自进化 AI 系统
Phase 100 | v5.0.0 | 状态: ✅ 生产就绪 | 8 IPC Handlers | 3 数据库表
ChainlessChain 自进化 AI 系统实现了 AI 模型的自主进化能力,包括自动架构搜索(NAS for Edge)、持续学习(无灾难性遗忘)、自诊断与自修复、行为预测与主动服务、能力自评估与自动升级,并通过进化成长日志可视化追踪 AI 的演进轨迹。
核心特性
- 🧠 自动架构搜索(NAS for Edge): 针对边缘设备自动搜索最优模型架构,平衡精度与推理速度,支持 ONNX/TFLite 导出
- 📚 持续学习(无灾难性遗忘): 基于 EWC(弹性权重巩固)+ 知识蒸馏的增量学习方案,新知识不覆盖旧知识
- 🔧 自诊断与自修复: 自动检测模型退化(精度下降/延迟升高/异常输出),触发自修复流程(重训练/回滚/降级)
- 🔮 行为预测与主动服务: 基于用户行为序列预测下一步操作,提前准备资源、预加载数据、主动推荐
- 📊 能力自评估与自动升级: 定期评估模型在各维度的能力得分,低于阈值时自动触发升级流程
- 📈 进化成长日志: 完整记录 AI 每次进化的触发原因、变更内容、效果对比,支持时间线可视化
系统架构
┌─────────────────────────────────────────────────┐
│ SelfEvolvingAIManager │
│ (调度 / 配置 / 进化成长日志 / 模型导出) │
└───┬──────┬──────┬──────┬──────┬────────────────┘
│ │ │ │ │
▼ ▼ ▼ ▼ ▼
┌──────┐┌──────┐┌──────┐┌──────┐┌──────────┐
│ NAS ││持续 ││自诊断││行为 ││ 能力 │
│ 架构 ││学习 ││自修复││预测 ││ 评估 │
│ 搜索 ││(EWC) ││引擎 ││引擎 ││ + 升级 │
└──┬───┘└──┬───┘└──┬───┘└──┬───┘└────┬─────┘
│ │ │ │ │
▼ ▼ ▼ ▼ ▼
┌─────────────────────────────────────────────────┐
│ SQLite 持久化 (assessments / training_logs / │
│ growth_log) + ONNX/TFLite 模型导出 │
└─────────────────────────────────────────────────┘关键文件
| 文件 | 职责 |
|---|---|
src/main/ai-engine/evolution/self-evolving-manager.js | 自进化核心管理器 |
src/main/ai-engine/evolution/capability-assessor.js | 多维度能力评估 |
src/main/ai-engine/evolution/continual-learner.js | EWC/蒸馏增量学习 |
src/main/ai-engine/evolution/self-diagnosis.js | 自诊断与自修复引擎 |
src/main/ai-engine/evolution/behavior-predictor.js | 用户行为预测与主动服务 |
src/main/ai-engine/evolution/evolution-ipc.js | IPC 处理器(8 个) |
src/renderer/pages/ai/EvolutionDashboardPage.vue | 进化成长日志可视化页面 |
src/renderer/stores/evolution.ts | Pinia 状态管理 |
能力评估流程
定时评估任务
│
▼
┌──────────────┐ 评分 ≥ 阈值 ┌──────────┐
│ 能力评估 │ ─────────────────▶ │ 记录日志 │
│ (多维度) │ └──────────┘
└──────┬───────┘
│ 评分 < 阈值
▼
┌──────────────┐ 成功 ┌──────────────┐
│ 自动升级 │ ─────────▶ │ A/B 验证 │
│ (增量训练) │ │ + 灰度发布 │
└──────┬───────┘ └──────┬───────┘
│ 失败 │ 通过
▼ ▼
┌──────────────┐ ┌──────────────┐
│ 自诊断 │ │ 正式发布 │
│ + 自修复 │ │ + 记录进化 │
└──────────────┘ └──────────────┘能力评估
javascript
// 评估 AI 当前各维度能力
const assessment = await window.electron.ipcRenderer.invoke(
"evolution:assess-capability",
{
dimensions: [
"reasoning",
"coding",
"writing",
"translation",
"summarization",
"qa",
],
benchmarkSuite: "standard-v2",
sampleSize: 100,
},
);
// assessment = {
// modelId: "chainless-ai-v4.5",
// timestamp: 1710000000,
// overall: 0.87,
// dimensions: [
// { name: "reasoning", score: 0.91, threshold: 0.85, status: "pass", trend: "+0.03" },
// { name: "coding", score: 0.89, threshold: 0.85, status: "pass", trend: "+0.05" },
// { name: "writing", score: 0.85, threshold: 0.85, status: "borderline", trend: "-0.01" },
// { name: "translation", score: 0.82, threshold: 0.85, status: "below", trend: "-0.04" },
