chore(desktop): remove dead active-learning frontend code

Zero imports across codebase — never wired to any UI or Tauri command.
Rust Growth crate handles memory/summary generation instead.
This commit is contained in:
iven
2026-04-04 00:38:13 +08:00
parent 8faefd6a61
commit 276ec3ca94
2 changed files with 0 additions and 428 deletions

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/**
* 主动学习引擎 - 从用户交互中学习并改进 Agent 行为
*
* 提供学习事件记录、模式提取和建议生成功能。
* Phase 1: 内存存储Zustand 持久化
* Phase 2: SQLite + 向量化存储
*/
import {
type LearningEvent,
type LearningPattern,
type LearningSuggestion,
type LearningEventType,
type FeedbackSentiment,
} from '../types/active-learning';
import { generateRandomString } from './crypto-utils';
// === 常量 ===
const MAX_EVENTS = 1000;
const PATTERN_CONFIDENCE_THRESHOLD = 0.7;
const SUGGESTION_COOLDOWN_HOURS = 2;
// === 生成 ID ===
function generateEventId(): string {
return `le-${Date.now()}-${generateRandomString(8)}`;
}
// === 分析反馈情感 ===
export function analyzeSentiment(text: string): FeedbackSentiment {
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.toLowerCase()))) return 'positive';
if (negative.some(w => lowerText.includes(w.toLowerCase()))) return 'negative';
return 'neutral';
}
// === 分析学习类型 ===
export 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 'implicit';
}
// === 推断偏好 ===
export function inferPreference(feedback: string, sentiment: FeedbackSentiment): 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';
}
// === 学习引擎类 ===
export class ActiveLearningEngine {
private events: LearningEvent[] = [];
private patterns: LearningPattern[] = [];
// Reserved for future learning suggestions feature
private suggestions: LearningSuggestion[] = [];
private initialized: boolean = false;
constructor() {
this.initialized = true;
}
/** Get current suggestions (reserved for future use) */
getSuggestions(): LearningSuggestion[] {
return this.suggestions;
}
/** Check if engine is initialized */
isInitialized(): boolean {
return this.initialized;
}
/**
* 记录学习事件
*/
recordEvent(
event: Omit<LearningEvent, 'id' | 'timestamp' | 'acknowledged' | 'appliedCount'>
): LearningEvent {
// 检查重复事件
const existing = this.events.find(e =>
e.agentId === event.agentId &&
e.messageId === event.messageId &&
e.type === event.type
);
if (existing) {
// 更新现有事件
existing.observation += ' | ' + event.observation;
existing.confidence = (existing.confidence + event.confidence) / 2;
existing.appliedCount++;
return existing;
}
// 创建新事件
const newEvent: LearningEvent = {
...event,
id: generateEventId(),
timestamp: Date.now(),
acknowledged: false,
appliedCount: 0,
};
this.events.push(newEvent);
this.extractPatterns(newEvent);
// 保持事件数量限制
if (this.events.length > MAX_EVENTS) {
this.events = this.events.slice(-MAX_EVENTS);
}
return newEvent;
}
/**
* 从反馈中学习
*/
learnFromFeedback(
agentId: string,
messageId: string,
feedback: string,
context?: string
): LearningEvent {
const sentiment = analyzeSentiment(feedback);
const type = analyzeEventType(feedback);
return this.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,
});
}
/**
* 提取学习模式
*/
private extractPatterns(event: LearningEvent): void {
// 1. 正面反馈 -> 偏好正面回复
if (event.observation.includes('谢谢') || event.observation.includes('好的')) {
this.addPattern({
id: `pat-${Date.now()}-${generateRandomString(8)}`,
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,
});
}
// 2. 纠正 -> 需要更精确
if (event.type === 'correction') {
this.addPattern({
id: `pat-${Date.now()}-${generateRandomString(8)}`,
type: 'preference',
pattern: 'precision_preference',
description: '用户对精确性有更高要求',
examples: [event.observation],
confidence: 0.9,
agentId: event.agentId,
});
}
// 3. 上下文相关 -> 场景偏好
if (event.context) {
this.addPattern({
id: `pat-${Date.now()}-${generateRandomString(8)}`,
type: 'context',
pattern: 'context_aware',
description: 'Agent 需要关注上下文',
examples: [event.context],
