Azreen Jamal
985 lines
41 KiB
TypeScript
985 lines
41 KiB
TypeScript
/**
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* Nexus — The unified Pi intelligence layer
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*
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* Combines model routing + sub-agent orchestration into one seamless system.
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* The main agent stays fast and interactive. Complex work is automatically
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* offloaded to sub-agents. The model auto-adapts to task complexity.
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*
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* Model routing uses a REAL LLM call (Haiku, ~200ms) to classify task
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* complexity — no brittle regex patterns. The classifier returns a tier
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* (1-3) and whether to offload to a sub-agent.
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*
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* Features:
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* ✦ LLM-powered task classification (Haiku as router brain)
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* ✦ Auto model routing (Haiku → Sonnet → Opus based on classification)
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* ✦ Sub-agent spawning for heavy work (preserves main context)
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* ✦ Auto-delegation when classifier says to offload
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* ✦ Context pressure monitoring (warns & suggests offload at 70%+)
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* ✦ Mid-turn escalation on errors/heavy tool usage
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* ✦ Live dashboard widget showing all agents
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* ✦ Cost tracking across main + sub-agents
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* ✦ Persistent sub-agent sessions for multi-turn continuations
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*
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* Usage:
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* pi -e extensions/nexus.ts
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* alias pn='pi -e extensions/nexus.ts'
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*
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* Commands:
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* /nx — Full dashboard
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* /nx spawn <task> — Manual sub-agent spawn
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* /nx kill <id> — Kill sub-agent
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* /nx clear — Clear all sub-agents
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* /nx mode <m> — interactive | hybrid | delegator
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* /nx auto on|off — Toggle auto-delegation
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* /nx lock — Lock model (disable auto-routing)
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* /nx unlock — Unlock model
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* /nx tier 1|2|3 — Force model tier
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*/
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import type { AssistantMessage as AssistantMsg } from "@mariozechner/pi-ai";
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import { complete, getModel } from "@mariozechner/pi-ai";
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import type { ExtensionAPI, ExtensionContext } from "@mariozechner/pi-coding-agent";
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import { DynamicBorder } from "@mariozechner/pi-coding-agent";
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import { Container, Text, truncateToWidth, visibleWidth, type AutocompleteItem } from "@mariozechner/pi-tui";
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import { Type } from "@sinclair/typebox";
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import { spawn as cpSpawn, type ChildProcess } from "child_process";
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import { existsSync, mkdirSync, readdirSync, readFileSync } from "fs";
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import { basename, join } from "path";
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import { applyExtensionDefaults } from "./themeMap.ts";
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// ══════════════════════════════════════════════════════════════════════════
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// CONSTANTS
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// ══════════════════════════════════════════════════════════════════════════
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const AGENT_TIMEOUT_MS = 10 * 60 * 1000;
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const WIDGET_THROTTLE_MS = 400;
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const CONTEXT_WARN_PCT = 70;
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const MAX_RESULT_LEN = 12000;
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// ══════════════════════════════════════════════════════════════════════════
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// MODEL TIERS
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// ══════════════════════════════════════════════════════════════════════════
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interface Tier {
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name: string;
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icon: string;
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provider: string;
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modelId: string;
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thinking: "off" | "low" | "medium" | "high";
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inputCost: number;
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outputCost: number;
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}
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const TIERS: Tier[] = [
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{ name: "Haiku", icon: "⚡", provider: "anthropic", modelId: "claude-haiku-4-5", thinking: "off", inputCost: 0.80, outputCost: 4.00 },
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{ name: "Sonnet", icon: "⚖️", provider: "anthropic", modelId: "claude-sonnet-4-6", thinking: "low", inputCost: 3.00, outputCost: 15.00 },
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{ name: "Opus", icon: "🧠", provider: "anthropic", modelId: "claude-opus-4-6", thinking: "high", inputCost: 15.00, outputCost: 75.00 },
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];
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// ══════════════════════════════════════════════════════════════════════════
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// LLM-POWERED TASK CLASSIFIER
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// ══════════════════════════════════════════════════════════════════════════
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const CLASSIFIER_SYSTEM_PROMPT = `You are a task complexity classifier for a coding assistant. Given a user prompt, respond with ONLY a JSON object (no markdown, no explanation):
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{"tier": <1|2|3>, "thinking": "<off|low|medium|high>", "offload": <true|false>, "reason": "<brief reason>"}
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Classification rules:
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TIER 1 (simple — use cheapest model):
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- Quick questions, yes/no answers, explanations
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- Reading/viewing files, checking status, listing things
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- Small single-line edits, formatting, renaming
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- Conversational responses (thanks, ok, etc.)
