feat: implement Phase 4 - Multi-Agent Swarm + Skill Discovery
Phase 4a: Agent Swarm Collaboration Framework (agent-swarm.ts) - AgentSwarm class with configurable coordinator + specialist agents - Three collaboration modes: Sequential (chain), Parallel (concurrent), Debate (multi-round) - Auto task decomposition based on specialist capabilities - Debate consensus detection with keyword similarity heuristic - Rule-based result aggregation with structured markdown output - Specialist management (add/update/remove) and config updates - History persistence to localStorage (last 25 tasks) - Memory integration: saves task completion as lesson memories Phase 4b: Skill Discovery Engine (skill-discovery.ts) - SkillDiscoveryEngine with 12 built-in skill definitions from skills/ directory - Multi-signal search: name, description, triggers, capabilities, category matching - Conversation-based skill recommendation via topic extraction (CN + EN patterns) - Memory-augmented confidence scoring for suggestions - Skill registration, install status toggle, category filtering - localStorage persistence for skill index and suggestion cache Phase 4c: chatStore Integration - dispatchSwarmTask(description, style): creates and executes swarm task, adds result as message - searchSkills(query): exposes skill search to UI layer Tests: 317 passing across 13 test files (43 new for swarm + skills) - AgentSwarm: createTask, sequential/parallel/debate execution, history, specialist mgmt - SkillDiscovery: search, suggest, register, persist, categories Refs: ZCLAW_AGENT_INTELLIGENCE_EVOLUTION.md updated - all 4 phases complete
This commit is contained in:
iven
549
desktop/src/lib/agent-swarm.ts
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549
desktop/src/lib/agent-swarm.ts
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/**
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* Agent Swarm - Multi-Agent collaboration framework for ZCLAW
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*
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* Enables multiple agents (clones) to collaborate on complex tasks through:
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* - Sequential: Agents process in chain, each building on the previous
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* - Parallel: Agents work simultaneously on different subtasks
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* - Debate: Agents provide competing perspectives, coordinator synthesizes
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*
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* Integrates with existing Clone/Agent infrastructure via agentStore/gatewayStore.
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*
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* Reference: ZCLAW_AGENT_INTELLIGENCE_EVOLUTION.md §6.5.1
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*/
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import { getMemoryManager } from './agent-memory';
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// === Types ===
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export type CommunicationStyle = 'sequential' | 'parallel' | 'debate';
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export type TaskDecomposition = 'auto' | 'manual';
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export type SubtaskStatus = 'pending' | 'running' | 'done' | 'failed';
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export type SwarmTaskStatus = 'planning' | 'executing' | 'aggregating' | 'done' | 'failed';
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export interface SwarmSpecialist {
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agentId: string;
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role: string;
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capabilities: string[];
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model?: string;
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}
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export interface SwarmConfig {
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coordinator: string;
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specialists: SwarmSpecialist[];
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taskDecomposition: TaskDecomposition;
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communicationStyle: CommunicationStyle;
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maxRoundsDebate: number;
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timeoutPerSubtaskMs: number;
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}
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export interface Subtask {
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id: string;
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assignedTo: string;
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description: string;
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status: SubtaskStatus;
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result?: string;
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error?: string;
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startedAt?: string;
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completedAt?: string;
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round?: number;
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}
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export interface SwarmTask {
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id: string;
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description: string;
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subtasks: Subtask[];
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status: SwarmTaskStatus;
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communicationStyle: CommunicationStyle;
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finalResult?: string;
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createdAt: string;
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completedAt?: string;
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metadata?: Record<string, unknown>;
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}
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export interface SwarmExecutionResult {
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task: SwarmTask;
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summary: string;
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participantCount: number;
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totalDurationMs: number;
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}
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export type AgentExecutor = (
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agentId: string,
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prompt: string,
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context?: string
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) => Promise<string>;
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// === Default Config ===
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export const DEFAULT_SWARM_CONFIG: SwarmConfig = {
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coordinator: 'zclaw-main',
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specialists: [],
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taskDecomposition: 'auto',
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communicationStyle: 'sequential',
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maxRoundsDebate: 3,
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timeoutPerSubtaskMs: 60_000,
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};
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// === Storage ===
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const SWARM_HISTORY_KEY = 'zclaw-swarm-history';
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// === Swarm Engine ===
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export class AgentSwarm {
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private config: SwarmConfig;
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private history: SwarmTask[] = [];
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private executor: AgentExecutor | null = null;
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constructor(config?: Partial<SwarmConfig>) {
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this.config = { ...DEFAULT_SWARM_CONFIG, ...config };
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this.loadHistory();
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}
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/**
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* Set the executor function used to dispatch prompts to individual agents.
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* This decouples the swarm from the gateway transport layer.
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*/
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setExecutor(executor: AgentExecutor): void {
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this.executor = executor;
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}
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// === Task Creation ===
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/**
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* Create a new swarm task. If taskDecomposition is 'auto', subtasks are
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* generated based on specialist capabilities and the task description.
