+                    "completion_tokens": 0,
+                    "total_tokens": total_tokens
+                }
+            }
+        )
+
+    async def _save_conversation_message(
+        self,
+        conversation_id: uuid.UUID,
+        user_message: str,
+        assistant_message: str,
+        meta_data: dict,
+        app_id: Optional[uuid.UUID] = None,
+        user_id: Optional[str] = None
+    ) -> None:
+        """保存会话消息
+
+        Args:
+            conversation_id: 会话ID
+            user_message: 用户消息
+            assistant_message: AI 回复消息
+            meta_data: 元数据（包括 token 消耗）
+            app_id: 应用ID
+            user_id: 用户ID
+        """
+        try:
+            from app.services.conversation_service import ConversationService
+
+            conversation_service = ConversationService(self.db)
+
+            conversation_service.add_message(
+                conversation_id=conversation_id,
+                role="user",
+                content=user_message
+            )
+            conversation_service.add_message(
+                conversation_id=conversation_id,
+                role="assistant",
+                content=assistant_message,
+                meta_data=meta_data
+            )
+
+            logger.debug(
+                "保存多 Agent 会话消息",
+                extra={
+                    "conversation_id": conversation_id,
+                    "user_message_length": len(user_message),
+                    "assistant_message_length": len(assistant_message)
+                }
+            )
+
+        except Exception as e:
+            logger.warning("保存会话消息失败", extra={"error": str(e)})
 
     # def add_sub_agent(
     #     self,

api/app/services/prompt_optimizer_service.py

@@ -1,3 +1,4 @@
+import os
 import re
 import uuid
 from typing import Any, AsyncGenerator
@@ -182,11 +183,12 @@ class PromptOptimizerService:
             base_url=api_config.api_base
         ), type=ModelType(model_config.type))
         try:
-            with open('app/services/prompt/prompt_optimizer_system.jinja2', 'r', encoding='utf-8') as f:
+            prompt_path = os.path.join(os.path.dirname(os.path.abspath(__file__)), 'prompt')
+            with open(os.path.join(prompt_path, 'prompt_optimizer_system.jinja2'), 'r', encoding='utf-8') as f:
                 opt_system_prompt = f.read()
             rendered_system_message = Template(opt_system_prompt).render()
 
-            with open('app/services/prompt/prompt_optimizer_user.jinja2', 'r', encoding='utf-8') as f:
+            with open(os.path.join(prompt_path, 'prompt_optimizer_user.jinja2'), 'r', encoding='utf-8') as f:
                 opt_user_prompt = f.read()
         except FileNotFoundError:
             raise BusinessException(message="System prompt template not found", code=BizCode.NOT_FOUND)

web/src/components/PageScrollList/index.tsx

@@ -26,6 +26,7 @@ interface PageScrollListProps<T, Q = Record<string, unknown>> {
   query?: Q;
   column?: number;
   className?: string;
+  needLoading?: boolean;
 }
 const PageScrollList = forwardRef(<T, Q = Record<string, unknown>>({
   renderItem, 
@@ -33,6 +34,7 @@ const PageScrollList = forwardRef(<T, Q = Record<string, unknown>>({
   url,
   column = 4,
   className = '',
+  needLoading = true,
 }: PageScrollListProps<T, Q>, ref: React.Ref<PageScrollListRef>) => {
   useImperativeHandle(ref, () => ({
     refresh,
@@ -104,9 +106,10 @@ const PageScrollList = forwardRef(<T, Q = Record<string, unknown>>({
           dataLength={data.length}
           next={loadMoreData}
           hasMore={hasMore}
-          loader={<PageLoading />}
+          loader={needLoading ? <PageLoading /> : undefined}
           // endMessage={<Divider plain>It is all, nothing more 🤐</Divider>}
           scrollableTarget="scrollableDiv"
+          className='rb:h-full!'
         >
           {data.length > 0 ? (
             <List

web/src/styles/index.css

@@ -180,4 +180,7 @@ body {
 .x6-node foreignObject > body {
   min-height: 100%;
   max-height: 100%;
+}
+#scrollableDiv .infinite-scroll-component__outerdiv {
+  height: 100%;
 }

web/src/views/Prompt/History.tsx

@@ -50,6 +50,7 @@ const History: React.FC<{ query: HistoryQuery; edit: (item: HistoryItem) => void
         url={getPromptReleaseListUrl}
         query={query}
         column={3}
+        needLoading={false}
         renderItem={(item) => {
           const historyItem = item as unknown as HistoryItem;
           return (