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- Simple lookups or searches
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TIER 2 (medium — use balanced model):
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- Writing new functions, classes, or components
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- Debugging, fixing bugs, error resolution
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- Refactoring single files
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- Writing tests for specific code
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- Database queries, API endpoint creation
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- Docker/CI configuration changes
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TIER 3 (complex — use most powerful model):
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- Architecture design, system planning
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- Multi-file refactoring or migrations
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- Security audits, performance optimization
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- Complex algorithmic problems
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- Designing new systems from scratch
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- Tasks requiring deep reasoning or trade-off analysis
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THINKING LEVEL (extended reasoning budget — set independently of tier):
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- "off" → Simple/conversational. No benefit from reasoning.
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- "low" → Moderate task. Light reasoning helpful (most Tier 2).
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- "medium" → Tricky bug, subtle logic, multi-step plan (upper Tier 2 / lower Tier 3).
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- "high" → Architecture, security audit, complex algorithm, deep trade-offs (Tier 3).
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Rule of thumb: Tier 1 → "off". Tier 2 → "low" or "medium". Tier 3 → "medium" or "high".
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Only use "high" when extended chain-of-thought would meaningfully improve correctness.
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OFFLOAD (spawn sub-agent instead of inline):
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- Set true when the task would generate lots of context (multi-file changes, codebase-wide operations)
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- Set true when the task is independent and can run in background
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- Set true when "across all files", "entire codebase", parallel work is mentioned
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- Set false for conversational, quick, or interactive tasks
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- Set false when user needs immediate back-and-forth
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Be concise. The "reason" should be under 10 words.`;
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interface ClassificationResult {
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tier: number;
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thinking: "off" | "low" | "medium" | "high";
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offload: boolean;
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reason: string;
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}
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// Cache recent classifications to avoid duplicate calls
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const classificationCache = new Map<string, { result: ClassificationResult; timestamp: number }>();
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const CACHE_TTL_MS = 60_000; // 1 minute
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async function classifyWithLLM(
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prompt: string,
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ctx: ExtensionContext,
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contextPercent: number | null,
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): Promise<ClassificationResult> {
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// Check cache (normalize by trimming + lowercasing)
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const cacheKey = prompt.trim().toLowerCase().slice(0, 200);
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const cached = classificationCache.get(cacheKey);
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if (cached && Date.now() - cached.timestamp < CACHE_TTL_MS) {
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return cached.result;
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}
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// Use Haiku for classification — fast and cheap (~0.001 cents per classification)
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const classifier = ctx.modelRegistry.find("anthropic", "claude-haiku-4-5");
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if (!classifier) {
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// Fallback: simple heuristic if Haiku unavailable
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return { tier: 2, thinking: "low", offload: false, reason: "classifier unavailable" };
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}
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const apiKey = await ctx.modelRegistry.getApiKey(classifier);
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if (!apiKey) {
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return { tier: 2, thinking: "low", offload: false, reason: "no API key" };