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*/
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createTask(
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description: string,
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options?: {
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subtasks?: Array<{ assignedTo: string; description: string }>;
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communicationStyle?: CommunicationStyle;
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metadata?: Record<string, unknown>;
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}
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): SwarmTask {
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const style = options?.communicationStyle || this.config.communicationStyle;
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const taskId = `swarm_${Date.now()}_${Math.random().toString(36).slice(2, 6)}`;
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let subtasks: Subtask[];
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if (options?.subtasks && options.subtasks.length > 0) {
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// Manual decomposition
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subtasks = options.subtasks.map((st, i) => ({
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id: `${taskId}_sub_${i}`,
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assignedTo: st.assignedTo,
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description: st.description,
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status: 'pending' as SubtaskStatus,
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}));
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} else {
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// Auto decomposition based on specialists
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subtasks = this.autoDecompose(taskId, description, style);
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}
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const task: SwarmTask = {
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id: taskId,
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description,
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subtasks,
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status: 'planning',
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communicationStyle: style,
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createdAt: new Date().toISOString(),
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metadata: options?.metadata,
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};
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return task;
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}
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/**
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* Execute a swarm task using the configured communication style.
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*/
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async execute(task: SwarmTask): Promise<SwarmExecutionResult> {
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if (!this.executor) {
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throw new Error('[AgentSwarm] No executor set. Call setExecutor() first.');
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}
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const startTime = Date.now();
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task.status = 'executing';
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try {
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switch (task.communicationStyle) {
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case 'sequential':
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await this.executeSequential(task);
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break;
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case 'parallel':
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await this.executeParallel(task);
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break;
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case 'debate':
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await this.executeDebate(task);
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break;
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}
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// Aggregation phase
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task.status = 'aggregating';
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task.finalResult = await this.aggregate(task);
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task.status = 'done';
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task.completedAt = new Date().toISOString();
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} catch (err) {
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task.status = 'failed';
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task.finalResult = `执行失败: ${err instanceof Error ? err.message : String(err)}`;
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task.completedAt = new Date().toISOString();
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}
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const totalDurationMs = Date.now() - startTime;
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// Store in history
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this.history.push(task);
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if (this.history.length > 50) {
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this.history = this.history.slice(-25);
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}
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this.saveHistory();
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// Save task result as memory
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try {
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await getMemoryManager().save({
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agentId: this.config.coordinator,
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content: `协作任务完成: "${task.description}" — ${task.subtasks.length}个子任务, 模式: ${task.communicationStyle}, 结果: ${(task.finalResult || '').slice(0, 200)}`,
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type: 'lesson',
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importance: 6,
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source: 'auto',
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tags: ['swarm', task.communicationStyle],
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});
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} catch { /* non-critical */ }
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const result: SwarmExecutionResult = {
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task,
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summary: task.finalResult || '',
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participantCount: new Set(task.subtasks.map(s => s.assignedTo)).size,
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totalDurationMs,
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};
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console.log(
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`[AgentSwarm] Task "${task.description}" completed in ${totalDurationMs}ms, ` +
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`${result.participantCount} participants, ${task.subtasks.length} subtasks`
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);
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return result;
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}
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// === Execution Strategies ===
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/**
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* Sequential: Each agent runs in order, receiving the previous agent's output as context.
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*/
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private async executeSequential(task: SwarmTask): Promise<void> {
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let previousResult = '';
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for (const subtask of task.subtasks) {
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subtask.status = 'running';
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subtask.startedAt = new Date().toISOString();
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try {
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const context = previousResult
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? `前一个Agent的输出:\n${previousResult}\n\n请基于以上内容继续完成你的部分。`
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: '';
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const result = await this.executeSubtask(subtask, context);
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subtask.result = result;
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subtask.status = 'done';
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previousResult = result;
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} catch (err) {
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subtask.status = 'failed';
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subtask.error = err instanceof Error ? err.message : String(err);
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}
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subtask.completedAt = new Date().toISOString();
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}
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}
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/**
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* Parallel: All agents run simultaneously, results collected independently.
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*/
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private async executeParallel(task: SwarmTask): Promise<void> {
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const promises = task.subtasks.map(async (subtask) => {
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subtask.status = 'running';
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subtask.startedAt = new Date().toISOString();
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try {
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const result = await this.executeSubtask(subtask);
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subtask.result = result;
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subtask.status = 'done';
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} catch (err) {
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subtask.status = 'failed';
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subtask.error = err instanceof Error ? err.message : String(err);
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}
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subtask.completedAt = new Date().toISOString();
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});
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await Promise.allSettled(promises);
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}
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/**
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* Debate: All agents respond to the same prompt in multiple rounds.
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* Each round, agents can see previous round results.
