feat(app):

1. Handling the storage of multimodal messages and adapting to the loading of historical messages for multi-round conversations;
2. Obtain the interface for retrieving the voice status of the reply;
3. File Information Retrieval Interface

api/app/services/app_chat_service.py

@@ -119,14 +119,12 @@ class AppChatService:
         )
 
         # 加载历史消息
-        messages = self.conversation_service.get_messages(
+        history = self.conversation_service.get_conversation_history(
             conversation_id=conversation_id,
-            limit=10
+            max_history=10,
+            current_provider=api_key_obj.provider,
+            current_is_omni=api_key_obj.is_omni
         )
-        history = [
-            {"role": msg.role, "content": msg.content}
-            for msg in messages
-        ]
 
         # 处理多模态文件
         processed_files = None
@@ -180,7 +178,8 @@ class AppChatService:
 
         # 构建用户消息内容（含多模态文件）
         human_meta = {
-            "files": []
+            "files": [],
+            "history_files": {}
         }
         assistant_meta = {
             "model": api_key_obj.model_name,
@@ -195,6 +194,13 @@ class AppChatService:
                     "url": f.url
                 })
 
+        if processed_files:
+            human_meta["history_files"] = {
+                "content": processed_files,
+                "provider": api_key_obj.provider,
+                "is_omni": api_key_obj.is_omni
+            }
+
         # 保存消息
         if audio_url:
             assistant_meta["audio_url"] = audio_url
@@ -225,6 +231,7 @@ class AppChatService:
             "suggested_questions": suggested_questions,
             "citations": self.agent_service._filter_citations(features_config, result.get("citations", [])),
             "audio_url": audio_url,
+            "audio_status": "pending"
         }
 
     async def agnet_chat_stream(
@@ -314,17 +321,12 @@ class AppChatService:
             )
 
             # 加载历史消息
-            history = []
-            memory_config = {"enabled": True, 'max_history': 10}
-            if memory_config.get("enabled"):
-                messages = self.conversation_service.get_messages(
-                    conversation_id=conversation_id,
-                    limit=memory_config.get("max_history", 10)
-                )
-                history = [
-                    {"role": msg.role, "content": msg.content}
-                    for msg in messages
-                ]
+            history = self.conversation_service.get_conversation_history(
+                conversation_id=conversation_id,
+                max_history=10,
+                current_provider=api_key_obj.provider,
+                current_is_omni=api_key_obj.is_omni
+            )
 
             # 处理多模态文件
             processed_files = None
@@ -347,8 +349,14 @@ class AppChatService:
             total_tokens = 0
 
             text_queue: asyncio.Queue = asyncio.Queue()
+            api_key_config = {
+                "model_name": api_key_obj.model_name,
+                "api_key": api_key_obj.api_key,
+                "api_base": api_key_obj.api_base,
+                "provider": api_key_obj.provider,
+            }
             stream_audio_url, tts_task = await self.agent_service._generate_tts_streaming(
-                features_config, api_key_obj,
+                features_config, api_key_config,
                 text_queue=text_queue,
                 tenant_id=tenant_id, workspace_id=workspace_id
             )
@@ -378,7 +386,7 @@ class AppChatService:
             elapsed_time = time.time() - start_time
             ModelApiKeyService.record_api_key_usage(self.db, api_key_obj.id)
 
-            # 发送结束事件（包含 suggested_questions、tts、citations）
+            # 发送结束事件（包含 suggested_questions、tts、audio_status、citations）
             end_data: dict = {"elapsed_time": elapsed_time, "message_length": len(full_content), "error": None}
             sq_config = features_config.get("suggested_questions_after_answer", {})
             if isinstance(sq_config, dict) and sq_config.get("enabled"):
@@ -388,11 +396,23 @@ class AppChatService:
                      "api_base": api_key_obj.api_base}, {}
                 )
             end_data["audio_url"] = stream_audio_url
+            # 检查TTS是否已完成（非阻塞，不取消任务）
+            audio_status = "pending"
+            if tts_task is not None and tts_task.done():
+                # 任务已完成，检查是否有异常
+                try:
+                    tts_task.result()
+                    audio_status = "completed"
+                except Exception as e:
+                    logger.warning(f"TTS任务异常: {e}")
+                    audio_status = "failed"
+            end_data["audio_status"] = audio_status if stream_audio_url else None
             end_data["citations"] = self.agent_service._filter_citations(features_config, [])
 