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}
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// Build context message with additional signals
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let userMsg = prompt;
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if (contextPercent !== null && contextPercent > CONTEXT_WARN_PCT) {
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userMsg += `\n\n[SYSTEM NOTE: Main context is at ${Math.round(contextPercent)}% capacity. Prefer offload=true for heavy tasks.]`;
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}
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try {
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const response = await complete(classifier, {
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systemPrompt: CLASSIFIER_SYSTEM_PROMPT,
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messages: [{
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role: "user" as const,
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content: userMsg,
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timestamp: Date.now(),
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}],
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}, {
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reasoning: "off",
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});
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// Extract text from response
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const text = response.content
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.filter((c): c is { type: "text"; text: string } => c.type === "text")
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.map(c => c.text)
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.join("");
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// Parse JSON from response (handle potential markdown wrapping)
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const jsonStr = text.replace(/```json?\n?/g, "").replace(/```/g, "").trim();
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const parsed = JSON.parse(jsonStr);
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const validThinking = ["off", "low", "medium", "high"];
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const result: ClassificationResult = {
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tier: Math.max(1, Math.min(3, parsed.tier || 2)),
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thinking: validThinking.includes(parsed.thinking) ? parsed.thinking : "low",
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offload: Boolean(parsed.offload),
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reason: String(parsed.reason || "classified").slice(0, 50),
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};
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// Cache it
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classificationCache.set(cacheKey, { result, timestamp: Date.now() });
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return result;
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} catch (err: any) {
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// On any failure, default to Sonnet, no offload
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return { tier: 2, thinking: "low", offload: false, reason: `classify error: ${err?.message?.slice(0, 30)}` };
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}
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}
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// ══════════════════════════════════════════════════════════════════════════
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// SUB-AGENT TYPES
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// ══════════════════════════════════════════════════════════════════════════
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type AgentMode = "interactive" | "delegator" | "hybrid";
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type SubStatus = "queued" | "running" | "done" | "error" | "killed";
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interface SubAgent {
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id: number;
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status: SubStatus;
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task: string;
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role: string;
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tools: string;
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textChunks: string[];
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toolCount: number;
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elapsed: number;
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startTime: number;
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sessionFile: string;
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turnCount: number;
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proc?: ChildProcess;
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timer?: ReturnType<typeof setInterval>;
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inputTokens: number;
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outputTokens: number;
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cost: number;
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}
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interface RoleDef {
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name: string;
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description: string;
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tools: string;
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systemPrompt: string;
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}
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const ROLES: RoleDef[] = [
