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| 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 325 326 327 328 329 330 331 332 333 334 335 336 337 338 339 340 341 342 343 344 345 346 347 348 349 350 351 352 353 354 355 356 357 358 359 360 361 362 363 364 365 366 367 368 369 370 371 372 373 374 375 376 377 378 379 380 381 382 383 384 385 386 387 388 389 390 391 392 393 394 395 396 397 398 399 400 401 402 403 404 405 406 407 408 409 410 411 412 413 414 415 416 417 418 419 420 421 422 423 424 425 426 | /** * ActiveLearningStore - 主动学习状态管理 * * 猡久学习事件和学习模式，学习建议的状态。 */ import { create } from 'zustand'; import { persist } from 'zustand/middleware'; import { type LearningEvent, type LearningPattern, type LearningSuggestion, type LearningEventType, type LearningConfig, } from '../types/active-learning'; // === Types === interface ActiveLearningState { events: LearningEvent[]; patterns: LearningPattern[]; suggestions: LearningSuggestion[]; config: LearningConfig; isLoading: boolean; error: string | null; } interface ActiveLearningActions { recordEvent: (event: Omit<LearningEvent, 'id' | 'timestamp' | 'acknowledged'>) => Promise<LearningEvent>; recordFeedback: (agentId: string, messageId: string, feedback: string, context?: string) => Promise<LearningEvent | null>; acknowledgeEvent: (eventId: string) => void; getPatterns: (agentId: string) => LearningPattern[]; getSuggestions: (agentId: string) => LearningSuggestion[]; applySuggestion: (suggestionId: string) => void; dismissSuggestion: (suggestionId: string) => void; getStats: (agentId: string) => ActiveLearningStats; setConfig: (config: Partial<LearningConfig>) => void; clearEvents: (agentId: string) => void; exportLearningData: (agentId: string) => Promise<string>; importLearningData: (agentId: string, data: string) => Promise<void>; } interface ActiveLearningStats { totalEvents: number; eventsByType: Record<LearningEventType, number>; totalPatterns: number; avgConfidence: number; } export type ActiveLearningStore = ActiveLearningState & ActiveLearningActions; const STORAGE_KEY = 'zclaw-active-learning'; const MAX_EVENTS = 1000; // === Helper Functions === function generateEventId(): string { return `le-${Date.now()}-${Math.random().toString(36).slice(2)}`; } function analyzeSentiment(text: string): 'positive' | 'negative' | 'neutral' { const positive = ['好的', '很棒', '谢谢', '完美', 'excellent', '喜欢', '爱了', 'good', 'great', 'nice', '满意']; const negative = ['不好', '差', '糟糕', '错误', 'wrong', 'bad', '不喜欢', '讨厌', '问题', '失败', 'fail', 'error']; const lowerText = text.toLowerCase(); if (positive.some(w => lowerText.includes(w))) return 'positive'; if (negative.some(w => lowerText.includes(w))) return 'negative'; return 'neutral'; } function analyzeEventType(text: string): LearningEventType { const lowerText = text.toLowerCase(); if (lowerText.includes('纠正') || lowerText.includes('不对') || lowerText.includes('修改')) { return 'correction'; } if (lowerText.includes('喜欢') || lowerText.includes('偏好') || lowerText.includes('风格')) { return 'preference'; } if (lowerText.includes('场景') || lowerText.includes('上下文') || lowerText.includes('情况')) { return 'context'; } if (lowerText.includes('总是') || lowerText.includes('经常') || lowerText.includes('习惯')) { return 'behavior'; } return 'feedback'; } function inferPreference(feedback: string, sentiment: string): string { if (sentiment === 'positive') { if (feedback.includes('简洁')) return '用户偏好简洁的回复'; if (feedback.includes('详细')) return '用户偏好详细的回复'; if (feedback.includes('快速')) return '用户偏好快速响应'; return '用户对当前回复风格满意'; } if (sentiment === 'negative') { if (feedback.includes('太长')) return '用户偏好更短的回复'; if (feedback.includes('太短')) return '用户偏好更详细的回复'; if (feedback.includes('不准确')) return '用户偏好更准确的信息'; return '用户对当前回复风格不满意'; } return '用户反馈中性'; } // === Store === export const useActiveLearningStore = create<ActiveLearningStore>()( persist( (set, get) => ({ events: [], patterns: [], suggestions: [], config: { enabled: true, minConfidence: 0.5, maxEvents: MAX_EVENTS, suggestionCooldown: 2, }, isLoading: false, error: null, recordEvent: async (event) => { const { events, config } = get(); if (!config.enabled) throw new Error('Learning is disabled'); // 检查重复事件 const existing = events.find(e => e.agentId === event.agentId && e.messageId === event.messageId && e.type === event.type ); if (existing) { // 更新现有事件 const updated = events.map(e => e.id === existing.id ? { ...e, observation: e.observation + ' | ' + event.observation, confidence: (e.confidence + event.confidence) / 2, appliedCount: e.appliedCount + 1, } : e ); set({ events: updated }); return existing; } // 创建新事件 const newEvent: LearningEvent = { ...event, id: generateEventId(), timestamp: Date.now(), acknowledged: false, appliedCount: 0, }; // 提取模式 const newPatterns = extractPatterns(newEvent, get().patterns); const newSuggestions = generateSuggestions(newEvent, newPatterns); // 保持事件数量限制 const updatedEvents = [newEvent, ...events].slice(0, config.maxEvents); set({ events: updatedEvents, patterns: [...get().patterns, ...newPatterns], suggestions: [...get().suggestions, ...newSuggestions], }); return newEvent; }, recordFeedback: async (agentId, messageId, feedback, context) => { const { config } = get(); if (!config.enabled) return null; const sentiment = analyzeSentiment(feedback); const type = analyzeEventType(feedback); return get().recordEvent({ type, agentId, messageId, trigger: context || 'User feedback', observation: feedback, context, inferredPreference: inferPreference(feedback, sentiment), confidence: sentiment === 'positive' ? 