feat(agent, memory): add agent-perceived memory writing

api/app/services/app_chat_service.py

@@ -10,6 +10,7 @@ from sqlalchemy.orm import Session
 
 from app.core.agent.langchain_agent import LangChainAgent
 from app.core.logging_config import get_business_logger
+from app.core.memory.agent.langgraph_graph.write_graph import write_long_term
 from app.db import get_db
 from app.models import MultiAgentConfig, AgentConfig, ModelType
 from app.models import WorkflowConfig
@@ -20,11 +21,11 @@ from app.schemas.model_schema import ModelInfo
 from app.schemas.prompt_schema import render_prompt_message, PromptMessageRole
 from app.services.conversation_service import ConversationService
 from app.services.draft_run_service import AgentRunService
+from app.services.memory_agent_service import get_end_user_connected_config
 from app.services.model_service import ModelApiKeyService
 from app.services.multi_agent_orchestrator import MultiAgentOrchestrator
 from app.services.multimodal_service import MultimodalService
 from app.services.workflow_service import WorkflowService
-from app.schemas import FileType
 
 logger = get_business_logger()
 
@@ -43,18 +44,17 @@ class AppChatService:
             message: str,
             conversation_id: uuid.UUID,
             config: AgentConfig,
-            user_id: Optional[str] = None,
+            files: list[FileInput],
+            user_id: str,
             variables: Optional[Dict[str, Any]] = None,
             web_search: bool = False,
             memory: bool = True,
             storage_type: Optional[str] = None,
             user_rag_memory_id: Optional[str] = None,
-            workspace_id: Optional[str] = None,
-            files: Optional[List[FileInput]] = None
+            workspace_id: Optional[str] = None
     ) -> Dict[str, Any]:
         """聊天（非流式）"""
         start_time = time.time()
-        config_id = None
 
         # 应用 features 配置
         features_config: dict = config.features or {}
@@ -93,7 +93,8 @@ class AppChatService:
         tools.extend(skill_tools)
         if skill_prompts:
             system_prompt = f"{system_prompt}\n\n{skill_prompts}"
-        kb_tools, citations_collector = self.agent_service.load_knowledge_retrieval_config(config.knowledge_retrieval, user_id)
+        kb_tools, citations_collector = self.agent_service.load_knowledge_retrieval_config(config.knowledge_retrieval,
+                                                                                           user_id)
         tools.extend(kb_tools)
         memory_flag = False
         if memory:
@@ -168,11 +169,6 @@ class AppChatService:
             message=message,
             history=history,
             context=None,
-            end_user_id=user_id,
-            storage_type=storage_type,
-            user_rag_memory_id=user_rag_memory_id,
-            config_id=config_id,
-            memory_flag=memory_flag,
             files=processed_files  # 传递处理后的文件
         )
 
@@ -229,6 +225,21 @@ class AppChatService:
         # 保存消息
         if audio_url:
             assistant_meta["audio_url"] = audio_url
+        if memory_flag:
+            connected_config = get_end_user_connected_config(user_id, self.db)
+            memory_config_id: str = connected_config.get("memory_config_id")
+            messages = [
+                {"role": "user", "content": message, "files": [file.model_dump() for file in files]},
+                {"role": "assistant", "content": result["content"]}
+            ]
+            if memory_config_id:
+                await write_long_term(
+                    storage_type,
+                    user_id,
+                    messages,
+                    user_rag_memory_id,
+                    memory_config_id
+                )
         self.conversation_service.add_message(
             conversation_id=conversation_id,
             role="user",
@@ -264,20 +275,19 @@ class AppChatService:
             message: str,
             conversation_id: uuid.UUID,
             config: AgentConfig,
+            files: list[FileInput],
             user_id: Optional[str] = None,
             variables: Optional[Dict[str, Any]] = None,
             web_search: bool = False,
             memory: bool = True,
             storage_type: Optional[str] = None,
             user_rag_memory_id: Optional[str] = None,
-            workspace_id: Optional[str] = None,
-            files: Optional[List[FileInput]] = None
+            workspace_id: Optional[str] = None
     ) -> AsyncGenerator[str, None]:
         """聊天（流式）"""
 
         try:
             start_time = time.time()
-            config_id = None
             message_id = uuid.uuid4()
 
             # 应用 features 配置
@@ -319,7 +329,8 @@ class AppChatService:
             tools.extend(skill_tools)
             if skill_prompts:
                 system_prompt = f"{system_prompt}\n\n{skill_prompts}"
-            kb_tools, citations_collector = self.agent_service.load_knowledge_retrieval_config(config.knowledge_retrieval, user_id)
+            kb_tools, citations_collector = self.agent_service.load_knowledge_retrieval_config(
+                config.knowledge_retrieval, user_id)
             tools.extend(kb_tools)
             # 添加长期记忆工具
             memory_flag = False
@@ -411,11 +422,6 @@ class AppChatService:
                     message=message,
                     history=history,
                     context=None,
-                    end_user_id=user_id,
-                    storage_type=storage_type,
-                    user_rag_memory_id=user_rag_memory_id,
-                    config_id=config_id,
-                    memory_flag=memory_flag,
                     files=processed_files
             ):
                 if isinstance(chunk, int):
@@ -459,7 +465,7 @@ class AppChatService:
 
             # 保存消息
             human_meta = {
-                "files":[],
+                "files": [],
                 "history_files": {}
             }
             assistant_meta = {
@@ -484,6 +490,22 @@ class AppChatService:
 
             if stream_audio_url:
                 assistant_meta["audio_url"] = stream_audio_url
+
+            if memory_flag:
+                connected_config = get_end_user_connected_config(user_id, self.db)
+                memory_config_id: str = connected_config.get("memory_config_id")
+                messages = [
+                    {"role": "user", "content": message, "files": [file.model_dump() for file in files]},
+                    {"role": "assistant", "content": full_content}
+                ]
+                if memory_config_id:
+                    await write_long_term(
+                        storage_type,
+                        user_id,
+                        messages,
+                        user_rag_memory_id,
+                        memory_config_id
+                    )
             self.conversation_service.add_message(
                 conversation_id=conversation_id,
                 role="user",
@@ -618,7 +640,6 @@ class AppChatService:
             # 2. 创建编排器
             orchestrator = MultiAgentOrchestrator(self.db, config)
 
-
             # 3. 流式执行任务
             async for event in orchestrator.execute_stream(
                     message=message,