confidence: 0.6,
agentId: event.agentId,
});
}
}
/**
* 添加学习模式
*/
private addPattern(pattern: Omit<LearningPattern, 'updatedAt'>): void {
const existing = this.patterns.find(p =>
p.type === pattern.type &&
p.pattern === pattern.pattern &&
p.agentId === pattern.agentId
);
if (existing) {
// 增强置信度
existing.confidence = Math.min(1, existing.confidence + pattern.confidence * 0.1);
existing.examples.push(pattern.examples[0]);
existing.updatedAt = Date.now();
} else {
this.patterns.push({
...pattern,
updatedAt: Date.now(),
});
}
}
/**
* 生成学习建议
*/
generateSuggestions(agentId: string): LearningSuggestion[] {
const suggestions: LearningSuggestion[] = [];
const now = Date.now();
// 获取该 Agent 的模式
const agentPatterns = this.patterns.filter(p => p.agentId === agentId);
for (const pattern of agentPatterns) {
// 检查冷却时间
const hoursSinceUpdate = (now - (pattern.updatedAt || now)) / (1000 * 60 * 60);
if (hoursSinceUpdate < SUGGESTION_COOLDOWN_HOURS) continue;
// 检查置信度阈值
if (pattern.confidence < PATTERN_CONFIDENCE_THRESHOLD) continue;
// 生成建议
suggestions.push({
id: `sug-${Date.now()}-${generateRandomString(8)}`,
agentId,
type: pattern.type,
pattern: pattern.pattern,
suggestion: this.generateSuggestionContent(pattern),
confidence: pattern.confidence,
createdAt: now,
expiresAt: new Date(now + 7 * 24 * 60 * 60 * 1000),
dismissed: false,
});
}
return suggestions;
}
/**
* 生成建议内容
*/
private generateSuggestionContent(pattern: LearningPattern): string {
const 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。',
};
return templates[pattern.pattern] || `观察到模式: ${pattern.pattern}`;
}
/**
* 获取统计信息
*/
getStats(agentId: string) {
const agentEvents = this.events.filter(e => e.agentId === agentId);
const agentPatterns = this.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,
};
}
/**
* 获取所有事件
*/
getEvents(agentId?: string): LearningEvent[] {
if (agentId) {
return this.events.filter(e => e.agentId === agentId);
}
return [...this.events];
}
/**
* 获取所有模式
*/
getPatterns(agentId?: string): LearningPattern[] {
if (agentId) {
return this.patterns.filter(p => p.agentId === agentId);
}
return [...this.patterns];
}
/**
* 确认事件
*/
acknowledgeEvent(eventId: string): void {
const event = this.events.find(e => e.id === eventId);
if (event) {
event.acknowledged = true;
}
}
/**
* 清除事件
*/
clearEvents(agentId: string): void {
this.events = this.events.filter(e => e.agentId !== agentId);
this.patterns = this.patterns.filter(p => p.agentId !== agentId);
}
}
// === 单例实例 ===
let engineInstance: ActiveLearningEngine | null = null;
export function getActiveLearningEngine(): ActiveLearningEngine {
if (!engineInstance) {
engineInstance = new ActiveLearningEngine();
}
return engineInstance;
}
export function resetActiveLearningEngine(): void {
engineInstance = null;
}

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/**
* 主动学习引擎类型定义
*/
export type LearningEventType =
| 'preference'
| 'correction'
| 'context'
| 'feedback'
| 'behavior'
| 'implicit';
export type FeedbackSentiment = 'positive' | 'negative' | 'neutral';
export interface LearningEvent {
id: string;
type: LearningEventType;
agentId: string;
messageId: string;
timestamp: number;
trigger: string;
observation: string;
context?: string;
inferredPreference?: string;
confidence: number;
acknowledged: boolean;
appliedCount: number;
}
export interface LearningPattern {
id: string;
type: LearningEventType;
pattern: string;
description: string;
examples: string[];
confidence: number;
agentId: string;
updatedAt: number;
}
export interface LearningSuggestion {
id: string;
agentId: string;
type: LearningEventType;
pattern: string;
suggestion: string;
confidence: number;
createdAt: number;
expiresAt?: Date;
dismissed: boolean;
}
export interface ActiveLearningState {
events: LearningEvent[];
patterns: LearningPattern[];
suggestions: LearningSuggestion[];
isEnabled: boolean;
lastProcessed: number;
}