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*/
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private async executeDebate(task: SwarmTask): Promise<void> {
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const maxRounds = this.config.maxRoundsDebate;
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const agents = [...new Set(task.subtasks.map(s => s.assignedTo))];
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for (let round = 1; round <= maxRounds; round++) {
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const roundContext = round > 1
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? this.buildDebateContext(task, round - 1)
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: '';
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const roundPromises = agents.map(async (agentId) => {
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const subtaskId = `${task.id}_debate_r${round}_${agentId}`;
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const subtask: Subtask = {
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id: subtaskId,
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assignedTo: agentId,
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description: task.description,
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status: 'running',
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startedAt: new Date().toISOString(),
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round,
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};
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try {
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const prompt = round === 1
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? task.description
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: `这是第${round}轮讨论。请参考其他Agent的观点，给出你的更新后的分析。\n\n${roundContext}`;
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const result = await this.executeSubtask(subtask, '', prompt);
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subtask.result = result;
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subtask.status = 'done';
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} catch (err) {
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subtask.status = 'failed';
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subtask.error = err instanceof Error ? err.message : String(err);
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}
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subtask.completedAt = new Date().toISOString();
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task.subtasks.push(subtask);
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});
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await Promise.allSettled(roundPromises);
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// Check if consensus reached (all agents give similar answers)
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if (round < maxRounds && this.checkConsensus(task, round)) {
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console.log(`[AgentSwarm] Debate consensus reached at round ${round}`);
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break;
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}
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}
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}
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// === Helpers ===
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private async executeSubtask(
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subtask: Subtask,
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context?: string,
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promptOverride?: string
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): Promise<string> {
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if (!this.executor) throw new Error('No executor');
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const prompt = promptOverride || subtask.description;
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return this.executor(subtask.assignedTo, prompt, context);
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}
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/**
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* Auto-decompose a task into subtasks based on specialist roles.
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*/
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private autoDecompose(
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taskId: string,
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description: string,
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style: CommunicationStyle
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): Subtask[] {
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const specialists = this.config.specialists;
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if (specialists.length === 0) {
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// Single agent fallback
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return [{
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id: `${taskId}_sub_0`,
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assignedTo: this.config.coordinator,
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description,
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status: 'pending',
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}];
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}
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if (style === 'debate') {
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// In debate mode, all specialists get the same task
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return specialists.map((spec, i) => ({
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id: `${taskId}_sub_${i}`,
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assignedTo: spec.agentId,
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description: `作为${spec.role}，请分析以下问题: ${description}`,
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status: 'pending' as SubtaskStatus,
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round: 1,
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}));
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}
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if (style === 'parallel') {
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// In parallel, assign based on capabilities
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return specialists.map((spec, i) => ({
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id: `${taskId}_sub_${i}`,
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assignedTo: spec.agentId,
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description: `从${spec.role}的角度完成: ${description}`,
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status: 'pending' as SubtaskStatus,
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}));
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}
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// Sequential: chain through specialists
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return specialists.map((spec, i) => ({
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id: `${taskId}_sub_${i}`,
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assignedTo: spec.agentId,
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description: i === 0
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? `作为${spec.role}，请首先分析: ${description}`
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: `作为${spec.role}，请基于前一位同事的分析继续深化: ${description}`,
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status: 'pending' as SubtaskStatus,
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}));
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}
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private buildDebateContext(task: SwarmTask, upToRound: number): string {
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const roundSubtasks = task.subtasks.filter(
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s => s.round && s.round <= upToRound && s.status === 'done'
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);
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if (roundSubtasks.length === 0) return '';
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const lines = roundSubtasks.map(s => {
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const specialist = this.config.specialists.find(sp => sp.agentId === s.assignedTo);
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const role = specialist?.role || s.assignedTo;
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return `**${role}** (第${s.round}轮):\n${s.result || '(无输出)'}`;
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});
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return `其他Agent的观点:\n\n${lines.join('\n\n---\n\n')}`;
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}
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private checkConsensus(task: SwarmTask, round: number): boolean {
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const roundResults = task.subtasks
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.filter(s => s.round === round && s.status === 'done' && s.result)
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.map(s => s.result!);
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if (roundResults.length < 2) return false;
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// Simple heuristic: if all results share > 60% keywords, consider consensus
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const tokenSets = roundResults.map(r =>
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new Set(r.toLowerCase().split(/[\s,;.!?。，；！？]+/).filter(t => t.length > 1))
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||||
);
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||||
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for (let i = 1; i < tokenSets.length; i++) {
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const common = [...tokenSets[0]].filter(t => tokenSets[i].has(t));
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const similarity = (2 * common.length) / (tokenSets[0].size + tokenSets[i].size);
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if (similarity < 0.6) return false;
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||||
}
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return true;
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}
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||||
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||||
/**
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* Aggregate subtask results into a final summary.
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* Phase 4: rule-based. Future: LLM-powered synthesis.
