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/agent.py

@@ -0,0 +1,168 @@
+"""
+Agent数据模型
+定义AI聊天代理的配置结构
+"""
+from datetime import datetime
+from typing import Optional, Dict, Any, List
+from pydantic import Field
+from beanie import Document
+
+
+class AgentCapabilities:
+    """Agent能力配置"""
+    memory_enabled: bool = False          # 是否启用记忆
+    mcp_tools: List[str] = []             # 可用的MCP工具
+    skills: List[str] = []                # 可用的技能
+    multimodal: bool = False              # 是否支持多模态
+    
+    def __init__(
+        self,
+        memory_enabled: bool = False,
+        mcp_tools: Optional[List[str]] = None,
+        skills: Optional[List[str]] = None,
+        multimodal: bool = False
+    ):
+        self.memory_enabled = memory_enabled
+        self.mcp_tools = mcp_tools or []
+        self.skills = skills or []
+        self.multimodal = multimodal
+    
+    def to_dict(self) -> Dict[str, Any]:
+        """转换为字典"""
+        return {
+            "memory_enabled": self.memory_enabled,
+            "mcp_tools": self.mcp_tools,
+            "skills": self.skills,
+            "multimodal": self.multimodal
+        }
+    
+    @classmethod
+    def from_dict(cls, data: Dict[str, Any]) -> "AgentCapabilities":
+        """从字典创建"""
+        if not data:
+            return cls()
+        return cls(
+            memory_enabled=data.get("memory_enabled", False),
+            mcp_tools=data.get("mcp_tools", []),
+            skills=data.get("skills", []),
+            multimodal=data.get("multimodal", False)
+        )
+
+
+class AgentBehavior:
+    """Agent行为配置"""
+    speak_threshold: float = 0.5          # 发言阈值(判断是否需要发言)
+    max_speak_per_round: int = 2          # 每轮最多发言次数
+    speak_style: str = "balanced"         # 发言风格: concise, balanced, detailed
+    
+    def __init__(
+        self,
+        speak_threshold: float = 0.5,
+        max_speak_per_round: int = 2,
+        speak_style: str = "balanced"
+    ):
+        self.speak_threshold = speak_threshold
+        self.max_speak_per_round = max_speak_per_round
+        self.speak_style = speak_style
+    
+    def to_dict(self) -> Dict[str, Any]:
+        """转换为字典"""
+        return {
+            "speak_threshold": self.speak_threshold,
+            "max_speak_per_round": self.max_speak_per_round,
+            "speak_style": self.speak_style
+        }
+    
+    @classmethod
+    def from_dict(cls, data: Dict[str, Any]) -> "AgentBehavior":
+        """从字典创建"""
+        if not data:
+            return cls()
+        return cls(
+            speak_threshold=data.get("speak_threshold", 0.5),
+            max_speak_per_round=data.get("max_speak_per_round", 2),
+            speak_style=data.get("speak_style", "balanced")
+        )
+
+
+class Agent(Document):
+    """
+    Agent文档模型
+    存储AI代理的配置信息
+    """
+    agent_id: str = Field(..., description="唯一标识")
+    name: str = Field(..., description="Agent名称")
+    role: str = Field(..., description="角色定义")
+    system_prompt: str = Field(..., description="系统提示词")
+    provider_id: str = Field(..., description="使用的AI接口ID")
+    
+    # 模型参数
+    temperature: float = Field(default=0.7, ge=0, le=2, description="温度参数")
+    max_tokens: int = Field(default=2000, gt=0, description="最大token数")
+    
+    # 能力配置
+    capabilities: Dict[str, Any] = Field(
+        default_factory=lambda: {
+            "memory_enabled": False,
+            "mcp_tools": [],
+            "skills": [],
+            "multimodal": False
+        },
+        description="能力配置"
+    )
+    
+    # 行为配置
+    behavior: Dict[str, Any] = Field(
+        default_factory=lambda: {
+            "speak_threshold": 0.5,
+            "max_speak_per_round": 2,
+            "speak_style": "balanced"
+        },
+        description="行为配置"
+    )
+    
+    # 外观配置
+    avatar: Optional[str] = Field(default=None, description="头像URL")
+    color: str = Field(default="#1890ff", description="代表颜色")
+    
+    # 元数据
+    enabled: bool = Field(default=True, description="是否启用")
+    created_at: datetime = Field(default_factory=datetime.utcnow)
+    updated_at: datetime = Field(default_factory=datetime.utcnow)
+    
+    class Settings:
+        name = "agents"
+    
+    def get_capabilities(self) -> AgentCapabilities:
+        """获取能力配置对象"""
+        return AgentCapabilities.from_dict(self.capabilities)
+    
+    def get_behavior(self) -> AgentBehavior:
+        """获取行为配置对象"""
+        return AgentBehavior.from_dict(self.behavior)
+    
+    class Config:
+        json_schema_extra = {
+            "example": {
+                "agent_id": "product-manager",
+                "name": "产品经理",
+                "role": "产品规划和需求分析专家",
+                "system_prompt": "你是一位经验丰富的产品经理，擅长分析用户需求...",
+                "provider_id": "openrouter-gpt4",
+                "temperature": 0.7,
+                "max_tokens": 2000,
+                "capabilities": {
+                    "memory_enabled": True,
+                    "mcp_tools": ["web_search"],
+                    "skills": [],
+                    "multimodal": False
+                },
+                "behavior": {
+                    "speak_threshold": 0.5,
+                    "max_speak_per_round": 2,
+                    "speak_style": "balanced"
+                },
+                "avatar": "https://example.com/avatar.png",
+                "color": "#1890ff"
+            }
+        }