🧠 Promptless AI

// 主动推理引擎 interface ProactiveInference { // 意图预测 predictIntent(context: Context, behavior: Behavior): Intent; // 需求推断 inferNeeds(intent: Intent, userProfile: Profile): Need[]; // 行动生成 generateActions(needs: Need[]): Action[]; // 置信度评估 evaluateConfidence(actions: Action[]): number; } // 上下文表示 interface Context { currentTask: string; // 当前任务 timeOfDay: number; // 时间 recentActions: Action[]; // 最近操作 userState: UserState; // 用户状态 environment: Environment; // 环境信息 }

// OpenClaw配置 - Promptless AI { "name": "proactive-assistant", "type": "promptless", "capabilities": { "intentPrediction": "advanced", "contextAwareness": "deep", "proactiveResponse": true, "confidenceThreshold": 0.8 }, "observation": { "userBehavior": true, "taskContext": true, "timePatterns": true, "historicalData": true }, "actions": { "autoSuggest": true, "autoExecute": true, "confirmBeforeAction": true } }

// 智能内容推荐 class ProactiveContentRecommender { async observe(userBehavior: UserBehavior) { // 1. 分析用户行为 const pattern = this.analyzePattern(userBehavior); // 2. 预测意图 const intent = this.predictIntent(pattern); // 3. 推断需求 const needs = this.inferNeeds(intent); // 4. 生成推荐 if (needs.confidence > 0.8) { return this.generateRecommendation(needs); } return null; } } // 使用示例 const recommender = new ProactiveContentRecommender(); // 观察用户行为 recommender.observe({ recentPages: ['/glossary/mcp', '/glossary/a2a'], timeSpent: { '/glossary/mcp': 300, '/glossary/a2a': 180 }, searchQueries: ['agent protocol comparison'] }); // 自动推荐 // "你可能想了解：A2A vs MCP 对比分析"

// promptless-ai-system.ts import { OpenClaw, IntentPredictor, ContextEngine } from 'openclaw'; class PromptlessAISystem { private predictor: IntentPredictor; private context: ContextEngine; private userProfile: UserProfile; constructor() { this.predictor = new IntentPredictor({ model: 'intent-bert', threshold: 0.8 }); this.context = new ContextEngine({ trackBehavior: true, trackTime: true, trackHistory: true }); } async observe(event: UserEvent) { // 1. 更新上下文 this.context.update(event); // 2. 获取完整上下文 const fullContext = this.context.getFullContext(); // 3. 预测意图 const intent = await this.predictor.predict(fullContext); // 4. 评估置信度 if (intent.confidence > 0.8) { // 5. 主动生成响应 const response = await this.generateResponse(intent); return response; } return null; } private async generateResponse(intent: Intent) { switch (intent.type) { case 'content-creation': return this.suggestContent(intent); case 'task-automation': return this.suggestAutomation(intent); case 'information-seeking': return this.suggestInformation(intent); default: return null; } } } // 使用示例 const ai = new PromptlessAISystem(); // 用户行为事件 await ai.observe({ type: 'page-view', page: '/glossary/mcp-explained', duration: 300, actions: ['scroll', 'highlight', 'copy'] }); // AI主动响应 // "我注意到你在研究MCP协议，需要我帮你： // 1. 生成MCP与A2A的对比分析 // 2. 创建MCP实战教程 // 3. 找出相关案例研究"