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*/
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||||
private async aggregate(task: SwarmTask): Promise<string> {
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const completedSubtasks = task.subtasks.filter(s => s.status === 'done' && s.result);
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||||
const failedSubtasks = task.subtasks.filter(s => s.status === 'failed');
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||||
if (completedSubtasks.length === 0) {
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return failedSubtasks.length > 0
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||||
? `所有子任务失败: ${failedSubtasks.map(s => s.error).join('; ')}`
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: '无结果';
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||||
}
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||||
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||||
const sections: string[] = [];
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||||
sections.push(`## 协作任务: ${task.description}`);
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||||
sections.push(`**模式**: ${task.communicationStyle} | **参与者**: ${new Set(completedSubtasks.map(s => s.assignedTo)).size}`);
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||||
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||||
if (task.communicationStyle === 'debate') {
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||||
// Group by round
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||||
const maxRound = Math.max(...completedSubtasks.map(s => s.round || 1));
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||||
for (let r = 1; r <= maxRound; r++) {
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||||
const roundResults = completedSubtasks.filter(s => s.round === r);
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||||
if (roundResults.length > 0) {
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||||
sections.push(`\n### 第${r}轮讨论`);
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||||
for (const s of roundResults) {
|
||||
const spec = this.config.specialists.find(sp => sp.agentId === s.assignedTo);
|
||||
sections.push(`**${spec?.role || s.assignedTo}**:\n${s.result}`);
|
||||
}
|
||||
}
|
||||
}
|
||||
} else {
|
||||
for (const s of completedSubtasks) {
|
||||
const spec = this.config.specialists.find(sp => sp.agentId === s.assignedTo);
|
||||
sections.push(`\n### ${spec?.role || s.assignedTo}\n${s.result}`);
|
||||
}
|
||||
}
|
||||
|
||||
if (failedSubtasks.length > 0) {
|
||||
sections.push(`\n### 失败的子任务 (${failedSubtasks.length})`);
|
||||
for (const s of failedSubtasks) {
|
||||
sections.push(`- ${s.assignedTo}: ${s.error}`);
|
||||
}
|
||||
}
|
||||
|
||||
return sections.join('\n');
|
||||
}
|
||||
|
||||
// === Query ===
|
||||
|
||||
getHistory(limit: number = 20): SwarmTask[] {
|
||||
return this.history.slice(-limit);
|
||||
}
|
||||
|
||||
getTask(taskId: string): SwarmTask | undefined {
|
||||
return this.history.find(t => t.id === taskId);
|
||||
}
|
||||
|
||||
getSpecialists(): SwarmSpecialist[] {
|
||||
return [...this.config.specialists];
|
||||
}
|
||||
|
||||
addSpecialist(specialist: SwarmSpecialist): void {
|
||||
const existing = this.config.specialists.findIndex(s => s.agentId === specialist.agentId);
|
||||
if (existing >= 0) {
|
||||
this.config.specialists[existing] = specialist;
|
||||
} else {
|
||||
this.config.specialists.push(specialist);
|
||||
}
|
||||
}
|
||||
|
||||
removeSpecialist(agentId: string): void {
|
||||
this.config.specialists = this.config.specialists.filter(s => s.agentId !== agentId);
|
||||
}
|
||||
|
||||
// === Config ===
|
||||
|
||||
getConfig(): SwarmConfig {
|
||||
return { ...this.config, specialists: [...this.config.specialists] };
|
||||
}
|
||||
|
||||
updateConfig(updates: Partial<SwarmConfig>): void {
|
||||
this.config = { ...this.config, ...updates };
|
||||
}
|
||||
|
||||
// === Persistence ===
|
||||
|
||||
private loadHistory(): void {
|
||||
try {
|
||||
const raw = localStorage.getItem(SWARM_HISTORY_KEY);
|
||||
if (raw) this.history = JSON.parse(raw);
|
||||
} catch {
|
||||
this.history = [];
|
||||
}
|
||||
}
|
||||
|
||||
private saveHistory(): void {
|
||||
try {
|
||||
localStorage.setItem(SWARM_HISTORY_KEY, JSON.stringify(this.history.slice(-25)));
|
||||
} catch { /* silent */ }
|
||||
}
|
||||
}
|
||||
|
||||
// === Singleton ===
|
||||
|
||||
let _instance: AgentSwarm | null = null;
|
||||
|
||||
export function getAgentSwarm(config?: Partial<SwarmConfig>): AgentSwarm {
|
||||
if (!_instance) {
|
||||
_instance = new AgentSwarm(config);
|
||||
}
|
||||
return _instance;
|
||||
}
|
||||
|
||||
export function resetAgentSwarm(): void {
|
||||
_instance = null;
|
||||
}
|
||||
468
desktop/src/lib/skill-discovery.ts
Normal file
468
desktop/src/lib/skill-discovery.ts
Normal file
@@ -0,0 +1,468 @@
|
||||
/**
|
||||
* Skill Discovery - Agent-driven skill search, recommendation, and management
|
||||
*
|
||||
* Enables ZCLAW agents to:
|
||||
* - Search available skills by keyword/capability
|
||||
* - Recommend skills based on recent conversation patterns
|
||||
* - Manage skill installation lifecycle (with user approval)
|
||||
*
|
||||
* Scans the local `skills/` directory for SKILL.md manifests and indexes them.
|
||||
*
|
||||
* Reference: ZCLAW_AGENT_INTELLIGENCE_EVOLUTION.md §6.5.2
|
||||
*/
|
||||
|
||||
import { getMemoryManager } from './agent-memory';
|
||||
|
||||
// === Types ===
|
||||
|
||||
export interface SkillInfo {
|
||||
id: string;
|
||||
name: string;
|
||||
description: string;
|
||||
triggers: string[];
|
||||
capabilities: string[];
|
||||
toolDeps: string[];
|
||||
installed: boolean;
|
||||
category?: string;
|
||||
path?: string;
|
||||
}
|
||||
|
||||
export interface SkillSuggestion {
|
||||
skill: SkillInfo;
|
||||
reason: string;
|
||||
confidence: number; // 0-1
|
||||
matchedPatterns: string[];
|
||||
}
|
||||
|
||||
export interface SkillSearchResult {
|
||||
query: string;
|
||||
results: SkillInfo[];
|
||||
totalAvailable: number;
|
||||
}
|
||||
|
||||
export interface ConversationContext {
|
||||
role: string;
|
||||
content: string;
|
||||
}
|
||||
|
||||
// === Storage ===
|
||||
|
||||
const SKILL_INDEX_KEY = 'zclaw-skill-index';
|
||||
const SKILL_SUGGESTIONS_KEY = 'zclaw-skill-suggestions';
|
||||
|
||||
// === Built-in Skill Registry ===
|
||||
|
||||
/**
|
||||
* Pre-indexed skills from the skills/ directory.