             # 保存消息
             human_meta = {
-                "files":[]
+                "files":[],
+                "history_files": {}
             }
             assistant_meta = {
                 "model": api_key_obj.model_name,
@@ -402,11 +422,16 @@ class AppChatService:
 
             if files:
                 for f in files:
-                    # url = await MultimodalService(self.db).get_file_url(f)
                     human_meta["files"].append({
                         "type": f.type,
                         "url": f.url
                     })
+            if processed_files:
+                human_meta["history_files"] = {
+                    "content": processed_files,
+                    "provider": api_key_obj.provider,
+                    "is_omni": api_key_obj.is_omni
+                }
 
             if stream_audio_url:
                 assistant_meta["audio_url"] = stream_audio_url

api/app/services/conversation_service.py

@@ -119,25 +119,27 @@ class ConversationService:
 
     def get_user_conversations(
             self,
-            user_id: uuid.UUID
-    ) -> list[Conversation]:
+            user_id: uuid.UUID,
+            page: int = 1,
+            page_size: int = 20
+    ) -> tuple[list[Conversation], int]:
         """
-        Retrieve recent conversations for a specific user
-
-        This method delegates persistence logic to the repository layer and
-        applies service-level defaults (e.g. recent conversation limit).
+        Retrieve recent conversations for a specific user with pagination.
 
         Args:
             user_id (uuid.UUID): Unique identifier of the user.
+            page (int): Page number (1-based). Defaults to 1.
+            page_size (int): Number of items per page. Defaults to 20.
 
         Returns:
-            list[Conversation]: A list of recent conversation entities.
+            tuple[list[Conversation], int]: A list of recent conversation entities and total count.
         """
-        conversations = self.conversation_repo.get_conversation_by_user_id(
+        conversations, total = self.conversation_repo.get_conversation_by_user_id(
             user_id,
-            limit=10
+            page=page,
+            page_size=page_size
         )
-        return conversations
+        return conversations, total
 
     def list_conversations(
             self,
@@ -270,7 +272,9 @@ class ConversationService:
     def get_conversation_history(
             self,
             conversation_id: uuid.UUID,
-            max_history: Optional[int] = None
+            max_history: Optional[int] = None,
+            current_provider: Optional[str] = None,
+            current_is_omni: Optional[bool] = None
     ) -> List[dict]:
         """
         Retrieve historical conversation messages formatted as dictionaries.
@@ -278,6 +282,8 @@ class ConversationService:
         Args:
             conversation_id (uuid.UUID): Conversation UUID.
             max_history (Optional[int]): Maximum number of messages to retrieve.
+            current_provider (Optional[str]): Current provider for file handling.
+            current_is_omni (Optional[bool]): Current omni flag for file handling.
 
         Returns:
             List[dict]: List of message dictionaries with keys 'role' and 'content'.
@@ -287,14 +293,30 @@ class ConversationService:
             limit=max_history
         )
 
-        # 转换为字典格式
-        history = [
-            {
+        history = []
+        for msg in messages:
+            msg_dict = {
                 "role": msg.role,
-                "content": msg.content
+                "content": [{"type": "text", "text": msg.content}]
             }
-            for msg in messages
-        ]
+
+            # 处理用户消息中的多模态文件
+            if msg.role == "user" and msg.meta_data:
+                history_files = msg.meta_data.get("history_files", {})
+
+                if history_files and current_provider and current_is_omni is not None:
+                    # 检查是否需要重新处理文件
+                    stored_provider = history_files.get("provider")
+                    stored_is_omni = history_files.get("is_omni")
+
+                    # 如果provider或is_omni不匹配，需要重新处理
+                    if stored_provider != current_provider or stored_is_omni != current_is_omni:
+                        continue
+
+                    # provider和is_omni匹配，直接使用存储的内容
+                    msg_dict["content"].extend(history_files.get("content"))
+
+            history.append(msg_dict)
 
         return history
 
@@ -510,6 +532,7 @@ class ConversationService:
         provider = api_config.provider
         api_key = api_config.api_key
         api_base = api_config.api_base
+        is_omni = api_config.is_omni
         model_type = config.type
 
         llm = RedBearLLM(
@@ -517,14 +540,17 @@ class ConversationService:
                 model_name=model_name,
                 provider=provider,
                 api_key=api_key,
-                base_url=api_base
+                base_url=api_base,
+                is_omni=is_omni
             ),
             type=ModelType(model_type)
         )
 
         conversation_messages = self.get_conversation_history(
             conversation_id=conversation_id,
-            max_history=20
+            max_history=20,
+            current_provider=provider,
+            current_is_omni=is_omni
         )
         if len(conversation_messages) == 0:
             return ConversationOut(

api/app/services/draft_run_service.py

@@ -582,7 +582,9 @@ class AgentRunService:
             # 6. 加载历史消息
             history = await self._load_conversation_history(
                 conversation_id=conversation_id,
-                max_history=10
+                max_history=10,
+                current_provider=api_key_config.get("provider"),
+                current_is_omni=api_key_config.get("is_omni", False)
             )
 