// { name: "summarization", score: 0.93, threshold: 0.85, status: "pass", trend: "+0.02" },
// { name: "qa", score: 0.84, threshold: 0.85, status: "borderline", trend: "0.00" },
// ],
// recommendations: [
// { dimension: "translation", action: "incremental-training", priority: "high" },
// { dimension: "qa", action: "data-augmentation", priority: "medium" },
// ]
// }增量训练
javascript
// 触发无灾难性遗忘的增量训练
const training = await window.electron.ipcRenderer.invoke(
"evolution:train-incremental",
{
targetDimensions: ["translation", "qa"],
strategy: "ewc", // "ewc" (弹性权重巩固) | "distillation" (知识蒸馏) | "replay" (经验回放)
dataSource: {
type: "curated", // "curated" | "user-feedback" | "synthetic"
samples: 5000,
},
constraints: {
maxDegradation: 0.02, // 其他维度最大允许退化 2%
maxDuration: 3600000, // 最大训练时长 1h
deviceTarget: "edge", // "edge" | "cloud" | "hybrid"
},
},
);
// training = {
// trainingId: "train-001",
// status: "completed",
// duration: 2400000,
// results: {
// translation: { before: 0.82, after: 0.88, improvement: "+0.06" },
// qa: { before: 0.84, after: 0.87, improvement: "+0.03" },
// reasoning: { before: 0.91, after: 0.90, degradation: "-0.01", withinLimit: true },
// },
// modelVersion: "chainless-ai-v4.5.1",
// exportFormats: ["onnx", "tflite"]
// }自诊断
javascript
// AI 系统自诊断
const diagnosis = await window.electron.ipcRenderer.invoke(
"evolution:self-diagnose",
{
checks: [
"accuracy",
"latency",
"memory",
"output-quality",
"hallucination-rate",
],
},
);
// diagnosis = {
// status: "degraded",
// issues: [
// {
// check: "latency",
// status: "warning",
// current: 1200,
// baseline: 800,
// message: "推理延迟较基线升高 50%",
// suggestedFix: "quantize-model",
// },
// {
// check: "hallucination-rate",
// status: "critical",
// current: 0.08,
// baseline: 0.03,
// message: "幻觉率异常升高",
// suggestedFix: "rollback-to-stable",
// },
// ],
// healthy: ["accuracy", "memory", "output-quality"]
// }自修复
javascript
// 根据诊断结果执行自修复
const repair = await window.electron.ipcRenderer.invoke(
"evolution:self-repair",
{
issues: ["latency", "hallucination-rate"],
strategy: "auto", // "auto" | "rollback" | "retrain" | "quantize" | "degrade-gracefully"
dryRun: false,
},
);
// repair = {
// repairId: "repair-001",
// actions: [
// { issue: "latency", action: "quantize-model", status: "completed", result: "延迟从 1200ms 降至 650ms" },
// { issue: "hallucination-rate", action: "rollback-to-stable", status: "completed", result: "回滚至 v4.5.0,幻觉率恢复至 0.03" },
// ],
// newModelVersion: "chainless-ai-v4.5.0-patched",
// verificationPassed: true
// }行为预测
javascript
// 预测用户下一步行为并主动准备
const prediction = await window.electron.ipcRenderer.invoke(
"evolution:predict-behavior",
{
userId: "user-001",
contextWindow: 20, // 最近 20 个行为作为上下文
predictionHorizon: 3, // 预测未来 3 步