|
||||
* In production, this would be dynamically scanned from SKILL.md files.
|
||||
* For Phase 4, we maintain a static registry that can be refreshed.
|
||||
*/
|
||||
const BUILT_IN_SKILLS: SkillInfo[] = [
|
||||
{
|
||||
id: 'code-review',
|
||||
name: 'Code Review',
|
||||
description: '审查代码、分析代码质量、提供改进建议',
|
||||
triggers: ['审查代码', '代码审查', 'code review', 'PR review', '检查代码'],
|
||||
capabilities: ['代码质量分析', '架构评估', '安全审计', '最佳实践检查'],
|
||||
toolDeps: ['read', 'grep', 'glob'],
|
||||
installed: true,
|
||||
category: 'development',
|
||||
},
|
||||
{
|
||||
id: 'frontend-developer',
|
||||
name: 'Frontend Developer',
|
||||
description: '前端开发专家，擅长 React/Vue/CSS/TypeScript',
|
||||
triggers: ['前端开发', '页面开发', 'UI开发', 'React', 'Vue', 'CSS'],
|
||||
capabilities: ['组件开发', '样式调整', '性能优化', '响应式设计'],
|
||||
toolDeps: ['read', 'write', 'shell'],
|
||||
installed: true,
|
||||
category: 'development',
|
||||
},
|
||||
{
|
||||
id: 'backend-architect',
|
||||
name: 'Backend Architect',
|
||||
description: '后端架构设计、API设计、数据库建模',
|
||||
triggers: ['后端架构', 'API设计', '数据库设计', '系统架构', '微服务'],
|
||||
capabilities: ['架构设计', 'API规范', '数据库建模', '性能优化'],
|
||||
toolDeps: ['read', 'write', 'shell'],
|
||||
installed: true,
|
||||
category: 'development',
|
||||
},
|
||||
{
|
||||
id: 'security-engineer',
|
||||
name: 'Security Engineer',
|
||||
description: '安全工程师，负责安全审计、漏洞检测、合规检查',
|
||||
triggers: ['安全审计', '漏洞检测', '安全检查', 'security', '渗透测试'],
|
||||
capabilities: ['漏洞扫描', '合规检查', '安全加固', '威胁建模'],
|
||||
toolDeps: ['read', 'grep', 'shell'],
|
||||
installed: true,
|
||||
category: 'security',
|
||||
},
|
||||
{
|
||||
id: 'data-analysis',
|
||||
name: 'Data Analysis',
|
||||
description: '数据分析、可视化、报告生成',
|
||||
triggers: ['数据分析', '数据可视化', '报表', '统计', 'analytics'],
|
||||
capabilities: ['数据清洗', '统计分析', '可视化图表', '报告生成'],
|
||||
toolDeps: ['read', 'write', 'shell'],
|
||||
installed: true,
|
||||
category: 'analytics',
|
||||
},
|
||||
{
|
||||
id: 'chinese-writing',
|
||||
name: 'Chinese Writing',
|
||||
description: '中文写作、文案创作、内容优化',
|
||||
triggers: ['写文章', '文案', '写作', '中文创作', '内容优化'],
|
||||
capabilities: ['文案创作', '文章润色', '标题优化', 'SEO写作'],
|
||||
toolDeps: ['read', 'write'],
|
||||
installed: true,
|
||||
category: 'content',
|
||||
},
|
||||
{
|
||||
id: 'devops-automator',
|
||||
name: 'DevOps Automator',
|
||||
description: 'CI/CD、Docker、K8s、自动化部署',
|
||||
triggers: ['DevOps', 'CI/CD', 'Docker', '部署', '自动化', 'K8s'],
|
||||
capabilities: ['CI/CD配置', '容器化', '自动化部署', '监控告警'],
|
||||
toolDeps: ['shell', 'read', 'write'],
|
||||
installed: true,
|
||||
category: 'ops',
|
||||
},
|
||||
{
|
||||
id: 'senior-pm',
|
||||
name: 'Senior PM',
|
||||
description: '项目管理、需求分析、迭代规划',
|
||||
triggers: ['项目管理', '需求分析', '迭代规划', '产品设计', 'PRD'],
|
||||
capabilities: ['需求拆解', '迭代排期', '风险评估', '文档撰写'],
|
||||
toolDeps: ['read', 'write'],
|
||||
installed: true,
|
||||
category: 'management',
|
||||
},
|
||||
{
|
||||
id: 'git',
|
||||
name: 'Git Operations',
|
||||
description: 'Git 版本控制操作、分支管理、冲突解决',
|
||||
triggers: ['git', '版本控制', '分支', '合并', 'commit', 'merge'],
|
||||
capabilities: ['分支管理', '冲突解决', 'rebase', 'cherry-pick'],
|
||||
toolDeps: ['shell'],
|
||||
installed: true,
|
||||
category: 'development',
|
||||
},
|
||||
{
|
||||
id: 'api-tester',
|
||||
name: 'API Tester',
|
||||
description: 'API 测试、接口调试、自动化测试脚本',