             # 6. 处理多模态文件
@@ -659,7 +661,10 @@ class AgentRunService:
                         })
                     },
                     files=files,
-                    audio_url=audio_url
+                    processed_files=processed_files,
+                    audio_url=audio_url,
+                    provider=api_key_config.get("provider"),
+                    is_omni=api_key_config.get("is_omni", False)
                 )
 
             response = {
@@ -676,6 +681,7 @@ class AgentRunService:
                 ) if not sub_agent else [],
                 "citations": self._filter_citations(features_config, result.get("citations", [])),
                 "audio_url": audio_url,
+                "audio_status": "pending"
             }
 
             logger.info(
@@ -818,7 +824,9 @@ class AgentRunService:
             # 6. 加载历史消息
             history = await self._load_conversation_history(
                 conversation_id=conversation_id,
-                max_history=memory_config.get("max_history", 10)
+                max_history=memory_config.get("max_history", 10),
+                current_provider=api_key_config.get("provider"),
+                current_is_omni=api_key_config.get("is_omni", False)
             )
 
             # 6. 处理多模态文件
@@ -905,10 +913,13 @@ class AgentRunService:
                         "usage": {"prompt_tokens": 0, "completion_tokens": 0, "total_tokens": total_tokens}
                     },
                     files=files,
-                    audio_url=stream_audio_url
+                    processed_files=processed_files,
+                    audio_url=stream_audio_url,
+                    provider=api_key_config.get("provider"),
+                    is_omni=api_key_config.get("is_omni", False)
                 )
 
-            # 12. 发送结束事件（包含 suggested_questions 和 tts）
+            # 12. 发送结束事件（包含 suggested_questions、audio_url 和 audio_status）
             end_data: Dict[str, Any] = {
                 "conversation_id": conversation_id,
                 "elapsed_time": elapsed_time,
@@ -919,6 +930,17 @@ class AgentRunService:
                     features_config, full_content, api_key_config, effective_params
                 )
                 end_data["audio_url"] = stream_audio_url
+                # 检查TTS是否已完成（非阻塞，不取消任务）
+                audio_status = "pending"
+                if tts_task is not None and tts_task.done():
+                    # 任务已完成，检查是否有异常
+                    try:
+                        tts_task.result()
+                        audio_status = "completed"
+                    except Exception as e:
+                        logger.warning(f"TTS任务异常: {e}")
+                        audio_status = "failed"
+                end_data["audio_status"] = audio_status if stream_audio_url else None
                 end_data["citations"] = self._filter_citations(features_config, [])
             yield self._format_sse_event("end", end_data)
 
@@ -1115,13 +1137,17 @@ class AgentRunService:
     async def _load_conversation_history(
             self,
             conversation_id: str,
-            max_history: int = 10
+            max_history: int = 10,
+            current_provider: Optional[str] = None,
+            current_is_omni: Optional[bool] = None
     ) -> List[Dict[str, str]]:
-        """加载会话历史消息
+        """加载会话历史消息，并根据当前模型配置处理多模态文件
 
         Args:
             conversation_id: 会话ID
             max_history: 最大历史消息数量
+            current_provider: 当前模型的provider
+            current_is_omni: 当前模型的is_omni
 
         Returns:
             List[Dict]: 历史消息列表
@@ -1131,7 +1157,9 @@ class AgentRunService:
             conversation_service = ConversationService(self.db)
             history = conversation_service.get_conversation_history(
                 conversation_id=uuid.UUID(conversation_id),
-                max_history=max_history
+                max_history=max_history,
+                current_provider=current_provider,
+                current_is_omni=current_is_omni
             )
 
             logger.debug(
@@ -1159,7 +1187,10 @@ class AgentRunService:
             app_id: Optional[uuid.UUID] = None,
             user_id: Optional[str] = None,
             files: Optional[List[FileInput]] = None,
-            audio_url: Optional[str] = None
+            processed_files: Optional[List[Dict[str, Any]]] = None,
+            audio_url: Optional[str] = None,
+            provider: Optional[str] = None,
+            is_omni: Optional[bool] = None
     ) -> None:
         """保存会话消息（会话已通过 _ensure_conversation 确保存在）
 