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{ name: "general", description: "General-purpose coding agent", tools: "read,bash,edit,write,grep,find,ls", systemPrompt: "You are a focused coding agent. Complete the given task efficiently. Be thorough but concise." },
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{ name: "scout", description: "Fast recon (read-only)", tools: "read,grep,find,ls", systemPrompt: "You are a scout. Investigate the codebase quickly and report findings. Do NOT modify files." },
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{ name: "builder", description: "Implementation & code generation", tools: "read,write,edit,bash,grep,find,ls", systemPrompt: "You are a builder. Implement changes thoroughly. Clean, minimal code. Follow existing patterns." },
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{ name: "reviewer", description: "Code review (read-only)", tools: "read,grep,find,ls", systemPrompt: "You are a reviewer. Analyze code for bugs, security, performance, style. Be specific about line numbers." },
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{ name: "tester", description: "Test writing & execution", tools: "read,write,edit,bash,grep,find,ls", systemPrompt: "You are a tester. Write and run tests. Cover edge cases. Use the project's existing test framework." },
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];
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// ══════════════════════════════════════════════════════════════════════════
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// EXTENSION
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// ══════════════════════════════════════════════════════════════════════════
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export default function nexus(pi: ExtensionAPI) {
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// ── Router State ───────────────────────────────────────────────────────
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let currentTier = 1;
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let lastThinking: "off" | "low" | "medium" | "high" = "low";
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let tierLocked = false;
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let totalSwitches = 0;
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let turnsSinceSwitch = 0;
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let consecutiveErrors = 0;
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let totalToolCalls = 0;
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let editWriteThisTurn = 0;
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let toolsThisTurn = 0;
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let turnCount = 0;
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let savedVsOpus = 0;
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let classifierCost = 0; // Track cost of Haiku classifier calls
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const tierHistory: Array<{ tier: number; reason: string; turn: number }> = [];
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// ── Agent State ────────────────────────────────────────────────────────
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const agents: Map<number, SubAgent> = new Map();
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const activeProcs: Set<ChildProcess> = new Set();
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let nextId = 1;
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let widgetCtx: ExtensionContext | null = null;
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let mode: AgentMode = "hybrid";
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let autoDelegate = true;
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let sessionDir = "";
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let customRoles: RoleDef[] = [];
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// ── Widget throttle ────────────────────────────────────────────────────
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let wDirty = false;
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let wTimer: ReturnType<typeof setTimeout> | null = null;
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function scheduleWidget() {
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wDirty = true;
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if (wTimer) return;
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wTimer = setTimeout(() => { wTimer = null; if (wDirty) { wDirty = false; renderWidget(); } }, WIDGET_THROTTLE_MS);
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}
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function flushWidget() {
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if (wTimer) { clearTimeout(wTimer); wTimer = null; }
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wDirty = false;
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renderWidget();
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}
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// ── Helpers ────────────────────────────────────────────────────────────
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function getAllRoles(): RoleDef[] { return [...ROLES, ...customRoles]; }
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function findRole(name: string): RoleDef {
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return getAllRoles().find(r => r.name.toLowerCase() === name.toLowerCase()) || ROLES[0];
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}
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function makeSessionFile(id: number): string {
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if (!existsSync(sessionDir)) mkdirSync(sessionDir, { recursive: true });