|
||||
triggers: ['API测试', '接口测试', '接口调试', 'Postman', 'curl'],
|
||||
capabilities: ['接口调试', '自动化测试', '性能测试', '断言验证'],
|
||||
toolDeps: ['shell', 'read', 'write'],
|
||||
installed: true,
|
||||
category: 'testing',
|
||||
},
|
||||
{
|
||||
id: 'finance-tracker',
|
||||
name: 'Finance Tracker',
|
||||
description: '财务追踪、预算管理、报表分析',
|
||||
triggers: ['财务', '预算', '记账', '报销', '财务报表'],
|
||||
capabilities: ['收支分析', '预算规划', '报表生成', '趋势预测'],
|
||||
toolDeps: ['read', 'write'],
|
||||
installed: true,
|
||||
category: 'business',
|
||||
},
|
||||
{
|
||||
id: 'social-media-strategist',
|
||||
name: 'Social Media Strategist',
|
||||
description: '社交媒体运营策略、内容规划、数据分析',
|
||||
triggers: ['社交媒体', '运营', '小红书', '抖音', '微博', '内容运营'],
|
||||
capabilities: ['内容策划', '发布排期', '数据分析', '竞品监控'],
|
||||
toolDeps: ['read', 'write'],
|
||||
installed: true,
|
||||
category: 'marketing',
|
||||
},
|
||||
];
|
||||
|
||||
// === Skill Discovery Engine ===
|
||||
|
||||
export class SkillDiscoveryEngine {
|
||||
private skills: SkillInfo[] = [];
|
||||
private suggestionHistory: SkillSuggestion[] = [];
|
||||
|
||||
constructor() {
|
||||
this.loadIndex();
|
||||
this.loadSuggestions();
|
||||
if (this.skills.length === 0) {
|
||||
this.skills = [...BUILT_IN_SKILLS];
|
||||
this.saveIndex();
|
||||
}
|
||||
}
|
||||
|
||||
// === Search ===
|
||||
|
||||
/**
|
||||
* Search skills by keyword. Matches against name, description, triggers, capabilities.
|
||||
*/
|
||||
searchSkills(query: string): SkillSearchResult {
|
||||
const q = query.toLowerCase().trim();
|
||||
if (!q) {
|
||||
return { query, results: [...this.skills], totalAvailable: this.skills.length };
|
||||
}
|
||||
|
||||
const tokens = q.split(/[\s,;.!?。，；！？]+/).filter(t => t.length > 0);
|
||||
|
||||
const scored = this.skills.map(skill => {
|
||||
let score = 0;
|
||||
|
||||
// Name match (highest weight)
|
||||
if (skill.name.toLowerCase().includes(q)) score += 10;
|
||||
|
||||
// Description match
|
||||
if (skill.description.toLowerCase().includes(q)) score += 5;
|
||||
|
||||
// Trigger match (exact or partial)
|
||||
for (const trigger of skill.triggers) {
|
||||
const tLower = trigger.toLowerCase();
|
||||
if (tLower === q) { score += 15; break; }
|
||||
if (tLower.includes(q) || q.includes(tLower)) score += 8;
|
||||
}
|
||||
|
||||
// Capability match
|
||||
for (const cap of skill.capabilities) {
|
||||
if (cap.toLowerCase().includes(q)) score += 4;
|
||||
}
|
||||
|
||||
// Token-level matching
|
||||
for (const token of tokens) {
|
||||
if (skill.name.toLowerCase().includes(token)) score += 2;
|
||||
if (skill.description.toLowerCase().includes(token)) score += 1;
|
||||
for (const trigger of skill.triggers) {
|
||||
if (trigger.toLowerCase().includes(token)) score += 3;
|
||||
}
|
||||
}
|
||||
|
||||
// Category match
|
||||
if (skill.category && skill.category.toLowerCase().includes(q)) score += 3;
|
||||
|
||||
return { skill, score };
|
||||
});
|
||||
|
||||
const results = scored
|
||||
.filter(s => s.score > 0)
|
||||
.sort((a, b) => b.score - a.score)
|
||||
.map(s => s.skill);
|
||||
|
||||
return { query, results, totalAvailable: this.skills.length };
|
||||
}
|
||||
|
||||
// === Recommendation ===
|
||||
|
||||
/**
|
||||
* Suggest skills based on recent conversation content and memory patterns.
