feat: AI聊天室多Agent协作讨论平台

- 实现Agent管理，支持AI辅助生成系统提示词
- 支持多个AI提供商（OpenRouter、智谱、MiniMax等）
- 实现聊天室和讨论引擎
- WebSocket实时消息推送
- 前端使用React + Ant Design
- 后端使用FastAPI + MongoDB

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>

backend/models/message.py

@@ -0,0 +1,123 @@
+"""
+消息数据模型
+定义聊天消息的结构
+"""
+from datetime import datetime
+from typing import Optional, Dict, Any, List
+from enum import Enum
+from pydantic import Field
+from beanie import Document
+
+
+class MessageType(str, Enum):
+    """消息类型枚举"""
+    TEXT = "text"               # 纯文本
+    IMAGE = "image"             # 图片
+    FILE = "file"               # 文件
+    SYSTEM = "system"           # 系统消息
+    ACTION = "action"           # 动作消息（如调用工具）
+
+
+class MessageAttachment:
+    """消息附件"""
+    attachment_type: str        # 附件类型: image, file
+    url: str                    # 资源URL
+    name: str                   # 文件名
+    size: int = 0               # 文件大小(字节)
+    mime_type: str = ""         # MIME类型
+    
+    def __init__(
+        self,
+        attachment_type: str,
+        url: str,
+        name: str,
+        size: int = 0,
+        mime_type: str = ""
+    ):
+        self.attachment_type = attachment_type
+        self.url = url
+        self.name = name
+        self.size = size
+        self.mime_type = mime_type
+    
+    def to_dict(self) -> Dict[str, Any]:
+        """转换为字典"""
+        return {
+            "attachment_type": self.attachment_type,
+            "url": self.url,
+            "name": self.name,
+            "size": self.size,
+            "mime_type": self.mime_type
+        }
+    
+    @classmethod
+    def from_dict(cls, data: Dict[str, Any]) -> "MessageAttachment":
+        """从字典创建"""
+        return cls(
+            attachment_type=data.get("attachment_type", ""),
+            url=data.get("url", ""),
+            name=data.get("name", ""),
+            size=data.get("size", 0),
+            mime_type=data.get("mime_type", "")
+        )
+
+
+class Message(Document):
+    """
+    消息文档模型
+    存储聊天消息
+    """
+    message_id: str = Field(..., description="唯一标识")
+    room_id: str = Field(..., description="聊天室ID")
+    discussion_id: str = Field(..., description="讨论ID")
+    agent_id: Optional[str] = Field(default=None, description="发送Agent ID(系统消息为空)")
+    
+    # 消息内容
+    content: str = Field(..., description="消息内容")
+    message_type: str = Field(default=MessageType.TEXT.value, description="消息类型")
+    attachments: List[Dict[str, Any]] = Field(default_factory=list, description="附件列表")
+    
+    # 元数据
+    round: int = Field(default=0, description="所属轮次")
+    token_count: int = Field(default=0, description="token数量")
+    
+    # 工具调用相关
+    tool_calls: List[Dict[str, Any]] = Field(default_factory=list, description="工具调用记录")
+    tool_results: List[Dict[str, Any]] = Field(default_factory=list, description="工具调用结果")
+    
+    # 时间戳
+    created_at: datetime = Field(default_factory=datetime.utcnow)
+    
+    class Settings:
+        name = "messages"
+        indexes = [
+            [("room_id", 1), ("created_at", 1)],
+            [("discussion_id", 1)],
+            [("agent_id", 1)],
+        ]
+    
+    def get_attachments(self) -> List[MessageAttachment]:
+        """获取附件对象列表"""
+        return [MessageAttachment.from_dict(a) for a in self.attachments]
+    
+    def is_from_agent(self, agent_id: str) -> bool:
+        """检查消息是否来自指定Agent"""
+        return self.agent_id == agent_id
+    
+    def is_system_message(self) -> bool:
+        """检查是否为系统消息"""
+        return self.message_type == MessageType.SYSTEM.value
+    
+    class Config:
+        json_schema_extra = {
+            "example": {
+                "message_id": "msg-001",
+                "room_id": "product-design-room",
+                "discussion_id": "disc-001",
+                "agent_id": "product-manager",
+                "content": "我认为登录系统应该支持多种认证方式...",
+                "message_type": "text",
+                "round": 1,
+                "token_count": 150
+            }
+        }