🔗 企业级 AI Agents 平台集成 OpenClaw 技术方案

# OpenClaw Gateway WebSocket 协议实现 import asyncio import websockets import json from typing import Dict, Any, Optional class OpenClawGateway: """ OpenClaw Gateway - Agent 核心协调层 功能： 1. WebSocket 连接管理 2. 消息路由与分发 3. 设备认证与授权 4. 安全策略执行 """ def __init__(self, host: str = "localhost", port: int = 18789): self.host = host self.port = port self.connections: Dict[str, websockets.WebSocketServerProtocol] = {} self.authenticated_devices: Dict[str, dict] = {} self.security_config = { "require_pairing": True, "max_login_attempts": 5, "lockout_duration": 300, # 5 分钟 "allowed_origins": [] # 企业白名单 } self.login_attempts: Dict[str, int] = {} async def start_server(self): """启动 Gateway 服务器""" # 企业级配置：绑定内网 IP，禁止公网访问 if self.host == "0.0.0.0": raise SecurityError("禁止绑定到所有网络接口") server = await websockets.serve( self._handle_connection, self.host, self.port, subprotocols=["openclaw-v1"], extra_headers={ "X-Frame-Options": "DENY", "X-Content-Type-Options": "nosniff" } ) await server.wait_closed() async def _handle_connection(self, websocket: websockets.WebSocketServerProtocol, path: str): """处理 WebSocket 连接""" device_id = None try: # 1. 验证 Origin（防止 CSRF） origin = websocket.request_headers.get("Origin") if not self._verify_origin(origin): await websocket.close(4003, "Forbidden origin") return # 2. 设备认证 auth_message = await websocket.recv() auth_data = json.loads(auth_message) if not await self._authenticate_device(auth_data, websocket): await websocket.close(4001, "Authentication failed") return device_id = auth_data["device_id"] self.connections[device_id] = websocket self.authenticated_devices[device_id] = auth_data # 3. 消息循环 async for message in websocket: await self._process_message(device_id, message) except websockets.exceptions.ConnectionClosed: pass finally: if device_id in self.connections: del self.connections[device_id] async def _authenticate_device(self, auth_data: dict, websocket) -> bool: """设备认证（增强版）""" device_id = auth_data.get("device_id") password = auth_data.get("password") # 检查登录尝试次数 attempts = self.login_attempts.get(device_id, 0) if attempts >= self.security_config["max_login_attempts"]: await websocket.close(4002, "Too many failed attempts") return False # 验证密码（企业应使用 OAuth2/JWT） if not self._verify_password(device_id, password): self.login_attempts[device_id] = attempts + 1 return False # 认证成功，清除尝试计数 self.login_attempts.pop(device_id, None) return True def _verify_origin(self, origin: Optional[str]) -> bool: """验证请求来源（企业白名单）""" if not origin: return False allowed = self.security_config["allowed_origins"] return origin in allowed or "*" in allowed async def _process_message(self, device_id: str, message: str): """处理消息路由""" data = json.loads(message) msg_type = data.get("type") if msg_type == "execute_command": # 执行命令前进行安全审查 if not await self._security_review(data): return # 路由到 Pi Agent 运行时 await self._route_to_agent(device_id, data) elif msg_type == "query_status": # 查询状态 status = await self._get_agent_status(device_id) await self.connections[device_id].send(json.dumps(status)) async def _security_review(self, command_data: dict) -> bool: """安全审查（企业级增强）""" command = command_data.get("command", "") # 黑名单命令检查 blocked_commands = ["rm -rf /", "sudo", "chmod 777"] for blocked in blocked_commands: if blocked in command: return False # 敏感文件访问检查 sensitive_paths = ["/etc/passwd", "/root", "/.ssh"] for path in sensitive_paths: if path in command: return False return True class SecurityError(Exception): """安全异常""" pass