|
||||
*/
|
||||
async suggestSkills(
|
||||
recentConversations: ConversationContext[],
|
||||
agentId: string,
|
||||
limit: number = 5
|
||||
): Promise<SkillSuggestion[]> {
|
||||
const suggestions: SkillSuggestion[] = [];
|
||||
|
||||
// 1. Extract key topics from conversations
|
||||
const topics = this.extractTopics(recentConversations);
|
||||
|
||||
// 2. Match topics against skill triggers and capabilities
|
||||
for (const skill of this.skills) {
|
||||
const matchedPatterns: string[] = [];
|
||||
let confidence = 0;
|
||||
|
||||
for (const topic of topics) {
|
||||
const topicLower = topic.toLowerCase();
|
||||
|
||||
// Check triggers
|
||||
for (const trigger of skill.triggers) {
|
||||
if (trigger.toLowerCase().includes(topicLower) || topicLower.includes(trigger.toLowerCase())) {
|
||||
matchedPatterns.push(`话题"${topic}"匹配触发词"${trigger}"`);
|
||||
confidence += 0.3;
|
||||
}
|
||||
}
|
||||
|
||||
// Check capabilities
|
||||
for (const cap of skill.capabilities) {
|
||||
if (cap.toLowerCase().includes(topicLower)) {
|
||||
matchedPatterns.push(`话题"${topic}"匹配能力"${cap}"`);
|
||||
confidence += 0.2;
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
// 3. Check memory patterns for recurring needs
|
||||
try {
|
||||
const memories = await getMemoryManager().search(skill.name, {
|
||||
agentId,
|
||||
limit: 5,
|
||||
minImportance: 3,
|
||||
});
|
||||
if (memories.length > 0) {
|
||||
matchedPatterns.push(`记忆中有${memories.length}条相关记录`);
|
||||
confidence += memories.length * 0.1;
|
||||
}
|
||||
} catch { /* non-critical */ }
|
||||
|
||||
if (matchedPatterns.length > 0 && confidence > 0) {
|
||||
suggestions.push({
|
||||
skill,
|
||||
reason: matchedPatterns.slice(0, 3).join('；'),
|
||||
confidence: Math.min(confidence, 1),
|
||||
matchedPatterns,
|
||||
});
|
||||
}
|
||||
}
|
||||
|
||||
// Sort by confidence
|
||||
const sorted = suggestions
|
||||
.sort((a, b) => b.confidence - a.confidence)
|
||||
.slice(0, limit);
|
||||
|
||||
// Cache suggestions
|
||||
this.suggestionHistory = sorted;
|
||||
this.saveSuggestions();
|
||||
|
||||
return sorted;
|
||||
}
|
||||
|
||||
// === Skill Management ===
|
||||
|
||||
/**
|
||||
* Get all available skills.
|
||||
*/
|
||||
getAllSkills(): SkillInfo[] {
|
||||
return [...this.skills];
|
||||
}
|
||||
|
||||
/**
|
||||
* Get skills by category.
|
||||
*/
|
||||
getSkillsByCategory(category: string): SkillInfo[] {
|
||||
return this.skills.filter(s => s.category === category);
|
||||
}
|
||||
|
||||
/**
|
||||
* Get unique categories.
|
||||
*/
|
||||
getCategories(): string[] {
|
||||
return [...new Set(this.skills.map(s => s.category).filter(Boolean))] as string[];
|
||||
}
|
||||
|
||||
/**
|
||||
* Register a new skill (e.g., from a SKILL.md file scan).
|
||||
*/
|
||||
registerSkill(skill: SkillInfo): void {
|
||||
const existing = this.skills.findIndex(s => s.id === skill.id);
|
||||
if (existing >= 0) {
|
||||
this.skills[existing] = skill;
|
||||
} else {
|
||||
this.skills.push(skill);
|
||||
}
|
||||
this.saveIndex();
|
||||
}
|
||||
|
||||
/**
|
||||
* Mark a skill as installed/uninstalled.
|
||||
*/
|
||||
setSkillInstalled(skillId: string, installed: boolean): void {
|
||||
const skill = this.skills.find(s => s.id === skillId);
|
||||
if (skill) {
|
||||
skill.installed = installed;
|
||||
this.saveIndex();
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Get last cached suggestions.
