feat: MVP v0.5 complete - All P0 features implemented and frontend verified. Backend API structure ready, pending final ES module configuration for deployment.

dist-server/lib/experience-manager.js

@@ -0,0 +1,136 @@
+"use strict";
+/**
+ * 经验管理员 - 知识管理 + 执行记录 + 跨Agent协调
+ */
+var __assign = (this && this.__assign) || function () {
+    __assign = Object.assign || function(t) {
+        for (var s, i = 1, n = arguments.length; i < n; i++) {
+            s = arguments[i];
+            for (var p in s) if (Object.prototype.hasOwnProperty.call(s, p))
+                t[p] = s[p];
+        }
+        return t;
+    };
+    return __assign.apply(this, arguments);
+};
+Object.defineProperty(exports, "__esModule", { value: true });
+exports.ExperienceManager = void 0;
+/**
+ * 经验管理员
+ */
+var ExperienceManager = /** @class */ (function () {
+    function ExperienceManager() {
+        this.executionLog = [];
+        this.decisionLog = [];
+        this.knowledgeBase = new Map();
+        this.records = [];
+    }
+    /**
+     * 记录Agent执行结果
+     */
+    ExperienceManager.prototype.recordExecution = function (record) {
+        this.records.push(record);
+        // Update knowledge base
+        this._updateKnowledge(record);
+    };
+    /**
+     * 获取相关上下文供Agent使用
+     */
+    ExperienceManager.prototype.getContext = function (taskType, keywords) {
+        // Find recent similar executions
+        var recentExecutions = this.records
+            .filter(function (r) { return r.atomicType === taskType; })
+            .slice(-10);
+        // Find relevant knowledge entries
+        var relevantKnowledge = Array.from(this.knowledgeBase.values())
+            .filter(function (k) { return k.taskType === taskType && k.score >= 3; });
+        // Generate suggestion
+        var bestPractice = relevantKnowledge
+            .sort(function (a, b) { return b.score - a.score; })[0];
+        var suggestion = bestPractice
+            ? "Based on ".concat(bestPractice.successCount, " successful executions, avg score ").concat(bestPractice.score.toFixed(1), ": use input pattern ").concat(JSON.stringify(Object.keys(bestPractice.inputPattern)))
+            : 'No prior experience for this task type. Using default approach.';
+        return { recentExecutions: recentExecutions, relevantKnowledge: relevantKnowledge, suggestion: suggestion };
+    };
+    /**
+     * 记录决策
+     */
+    ExperienceManager.prototype.recordDecision = function (decision) {
+        this.decisionLog.push(__assign(__assign({}, decision), { id: "decision-".concat(Date.now()), createdAt: new Date().toISOString() }));
+    };
+    /**
+     * 检查是否需要人工介入
+     */
+    ExperienceManager.prototype.checkInterventionNeeded = function (taskId, score, consecutiveFailures) {
+        if (score <= 2) {
+            return {
+                needed: true,
+                reason: "Agent execution score too low (".concat(score, "/5). Needs human review."),
+            };
+        }
+        if (consecutiveFailures >= 3) {
+            return {
+                needed: true,
+                reason: "".concat(consecutiveFailures, " consecutive failures. Human intervention required."),
+            };
+        }
+        return { needed: false, reason: '' };
+    };
+    /**
+     * 获取项目知识库摘要
+     */
+    ExperienceManager.prototype.getKnowledgeSummary = function () {
+        var entries = Array.from(this.knowledgeBase.values());
+        var byType = {};
+        for (var _i = 0, entries_1 = entries; _i < entries_1.length; _i++) {
+            var e = entries_1[_i];
+            byType[e.taskType] = (byType[e.taskType] || 0) + 1;
+        }
+        var avgScore = entries.length > 0
+            ? entries.reduce(function (sum, e) { return sum + e.score; }, 0) / entries.length
+            : 0;
+        return { totalEntries: entries.length, byType: byType, avgScore: avgScore };
+    };
+    /**
+     * 获取执行历史
+     */
+    ExperienceManager.prototype.getExecutionHistory = function (taskId) {
+        if (taskId) {
+            return this.records.filter(function (r) { return r.taskId === taskId; });
+        }
+        return this.records;
+    };
+    /**
+     * 获取决策历史
+     */
+    ExperienceManager.prototype.getDecisionHistory = function () {
+        return this.decisionLog;
+    };
+    // --- Private ---
+    ExperienceManager.prototype._updateKnowledge = function (record) {
+        var key = "".concat(record.atomicType, "_").concat(record.model);
+        var existing = this.knowledgeBase.get(key);
+        if (existing) {
+            existing.successCount += record.success ? 1 : 0;
+            existing.failCount += record.success ? 0 : 1;
+            // Running average score
+            var totalRuns = existing.successCount + existing.failCount;
+            existing.score = (existing.score * (totalRuns - 1) + record.score) / totalRuns;
+        }
+        else {
+            this.knowledgeBase.set(key, {
+                id: "kb-".concat(Date.now()),
+                taskType: record.atomicType,
+                description: "Pattern for ".concat(record.atomicType, " with ").concat(record.model),
+                inputPattern: record.input,
+                outputPattern: record.output,
+                score: record.score,
+                successCount: record.success ? 1 : 0,
+                failCount: record.success ? 0 : 1,
+                learnedAt: new Date().toISOString(),
+            });
+        }
+    };
+    return ExperienceManager;
+}());
+exports.ExperienceManager = ExperienceManager;