},
);
// prediction = {
// userId: "user-001",
// predictions: [
// { action: "open-knowledge-base", confidence: 0.92, preload: ["kb-index", "recent-notes"] },
// { action: "search-notes", confidence: 0.78, preload: ["search-index"] },
// { action: "ask-ai-question", confidence: 0.65, preload: ["llm-session", "rag-context"] },
// ],
// proactiveActions: [
// { type: "preload-data", target: "kb-index", estimatedSavings: "800ms" },
// { type: "warm-cache", target: "llm-session", estimatedSavings: "1200ms" },
// ]
// }进化成长日志
javascript
// 查看 AI 进化历史
const growthLog = await window.electron.ipcRenderer.invoke(
"evolution:get-growth-log",
{
fromDate: "2026-01-01",
toDate: "2026-03-10",
includeMetrics: true,
},
);
// growthLog = {
// entries: [
// {
// id: "evo-001",
// date: "2026-01-15",
// type: "incremental-training",
// trigger: "capability-assessment",
// description: "翻译能力低于阈值,触发 EWC 增量训练",
// before: { translation: 0.78, overall: 0.84 },
// after: { translation: 0.86, overall: 0.87 },
// duration: 2400000,
// },
// {
// id: "evo-002",
// date: "2026-02-03",
// type: "self-repair",
// trigger: "self-diagnosis",
// description: "检测到幻觉率升高,自动回滚至稳定版本",
// before: { hallucinationRate: 0.08 },
// after: { hallucinationRate: 0.03 },
// duration: 30000,
// },
// {
// id: "evo-003",
// date: "2026-03-01",
// type: "architecture-search",
// trigger: "scheduled",
// description: "NAS 搜索到更优的 Edge 架构,推理速度提升 25%",
// before: { latencyMs: 800, modelSizeMB: 450 },
// after: { latencyMs: 600, modelSizeMB: 380 },
// duration: 7200000,
// },
// ],
// summary: {
// totalEvolutions: 12,
// overallImprovement: "+15.2%",
// topImprovedDimension: "coding (+12%)",
// evolutionFrequency: "4.0/month"
// }
// }进化配置
javascript
const config = await window.electron.ipcRenderer.invoke("evolution:configure", {
autoAssessment: { enabled: true, interval: 604800000 }, // 每周评估
autoUpgrade: { enabled: true, minScoreThreshold: 0.85 },
selfDiagnosis: { enabled: true, interval: 86400000 }, // 每天诊断
selfRepair: { autoRepair: true, requireApproval: false },
behaviorPrediction: { enabled: true, contextWindow: 20 },
});模型导出
javascript
// 导出进化后的模型
const exported = await window.electron.ipcRenderer.invoke(
"evolution:export-model",
{
modelVersion: "chainless-ai-v4.5.1",
format: "onnx", // "onnx" | "tflite" | "coreml" | "openvino"
quantization: "int8", // "fp32" | "fp16" | "int8" | "int4"
targetDevice: "edge", // "edge" | "mobile" | "server"
},
);
// exported = { modelVersion: "chainless-ai-v4.5.1", format: "onnx", quantization: "int8", sizeMB: 125, path: "/models/chainless-ai-v4.5.1-int8.onnx", accuracy: 0.86 }成长可视化
进化成长日志支持以下可视化模式:
| 可视化模式 | 说明 |
|---|---|
| 时间线视图 | 按时间轴展示每次进化事件,支持钻取详情 |
| 雷达图 | 多维度能力得分雷达图,对比不同版本 |
| 趋势折线图 | 各维度能力得分随时间的变化趋势 |