# openclaw_sdk.py - 企业级 OpenClaw SDK import asyncio import aiohttp import json from typing import Dict, Any, Optional, Callable from dataclasses import dataclass @dataclass class OpenClawConfig: """OpenClaw 配置""" gateway_url: str = "ws://localhost:18789" api_key: str = "" device_id: str = "" timeout: int = 30 max_retries: int = 3 # 企业级配置 verify_ssl: bool = True proxy: Optional[str] = None allowed_origins: list = None class OpenClawClient: """ OpenClaw 企业级客户端 SDK 功能： 1. WebSocket 连接管理 2. 任务提交与结果查询 3. Skills 动态注册 4. 事件回调机制 """ def __init__(self, config: OpenClawConfig): self.config = config self.session: Optional[aiohttp.ClientSession] = None self.websocket: Optional[aiohttp.ClientWebSocketResponse] = None self.callbacks: Dict[str, Callable] = {} self.task_results: Dict[str, asyncio.Future] = {} async def connect(self): """连接到 OpenClaw Gateway""" self.session = aiohttp.ClientSession( timeout=aiohttp.ClientTimeout(total=self.config.timeout), connector=aiohttp.TCPConnector(ssl=self.config.verify_ssl) ) # WebSocket 连接 self.websocket = await self.session.ws_connect( self.config.gateway_url, headers={ "Authorization": f"Bearer {self.config.api_key}", "X-Device-ID": self.config.device_id, "Origin": self.config.allowed_origins[0] if self.config.allowed_origins else None } ) # 启动消息监听 asyncio.create_task(self._listen_messages()) async def execute_task(self, task_description: str, skills: list = None) -> str: """执行任务""" task_id = self._generate_task_id() message = { "type": "execute_task", "task_id": task_id, "description": task_description, "skills": skills or [] } await self.websocket.send_json(message) # 等待结果 future = asyncio.Future() self.task_results[task_id] = future try: result = await asyncio.wait_for(future, timeout=self.config.timeout) return result except asyncio.TimeoutError: raise TimeoutError(f"Task {task_id} timeout") async def register_skill(self, skill_name: str, skill_config: dict): """动态注册 Skill""" message = { "type": "register_skill", "skill_name": skill_name, "config": skill_config } await self.websocket.send_json(message) def on_event(self, event_type: str, callback: Callable): """注册事件回调""" self.callbacks[event_type] = callback async def _listen_messages(self): """监听消息""" async for message in self.websocket: data = message.json() await self._handle_message(data) async def _handle_message(self, data: dict): """处理消息""" msg_type = data.get("type") task_id = data.get("task_id") if msg_type == "task_result" and task_id in self.task_results: future = self.task_results.pop(task_id) future.set_result(data.get("result")) elif msg_type in self.callbacks: await self.callbacks[msg_type](data) def _generate_task_id(self) -> str: import uuid return str(uuid.uuid4()) async def close(self): """关闭连接""" if self.websocket: await self.websocket.close() if self.session: await self.session.close()

# OpenClaw Enterprise API 规范 """ Base URL: https://openclaw.enterprise.com/api/v1 认证方式：Bearer Token (JWT) 速率限制：1000 requests/minute Endpoints: POST /tasks - 创建任务 GET /tasks/{id} - 查询任务状态 DELETE /tasks/{id} - 取消任务 POST /skills - 注册 Skill GET /skills - 获取 Skills 列表 POST /knowledge - 上传知识库文档 GET /audit/logs - 查询审计日志 """ # 创建任务示例 POST /api/v1/tasks Content-Type: application/json Authorization: Bearer eyJhbGciOiJIUzI1NiIs... { "description": "分析 Q4 销售数据并生成 PPT 报告", "skills": ["excel-analyzer", "ppt-generator"], "context": { "department": "sales", "quarter": "Q4-2025" }, "priority": "high", "callback_url": "https://enterprise.com/webhook/task-complete" } # 响应 { "task_id": "task_abc123", "status": "queued", "created_at": "2026-03-03T10:30:00Z", "estimated_duration": 300 }

# 企业知识库 RAG 集成 from langchain.vectorstores import Milvus from langchain.embeddings import HuggingFaceEmbeddings from langchain.document_loaders import DirectoryLoader class EnterpriseKnowledgeBase: """企业知识库 RAG 集成""" def __init__(self, config: dict): # 初始化嵌入模型 self.embeddings = HuggingFaceEmbeddings( model_name=config["embedding_model"], model_kwargs={"device": "cuda"} ) # 连接向量数据库 self.vectorstore = Milvus( embedding_function=self.embeddings, connection_args={ "host": config["milvus_host"], "port": config["milvus_port"] }, collection_name=config["collection_name"] ) def ingest_documents(self, docs_path: str): """导入企业文档""" loader = DirectoryLoader( docs_path, glob="**/*.pdf", use_multithreading=True ) documents = loader.load() # 向量化并存储 self.vectorstore.add_documents(documents) def retrieve_context(self, query: str, top_k: int = 5) -> list: """检索相关上下文""" results = self.vectorstore.similarity_search(query, k=top_k) return [doc.page_content for doc in results] def enhance_prompt(self, user_query: str) -> str: """增强用户提示词""" context = self.retrieve_context(user_query) enhanced_prompt = f""" 基于以下企业知识库上下文回答问题： {chr(10).join(context)} 用户问题：{user_query} 请基于上述上下文提供准确、专业的回答。如果上下文中没有相关信息，请明确说明。 """ return enhanced_prompt

# 业务系统 API 适配器 from abc import ABC, abstractmethod class BusinessSystemAdapter(ABC): """业务系统适配器基类""" @abstractmethod def connect(self) -> bool: pass @abstractmethod def execute(self, action: str, params: dict) -> any: pass class FeishuAdapter(BusinessSystemAdapter): """飞书多维表格适配器""" def __init__(self, app_id: str, app_secret: str): self.app_id = app_id self.app_secret = app_secret self.access_token = None def connect(self) -> bool: # 获取访问令牌 pass def execute(self, action: str, params: dict): if action == "read_table": return self._read_table(params) elif action == "write_table": return self._write_table(params) elif action == "generate_ppt": return self._generate_ppt(params) def _read_table(self, params: dict): # 读取多维表格数据 pass def _write_table(self, params: dict): # 写入多维表格数据 pass def _generate_ppt(self, params: dict): # 生成 PPT 报告 pass class DingTalkAdapter(BusinessSystemAdapter): """钉钉适配器""" pass