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return join(sessionDir, `nexus-${id}-${Date.now()}.jsonl`);
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}
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function loadCustomRoles(cwd: string) {
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customRoles = [];
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const seen = new Set(ROLES.map(r => r.name));
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for (const dir of [join(cwd, ".pi", "agents"), join(cwd, "agents")]) {
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if (!existsSync(dir)) continue;
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try {
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for (const file of readdirSync(dir)) {
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if (!file.endsWith(".md")) continue;
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const raw = readFileSync(join(dir, file), "utf-8");
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const m = raw.match(/^---\n([\s\S]*?)\n---\n([\s\S]*)$/);
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if (!m) continue;
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const fm: Record<string, string> = {};
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for (const line of m[1].split("\n")) {
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const i = line.indexOf(":");
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if (i > 0) fm[line.slice(0, i).trim()] = line.slice(i + 1).trim();
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}
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if (!fm.name || seen.has(fm.name)) continue;
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seen.add(fm.name);
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customRoles.push({ name: fm.name, description: fm.description || "", tools: fm.tools || "read,grep,find,ls", systemPrompt: m[2].trim() });
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}
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} catch {}
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}
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}
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// ── Model Switching ────────────────────────────────────────────────────
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async function switchTier(target: number, reason: string, ctx?: ExtensionContext, thinkingOverride?: "off" | "low" | "medium" | "high") {
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const t = Math.max(0, Math.min(2, target));
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const tier = TIERS[t];
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const model = ctx?.modelRegistry.find(tier.provider, tier.modelId);
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if (!model) return;
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const thinking = thinkingOverride ?? tier.thinking;
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const tierChanged = t !== currentTier;
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const thinkingChanged = thinking !== lastThinking;
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if (!tierChanged && !thinkingChanged) return;
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if (tierChanged) {
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const ok = await pi.setModel(model);
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if (!ok) return;
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}
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pi.setThinkingLevel(thinking);
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lastThinking = thinking;
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const prev = currentTier;
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currentTier = t;
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if (tierChanged) totalSwitches++;
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turnsSinceSwitch = 0;
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const thinkTag = thinkingOverride ? ` 🧠${thinking}` : "";
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tierHistory.push({ tier: t, reason: `${TIERS[prev].icon}→${tier.icon} ${reason}${thinkTag}`, turn: turnCount });
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}
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// ── Widget Rendering ───────────────────────────────────────────────────
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function renderWidget() {
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if (!widgetCtx) return;
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if (agents.size === 0) {
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widgetCtx.ui.setWidget("nexus-agents", undefined);
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return;
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}
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widgetCtx.ui.setWidget("nexus-agents", (_tui: any, theme: any) => {
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const container = new Container();
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const content = new Text("", 0, 0);
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container.addChild(content);
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return {
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render(width: number): string[] {
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const lines: string[] = [];
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const tier = TIERS[currentTier];
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const modeIcon = mode === "hybrid" ? "⚡" : mode === "delegator" ? "📡" : "💬";
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lines.push(theme.fg("dim", "─".repeat(width)));