@@ -1170,6 +1201,11 @@ class AgentRunService:
             app_id: 应用ID（未使用，保留用于兼容性）
             user_id: 用户ID（未使用，保留用于兼容性）
             meta_data: token消耗
+            files: 原始文件输入
+            processed_files: 处理后的文件
+            audio_url: 音频URL
+            provider: 模型供应商
+            is_omni: 是否为全模态模型
         """
         try:
             from app.services.conversation_service import ConversationService
@@ -1179,15 +1215,24 @@ class AgentRunService:
 
             # 保存消息（会话已经存在）
             human_meta = {
-                "files": []
+                "files": [],
+                "history_files": {}
             }
             if files:
                 for f in files:
-                    # url = await MultimodalService(self.db).get_file_url(f)
                     human_meta["files"].append({
                         "type": f.type,
                         "url": f.url
                     })
+
+            # 保存 history_files，包含 provider 和 is_omni 信息
+            if processed_files:
+                human_meta["history_files"] = {
+                    "content": processed_files,
+                    "provider": provider,
+                    "is_omni": is_omni
+                }
+
             # 保存用户消息
             conversation_service.add_message(
                 conversation_id=conv_uuid,
@@ -1413,8 +1458,9 @@ class AgentRunService:
             workspace_id: Optional[uuid.UUID] = None,
     ) -> tuple[Optional[str], Optional[asyncio.Task]]:
         """文本流式输入并行合成音频。
-        返回 (audio_url, task)，audio_url 立即可用，task 完成后文件内容就绪。
+        返回 (audio_url, task)，audio_url 立即可用（pending状态），task 完成后文件内容就绪。
         调用方向 text_queue put 文本 chunk，结束时 put None。
+        前端可通过 GET /storage/files/{file_id}/status 轮询检查音频是否就绪。
         """
         tts_config = features_config.get("text_to_speech", {})
         if not isinstance(tts_config, dict) or not tts_config.get("enabled"):
@@ -1801,6 +1847,7 @@ class AgentRunService:
                     ),
                     "cost_estimate": self._estimate_cost(usage, model_info["model_config"]),
                     "audio_url": result.get("audio_url"),
+                    "audio_status": result.get("audio_status"),
                     "citations": result.get("citations", []),
                     "suggested_questions": result.get("suggested_questions", []),
                     "error": None
@@ -1878,6 +1925,7 @@ class AgentRunService:
             "results": [{
                 **r,
                 "audio_url": r.get("audio_url"),
+                "audio_status": r.get("audio_status"),
                 "citations": r.get("citations", []),
                 "suggested_questions": r.get("suggested_questions", []),
             } for r in results],
@@ -2009,6 +2057,7 @@ class AgentRunService:
                 full_content = ""
                 returned_conversation_id = model_conversation_id
                 audio_url = None
+                audio_status = None
                 citations = []
                 suggested_questions = []
 
@@ -2067,6 +2116,7 @@ class AgentRunService:
                             # 从 end 事件中提取 features 输出字段
                             if event_type == "end" and event_data:
                                 audio_url = event_data.get("audio_url")
+                                audio_status = event_data.get("audio_status")
                                 citations = event_data.get("citations", [])
                                 suggested_questions = event_data.get("suggested_questions", [])
 
@@ -2096,6 +2146,7 @@ class AgentRunService:
                     "message": full_content,
                     "elapsed_time": elapsed,
                     "audio_url": audio_url,
+                    "audio_status": audio_status,
                     "citations": citations,
                     "suggested_questions": suggested_questions,
                     "error": None
@@ -2110,6 +2161,7 @@ class AgentRunService:
                     "elapsed_time": elapsed,
                     "message_length": len(full_content),
                     "audio_url": audio_url,
+                    "audio_status": audio_status,
                     "citations": citations,
                     "suggested_questions": suggested_questions,
                     "timestamp": time.time()
@@ -2246,6 +2298,7 @@ class AgentRunService:
                 "message": r.get("message"),
                 "elapsed_time": r.get("elapsed_time", 0),
                 "audio_url": r.get("audio_url"),
+                "audio_status": r.get("audio_status"),
                 "citations": r.get("citations", []),
                 "suggested_questions": r.get("suggested_questions", []),
                 "error": r.get("error")