0.8 : sentiment === 'negative' ? 0.5 : 0.3, appliedCount: 0, }); }, acknowledgeEvent: (eventId) => { const { events } = get(); set({ events: events.map(e => e.id === eventId ? { ...e, acknowledged: true } : e ), }); }, getPatterns: (agentId) => { return get().patterns.filter(p => p.agentId === agentId); }, getSuggestions: (agentId) => { const now = Date.now(); return get().suggestions.filter(s => s.agentId === agentId && !s.dismissed && (!s.expiresAt || s.expiresAt.getTime() > now) ); }, applySuggestion: (suggestionId) => { const { suggestions, patterns } = get(); const suggestion = suggestions.find(s => s.id === suggestionId); if (suggestion) { // 更新模式置信度 const updatedPatterns = patterns.map(p => p.pattern === suggestion.pattern ? { ...p, confidence: Math.min(1, p.confidence + 0.1) } : p ); set({ suggestions: suggestions.map(s => s.id === suggestionId ? { ...s, dismissed: false } : s ), patterns: updatedPatterns, }); } }, dismissSuggestion: (suggestionId) => { const { suggestions } = get(); set({ suggestions: suggestions.map(s => s.id === suggestionId ? { ...s, dismissed: true } : s ), }); }, getStats: (agentId) => { const { events, patterns } = get(); const agentEvents = events.filter(e => e.agentId === agentId); const agentPatterns = patterns.filter(p => p.agentId === agentId); const eventsByType: Record<LearningEventType, number> = { preference: 0, correction: 0, context: 0, feedback: 0, behavior: 0, implicit: 0, }; for (const event of agentEvents) { eventsByType[event.type]++; } return { totalEvents: agentEvents.length, eventsByType, totalPatterns: agentPatterns.length, avgConfidence: agentPatterns.length > 0 ? agentPatterns.reduce((sum, p) => sum + p.confidence, 0) / agentPatterns.length : 0, }; }, setConfig: (config) => { set(state => ({ config: { ...state.config, ...config }, })); }, clearEvents: (agentId) => { const { events, patterns, suggestions } = get(); set({ events: events.filter(e => e.agentId !== agentId), patterns: patterns.filter(p => p.agentId !== agentId), suggestions: suggestions.filter(s => s.agentId !== agentId), }); }, exportLearningData: async (agentId) => { const { events, patterns, config } = get(); const data = { events: events.filter(e => e.agentId === agentId), patterns: patterns.filter(p => p.agentId === agentId), config, exportedAt: new Date().toISOString(), }; return JSON.stringify(data, null, 2); }, importLearningData: async (agentId, data) => { try { const parsed = JSON.parse(data); const { events, patterns } = get(); // 合并导入的数据 const mergedEvents = [ ...events, ...parsed.events.map((e: LearningEvent) => ({ ...e, id: generateEventId(), agentId, })), ].slice(0, MAX_EVENTS); const mergedPatterns = [ ...patterns, ...parsed.patterns.map((p: LearningPattern) => ({ ...p, agentId, })), ]; set({ events: mergedEvents, patterns: mergedPatterns, }); } catch (err) { throw new Error(`Failed to import learning data: ${err}`); } }, }), { name: STORAGE_KEY, } ) ); // === Pattern Extraction === function extractPatterns( event: LearningEvent, existingPatterns: LearningPattern[] ): LearningPattern[] { const patterns: LearningPattern[] = []; // 偏好模式 if (event.observation.includes('谢谢') || event.observation.includes('好的')) { patterns.push({ type: 'preference', pattern: 'positive_response_preference', description: '用户偏好正面回复风格', examples: [event.observation], confidence: 0.8, agentId: event.agentId, }); } // 精确性模式 if (event.type === 'correction') { patterns.push({ type: 'rule', pattern: 'precision_preference', description: '用户对精确性有更高要求', examples: [event.observation], confidence: 0.9, agentId: event.agentId, }); } // 上下文模式 if (event.context) { patterns.push({ type: 'context', pattern: 'context_aware', description: 'Agent 需要关注上下文', examples: [event.context], confidence: 0.6, agentId: event.agentId, }); } return patterns.filter(p => !existingPatterns.some(ep => ep.pattern === p.pattern && ep.agentId === p.agentId) ); } // === Suggestion Generation === function generateSuggestions( event: LearningEvent, patterns: LearningPattern[] ): LearningSuggestion[] { const suggestions: LearningSuggestion[] = []; const now = Date.now(); for (const pattern of patterns) { const template = SUGGESTION_TEMPLATES[pattern.pattern]; if (template) { suggestions.push({ id: `sug-${Date.now()}-${Math.random().toString(36).slice(2)}`, agentId: event.agentId, type: pattern.type, pattern: pattern.pattern, suggestion: template, confidence: pattern.confidence, createdAt: now, expiresAt: new Date(now + 7 * 24 * 60 * 60 * 1000), dismissed: false, }); } } return suggestions; } const SUGGESTION_TEMPLATES: Record<string, string> = { positive_response_preference: '用户似乎偏好正面回复。建议在回复时保持积极和确认的语气。', precision_preference: '用户对精确性有更高要求。建议在提供信息时更加详细和准确。', context_aware: 'Agent 需要关注上下文。建议在回复时考虑对话的背景和历史。', }; |