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lines.push(
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theme.fg("accent", ` ✦ Nexus`) +
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theme.fg("dim", ` ${tier.icon} ${tier.name} · ${modeIcon} ${mode} · `) +
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theme.fg("accent", `${agents.size}`) +
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theme.fg("dim", " agents")
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);
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for (const [, a] of agents) {
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const icon = a.status === "running" ? "●" : a.status === "done" ? "✓" : a.status === "queued" ? "◌" : "✗";
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const color = a.status === "running" ? "accent" : a.status === "done" ? "success" : a.status === "queued" ? "dim" : "error";
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const elapsed = a.status === "running" ? Math.round((Date.now() - a.startTime) / 1000) : Math.round(a.elapsed / 1000);
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const task = a.task.length > 50 ? a.task.slice(0, 47) + "..." : a.task;
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const turn = a.turnCount > 1 ? ` t${a.turnCount}` : "";
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lines.push(
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theme.fg(color, ` ${icon} #${a.id}`) +
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theme.fg("dim", ` [${a.role}${turn}] ${elapsed}s · ${a.toolCount} tools`) +
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(a.cost > 0 ? theme.fg("warning", ` $${a.cost.toFixed(4)}`) : "")
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);
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lines.push(theme.fg("muted", ` ${task}`));
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if (a.status === "running" && a.textChunks.length > 0) {
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const last = a.textChunks.join("").split("\n").filter((l: string) => l.trim()).pop() || "";
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if (last) lines.push(theme.fg("dim", ` → ${last.slice(0, width - 8)}`));
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}
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}
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lines.push(theme.fg("dim", "─".repeat(width)));
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content.setText(lines.join("\n"));
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return container.render(width);
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},
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invalidate() { container.invalidate(); },
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};
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});
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}
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// ── Sub-Agent Process ──────────────────────────────────────────────────
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function processLine(a: SubAgent, line: string) {
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if (!line.trim()) return;
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try {
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const e = JSON.parse(line);
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if (e.type === "message_update" && e.assistantMessageEvent?.type === "text_delta") {
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a.textChunks.push(e.assistantMessageEvent.delta || "");
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scheduleWidget();
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} else if (e.type === "tool_execution_start") {
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a.toolCount++;
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scheduleWidget();
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} else if (e.type === "message_end" || e.type === "agent_end") {
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const msg = e.message || (e.messages || []).reverse().find((m: any) => m.role === "assistant");
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if (msg?.usage) {
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a.inputTokens = msg.usage.input || 0;
|
|
a.outputTokens = msg.usage.output || 0;
|
|
a.cost = msg.usage.cost?.total || 0;
|
|
scheduleWidget();
|
|
}
|
|
}
|
|
} catch {}
|
|
}
|
|
|
|
function spawnProcess(a: SubAgent, prompt: string, ctx: ExtensionContext, isCont: boolean): Promise<{ output: string; exitCode: number }> {
|
|
a.status = "running";
|
|
a.startTime = Date.now();
|
|
scheduleWidget();
|
|
|
|
const role = findRole(a.role);
|
|
// Sub-agents use Sonnet for balanced cost/performance
|
|
const model = "anthropic/claude-sonnet-4-6";
|
|
|
|
const args = [
|
|
"--mode", "json", "-p", "--no-extensions", "--no-skills",
|
|
"--model", model, "--tools", role.tools, "--thinking", "low",
|
|
"--append-system-prompt", role.systemPrompt,
|
|
"--session", a.sessionFile,
|
|
];
|
|
if (isCont) args.push("-c");
|
|
args.push(prompt);
|
|
|
|
return new Promise(resolve => {
|
|
let done = false;
|
|
const fin = (val: { output: string; exitCode: number }) => { if (!done) { done = true; resolve(val); } };
|
|
|
|
const proc = cpSpawn("pi", args, { stdio: ["ignore", "pipe", "pipe"], env: { ...process.env } });
|
|
a.proc = proc;
|
|
activeProcs.add(proc);
|
|
|
|
a.timer = setInterval(() => { a.elapsed = Date.now() - a.startTime; scheduleWidget(); }, 1000);
|
|
|
|
const timeout = setTimeout(() => {
|
|
try { proc.kill("SIGTERM"); } catch {}
|
|
setTimeout(() => { try { proc.kill("SIGKILL"); } catch {} }, 3000);
|
|
