feat: 重构前后端架构，添加Go后端和Python Agent服务

- 新增 Go 语言后端服务(server/)，包含用户认证、Agent管理、数据库连接等API
- 新增 Python Agent 服务(agent/)，实现Agent核心逻辑和工具集
- 前端从原生HTML迁移到Vue.js框架(web/src/)
- 添加 Docker Compose 支持(docker-compose.yml)
- 添加项目架构文档(docs/ARCHITECTURE.md)
- 添加环境变量示例(.env.example)和本地启动脚本(start-local.ps1)

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

agent/app/agent/core/executor.py

@@ -0,0 +1,163 @@
+"""
+Agent 执行器 - 负责执行 Agent 的核心逻辑
+"""
+from typing import Any, Optional
+from app.llm.factory import LLMFactory
+from app.agent.tools.registry import ToolRegistry
+from app.agent.memory.session import SessionManager
+from app.security.audit import AuditLogger
+
+
+class AgentExecutor:
+    """Agent 执行器"""
+
+    def __init__(
+        self,
+        agent_id: str,
+        llm_factory: LLMFactory,
+        tool_registry: ToolRegistry,
+        session_manager: SessionManager,
+        audit_logger: AuditLogger,
+        config: dict
+    ):
+        self.agent_id = agent_id
+        self.llm_factory = llm_factory
+        self.tool_registry = tool_registry
+        self.session_manager = session_manager
+        self.audit_logger = audit_logger
+        self.config = config
+
+        # 获取 LLM
+        self.llm = self.llm_factory.get_llm()
+
+    async def run(
+        self,
+        message: str,
+        session_id: str,
+        context: dict
+    ) -> dict[str, Any]:
+        """运行 Agent"""
+        tools_used = []
+
+        # 1. 获取会话历史
+        history = self.session_manager.get_history(session_id)
+
+        # 2. 构建消息列表
+        messages = self._build_messages(message, history)
+
+        # 3. 获取可用工具
+        available_tools = self._get_available_tools()
+
+        # 4. 调用 LLM（带工具）
+        try:
+            response = await self.llm.agenerate(
+                messages=messages,
+                tools=available_tools
+            )
+
+            # 检查是否需要调用工具
+            response_message = response.generations[0][0]
+
+            # 如果有工具调用
+            if hasattr(response_message, "tool_calls") and response_message.tool_calls:
+                for tool_call in response_message.tool_calls:
+                    tool_name = tool_call.name
+                    tool_args = tool_call.arguments
+
+                    # 记录工具使用
+                    tools_used.append(tool_name)
+
+                    # 执行工具
+                    tool_result = await self._execute_tool(tool_name, tool_args)
+
+                    # 添加工具结果到消息
+                    messages.append(response_message)
+                    messages.append({
+                        "role": "tool",
+                        "tool_call_id": tool_call.id,
+                        "content": str(tool_result)
+                    })
+
+                    # 再次调用 LLM 生成最终响应
+                    final_response = await self.llm.agenerate(messages=messages)
+                    final_message = final_response.generations[0][0].text
+
+                    # 保存到历史
+                    self.session_manager.add_message(session_id, "user", message)
+                    self.session_manager.add_message(session_id, "assistant", final_message)
+
+                    return {
+                        "reply": final_message,
+                        "tools_used": tools_used,
+                        "metadata": {}
+                    }
+
+            # 没有工具调用，直接返回
+            reply = response_message.text
+
+            # 保存到历史
+            self.session_manager.add_message(session_id, "user", message)
+            self.session_manager.add_message(session_id, "assistant", reply)
+
+            return {
+                "reply": reply,
+                "tools_used": tools_used,
+                "metadata": {}
+            }
+
+        except Exception as e:
+            # 记录错误
+            self.audit_logger.log(
+                action="agent_error",
+                agent_id=self.agent_id,
+                session_id=session_id,
+                details={"error": str(e)}
+            )
+            raise
+
+    def _build_messages(self, message: str, history: list) -> list:
+        """构建消息列表"""
+        messages = []
+
+        # 添加系统提示
+        system_prompt = self.config.get("system_prompt", "You are a helpful assistant.")
+        messages.append({"role": "system", "content": system_prompt})
+
+        # 添加历史
+        for msg in history:
+            messages.append(msg)
+
+        # 添加当前消息
+        messages.append({"role": "user", "content": message})
+
+        return messages
+
+    def _get_available_tools(self) -> list:
+        """获取可用工具定义"""
+        agent_tools = self.config.get("tools", [])
+        tool_defs = []
+
+        for tool_name in agent_tools:
+            tool_def = self.tool_registry.get_tool_definition(tool_name)
+            if tool_def:
+                tool_defs.append(tool_def)
+
+        return tool_defs
+
+    async def _execute_tool(self, tool_name: str, args: dict) -> Any:
+        """执行工具"""
+        # 安全检查
+        tool_func, metadata = self.tool_registry.get_tool(tool_name)
+
+        # 如果需要审批，抛出异常
+        if metadata.require_approval:
+            raise PermissionError(
+                f"Tool '{tool_name}' requires approval before execution"
+            )
+
+        # 执行工具
+        try:
+            result = tool_func(**args)
+            return result
+        except Exception as e:
+            return {"error": str(e)}