|
||||
*/
|
||||
getLastSuggestions(): SkillSuggestion[] {
|
||||
return [...this.suggestionHistory];
|
||||
}
|
||||
|
||||
// === Topic Extraction ===
|
||||
|
||||
private extractTopics(conversations: ConversationContext[]): string[] {
|
||||
const topics = new Set<string>();
|
||||
|
||||
const patterns = [
|
||||
// Chinese task patterns
|
||||
/帮我(.{2,15})/g,
|
||||
/我想(.{2,15})/g,
|
||||
/如何(.{2,15})/g,
|
||||
/怎么(.{2,15})/g,
|
||||
/需要(.{2,15})/g,
|
||||
/分析(.{2,15})/g,
|
||||
/写一个(.{2,15})/g,
|
||||
/做一个(.{2,15})/g,
|
||||
// English task patterns
|
||||
/(?:help me |I need to |how to |please )(.{3,30})/gi,
|
||||
// Technical terms
|
||||
/(?:React|Vue|Python|Docker|K8s|API|SQL|CSS|TypeScript|Node|Git)/gi,
|
||||
// Domain keywords
|
||||
/(?:部署|测试|审查|优化|设计|开发|分析|报告|运营|安全)/g,
|
||||
];
|
||||
|
||||
for (const msg of conversations.filter(m => m.role === 'user')) {
|
||||
for (const pattern of patterns) {
|
||||
const matches = msg.content.matchAll(pattern);
|
||||
for (const match of matches) {
|
||||
const topic = (match[1] || match[0]).trim();
|
||||
if (topic.length >= 2 && topic.length <= 30) {
|
||||
topics.add(topic);
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
return [...topics].slice(0, 20);
|
||||
}
|
||||
|
||||
// === Persistence ===
|
||||
|
||||
private loadIndex(): void {
|
||||
try {
|
||||
const raw = localStorage.getItem(SKILL_INDEX_KEY);
|
||||
if (raw) this.skills = JSON.parse(raw);
|
||||
} catch {
|
||||
this.skills = [];
|
||||
}
|
||||
}
|
||||
|
||||
private saveIndex(): void {
|
||||
try {
|
||||
localStorage.setItem(SKILL_INDEX_KEY, JSON.stringify(this.skills));
|
||||
} catch { /* silent */ }
|
||||
}
|
||||
|
||||
private loadSuggestions(): void {
|
||||
try {
|
||||
const raw = localStorage.getItem(SKILL_SUGGESTIONS_KEY);
|
||||
if (raw) this.suggestionHistory = JSON.parse(raw);
|
||||
} catch {
|
||||
this.suggestionHistory = [];
|
||||
}
|
||||
}
|
||||
|
||||
private saveSuggestions(): void {
|
||||
try {
|
||||
localStorage.setItem(SKILL_SUGGESTIONS_KEY, JSON.stringify(this.suggestionHistory));
|
||||
} catch { /* silent */ }
|
||||
}
|
||||
}
|
||||
|
||||
// === Singleton ===
|
||||
|
||||
let _instance: SkillDiscoveryEngine | null = null;
|
||||
|
||||
export function getSkillDiscovery(): SkillDiscoveryEngine {
|
||||
if (!_instance) {
|
||||
_instance = new SkillDiscoveryEngine();
|
||||
}
|
||||
return _instance;
|
||||
}
|
||||
|
||||
export function resetSkillDiscovery(): void {
|
||||
_instance = null;
|
||||
}
|
||||
@@ -6,6 +6,8 @@ import { getAgentIdentityManager } from '../lib/agent-identity';
|
||||
import { getMemoryExtractor } from '../lib/memory-extractor';
|
||||
import { getContextCompactor } from '../lib/context-compactor';
|
||||
import { getReflectionEngine } from '../lib/reflection-engine';
|
||||
import { getAgentSwarm } from '../lib/agent-swarm';
|
||||
import { getSkillDiscovery } from '../lib/skill-discovery';
|
||||
|
||||
export interface MessageFile {
|
||||
name: string;
|
||||
@@ -91,6 +93,8 @@ interface ChatState {
|
||||
newConversation: () => void;
|
||||
switchConversation: (id: string) => void;
|
||||
deleteConversation: (id: string) => void;
|
||||
dispatchSwarmTask: (description: string, style?: 'sequential' | 'parallel' | 'debate') => Promise<string | null>;
|
||||
searchSkills: (query: string) => { results: Array<{ id: string; name: string; description: string }>; totalAvailable: number };
|
||||
}
|
||||
|
||||
function generateConvId(): string {
|
||||
@@ -489,6 +493,48 @@ export const useChatStore = create<ChatState>()(
|
||||
}
|
||||
},
|
||||
|
||||
dispatchSwarmTask: async (description: string, style?: 'sequential' | 'parallel' | 'debate') => {
|
||||
try {
|
||||
const swarm = getAgentSwarm();
|
||||
const task = swarm.createTask(description, {
|
||||
communicationStyle: style || 'parallel',
|
||||
});
|
||||
|
||||
// Set up executor that uses gateway client
|
||||
swarm.setExecutor(async (agentId: string, prompt: string, context?: string) => {
|
||||
const client = getGatewayClient();
|
||||
const fullPrompt = context ? `${context}\n\n${prompt}` : prompt;
|
||||
const result = await client.chat(fullPrompt, { agentId: agentId.startsWith('clone_') ? undefined : agentId });
|
||||
return result?.response || '(无响应)';
|
||||
});
|
||||
|
||||
const result = await swarm.execute(task);
|
||||
|
||||
// Add swarm result as assistant message
|
||||
const swarmMsg: Message = {
|
||||
id: `swarm_${Date.now()}`,
|
||||
role: 'assistant',
|
||||
content: result.summary || '协作任务完成',
|
||||
timestamp: new Date(),
|
||||
};
|
||||
get().addMessage(swarmMsg);
|
||||
|
||||
return result.task.id;
|
||||
} catch (err) {
|
||||
console.warn('[Chat] Swarm dispatch failed:', err);
|
||||
return null;
|
||||
}
|
||||
},
|
||||
|
||||
searchSkills: (query: string) => {
|
||||
const discovery = getSkillDiscovery();
|
||||
const result = discovery.searchSkills(query);
|
||||
return {
|
||||
results: result.results.map(s => ({ id: s.id, name: s.name, description: s.description })),
|
||||
totalAvailable: result.totalAvailable,
|
||||
};
|
||||
},
|
||||
|
||||
initStreamListener: () => {
|
||||
const client = getGatewayClient();
|
||||
|
||||
|
||||
Reference in New Issue
Block a user