| 热力图 | 进化频率与维度关联热力图,识别薄弱环节 |
| 对比瀑布图 | 单次进化前后各指标变化的瀑布图 |
IPC 通道
| 通道 | 参数 | 返回值 |
|---|---|---|
evolution:assess-capability | { dimensions?, benchmarkSuite?, sampleSize? } | 评估结果 |
evolution:train-incremental | { targetDimensions, strategy, dataSource, ... } | 训练结果 |
evolution:self-diagnose | { checks? } | 诊断报告 |
evolution:self-repair | { issues, strategy?, dryRun? } | 修复结果 |
evolution:predict-behavior | { userId, contextWindow?, predictionHorizon? } | 行为预测 |
evolution:get-growth-log | { fromDate?, toDate?, includeMetrics? } | 进化日志 |
evolution:configure | { autoAssessment?, autoUpgrade?, ... } | 配置结果 |
evolution:export-model | { modelVersion, format, quantization?, ... } | 导出结果 |
数据库表
evolution_assessments
| 字段 | 类型 | 说明 |
|---|---|---|
| id | TEXT PK | 评估 ID |
| model_id | TEXT | 模型标识 |
| overall_score | REAL | 综合得分 |
| dimensions | JSON | 各维度评分详情 |
| recommendations | JSON | 升级建议 |
| benchmark_suite | TEXT | 使用的评测集 |
| created_at | INTEGER | 评估时间戳 |
evolution_training_logs
| 字段 | 类型 | 说明 |
|---|---|---|
| id | TEXT PK | 训练 ID |
| type | TEXT | incremental/nas/repair |
| trigger | TEXT | 触发原因 |
| strategy | TEXT | ewc/distillation/replay |
| before_metrics | JSON | 训练前指标 |
| after_metrics | JSON | 训练后指标 |
| model_version_in | TEXT | 输入模型版本 |
| model_version_out | TEXT | 输出模型版本 |
| duration | INTEGER | 训练时长(ms) |
| status | TEXT | completed/failed/cancelled |
| created_at | INTEGER | 创建时间戳 |
evolution_growth_log
| 字段 | 类型 | 说明 |
|---|---|---|
| id | TEXT PK | 日志 ID |
| type | TEXT | 进化类型 |
| trigger | TEXT | 触发来源 |
| description | TEXT | 变更描述 |
| before_state | JSON | 进化前状态 |
| after_state | JSON | 进化后状态 |
| duration | INTEGER | 耗时(ms) |
| verified | INTEGER | 是否已验证(0/1) |
| created_at | INTEGER | 创建时间戳 |
配置
在 .chainlesschain/config.json 中配置:
json
{
"selfEvolvingAI": {
"enabled": true,
"autoAssessment": {
"enabled": true,
"interval": 604800000,
"dimensions": [
"reasoning",
"coding",
"writing",
"translation",
"summarization",
"qa"
],
"minScoreThreshold": 0.85
},
"continualLearning": {
"strategy": "ewc",
"maxDegradation": 0.02,
"maxTrainingDuration": 3600000,
"dataSourcePriority": ["user-feedback", "curated", "synthetic"]
},
"selfDiagnosis": {
"enabled": true,
"interval": 86400000,
"checks": [
"accuracy",
"latency",
"memory",
"output-quality",
"hallucination-rate"
]
},
"selfRepair": {
"enabled": true,
"autoRepair": true,
"requireApproval": false,
"strategies": ["quantize", "rollback", "retrain", "degrade-gracefully"]
},
"behaviorPrediction": {
"enabled": true,
"contextWindow": 20,
"predictionHorizon": 3,
"minConfidence": 0.6
},
"nas": {
"enabled": false,
"targetDevice": "edge",
"searchBudgetHours": 4,
"exportFormats": ["onnx", "tflite"]
}
}
}相关文档
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