}, AGENT_TIMEOUT_MS);
|
|
|
|
let buf = "";
|
|
proc.stdout!.setEncoding("utf-8");
|
|
proc.stdout!.on("data", (chunk: string) => {
|
|
buf += chunk;
|
|
const lines = buf.split("\n");
|
|
buf = lines.pop() || "";
|
|
for (const l of lines) processLine(a, l);
|
|
});
|
|
proc.stderr!.setEncoding("utf-8");
|
|
proc.stderr!.on("data", () => {});
|
|
|
|
proc.on("close", code => {
|
|
clearTimeout(timeout);
|
|
activeProcs.delete(proc);
|
|
a.proc = undefined;
|
|
if (a.timer) clearInterval(a.timer);
|
|
a.elapsed = Date.now() - a.startTime;
|
|
if (buf.trim()) processLine(a, buf);
|
|
a.status = a.elapsed >= AGENT_TIMEOUT_MS ? "error" : (code === 0 ? "done" : "error");
|
|
flushWidget();
|
|
fin({ output: a.textChunks.join(""), exitCode: code ?? 1 });
|
|
});
|
|
|
|
proc.on("error", err => {
|
|
clearTimeout(timeout);
|
|
activeProcs.delete(proc);
|
|
a.proc = undefined;
|
|
if (a.timer) clearInterval(a.timer);
|
|
a.status = "error";
|
|
flushWidget();
|
|
fin({ output: `Error: ${err.message}`, exitCode: 1 });
|
|
});
|
|
});
|
|
}
|
|
|
|
function spawnAndDeliver(a: SubAgent, prompt: string, ctx: ExtensionContext, isCont: boolean) {
|
|
spawnProcess(a, prompt, ctx, isCont).then(({ output, exitCode }) => {
|
|
const status = exitCode === 0 ? "✓" : "✗";
|
|
const elapsed = Math.round(a.elapsed / 1000);
|
|
const turn = a.turnCount > 1 ? ` (Turn ${a.turnCount})` : "";
|
|
const truncated = output.length > MAX_RESULT_LEN ? output.slice(0, MAX_RESULT_LEN) + "\n\n... [truncated]" : output;
|
|
|
|
ctx.ui.notify(`#${a.id} [${a.role}] ${status} ${elapsed}s`, exitCode === 0 ? "info" : "error");
|
|
|
|
pi.sendMessage({
|
|
customType: "nexus-result",
|
|
content: `**Sub-agent #${a.id}** [${a.role}]${turn} — ${status} ${elapsed}s | ${a.toolCount} tools | $${a.cost.toFixed(4)}\n\n${truncated}`,
|
|
display: "assistant",
|
|
}, { deliverAs: "followUp", triggerTurn: true });
|
|
});
|
|
}
|
|
|
|
// ── LLM Tools ──────────────────────────────────────────────────────────
|
|
|
|
const roleList = ROLES.map(r => `${r.name} (${r.description})`).join(", ");
|
|
|
|
pi.registerTool({
|
|
name: "nexus_spawn",
|
|
label: "Spawn Sub-Agent",
|
|
description: `Spawn a background sub-agent for heavy tasks. Preserves main chat context. Results auto-deliver when done.\n\nRoles: ${roleList}. Custom roles from .pi/agents/*.md also available.`,
|
|
promptGuidelines: [
|
|
"Spawn sub-agents for multi-file, long-running, or context-heavy work",
|
|
"Use role='scout' for exploration, 'builder' for code, 'reviewer' for review, 'tester' for tests",
|
|
"Spawn multiple agents in parallel for independent tasks",
|
|
"Continue chatting while sub-agents work — results arrive automatically",
|
|
],
|
|
parameters: Type.Object({
|
|
task: Type.String({ description: "Complete task description — sub-agent has no context from this conversation" }),
|
|
role: Type.Optional(Type.String({ description: "Agent role. Default: general" })),
|
|
}),
|
|
async execute(_id, params, _sig, onUpdate, ctx) {
|
|
widgetCtx = ctx;
|
|
const id = nextId++;
|
|
const a: SubAgent = {
|
|
id, status: "queued", task: params.task, role: params.role || "general",
|
|
tools: findRole(params.role || "general").tools, textChunks: [], toolCount: 0,
|
|
elapsed: 0, startTime: Date.now(), sessionFile: makeSessionFile(id),
|
|
turnCount: 1, inputTokens: 0, outputTokens: 0, cost: 0,
|
|
};
|
|
agents.set(id, a);
|
|
if (onUpdate) onUpdate({ content: [{ type: "text", text: `Spawning #${id} [${a.role}]...` }], details: { id, role: a.role } });
|
|
spawnAndDeliver(a, params.task, ctx, false);
|
|
return { content: [{ type: "text", text: `Sub-agent #${id} [${a.role}] running in background. Continue chatting.` }], details: { id, role: a.role } };
|
|
},
|
|
renderCall(args, theme) {
|
|
const r = (args as any).role || "general";
|
|
const t = ((args as any).task || "").slice(0, 55);
|
|
return new Text(theme.fg("toolTitle", theme.bold("nexus_spawn ")) + theme.fg("accent", `[${r}] `) + theme.fg("muted", t), 0, 0);
|
|
},
|
|
renderResult(result, opts, theme) {
|
|
const d = result.details as any;
|
|
if (!d) return undefined;
|
|
return new Text(theme.fg("success", `◉ #${d.id}`) + theme.fg("dim", ` [${d.role}] background`), 0, 0);
|
|
},
|
|
});
|
|
|
|
pi.registerTool({
|
|
name: "nexus_continue",
|
|
label: "Continue Sub-Agent",
|
|
description: "Continue a finished sub-agent's conversation with follow-up instructions.",
|
|
parameters: Type.Object({
|
|
id: Type.Number({ description: "Sub-agent ID" }),
|
|
prompt: Type.String({ description: "Follow-up instructions" }),
|
|
}),
|
|
async execute(_cid, params, _sig, _upd, ctx) {
|
|
widgetCtx = ctx;
|
|
const a = agents.get(params.id);
|
|
if (!a) return { content: [{ type: "text", text: `No #${params.id} found.` }] };
|
|
if (a.status === "running") return { content: [{ type: "text", text: `#${params.id} still running.` }] };
|
|
a.textChunks = []; a.toolCount = 0; a.elapsed = 0; a.turnCount++;
|
|
spawnAndDeliver(a, params.prompt, ctx, true);
|
|
return { content: [{ type: "text", text: `#${params.id} continuing (Turn ${a.turnCount}).` }] };
|
|
},
|
|
});
|
|
|
|
pi.registerTool({
|
|
name: "nexus_status",
|
|
label: "Agent Status",
|
|
description: "Check all sub-agents.",
|
|
parameters: Type.Object({}),
|
|
async execute() {
|
|
if (agents.size === 0) return { content: [{ type: "text", text: "No sub-agents." }] };
|
|
const lines = Array.from(agents.values()).map(a => {
|
|
const e = a.status === "running" ? Math.round((Date.now() - a.startTime) / 1000) : Math.round(a.elapsed / 1000);
|
|
return `#${a.id} [${a.role}] ${a.status} — ${e}s, ${a.toolCount} tools, $${a.cost.toFixed(4)}\n ${a.task}`;
|
|
});
|
|
return { content: [{ type: "text", text: lines.join("\n") }] };
|
|
},
|
|
});
|
|
|
|
pi.registerTool({
|
|
name: "nexus_kill",
|
|
label: "Kill Sub-Agent",
|
|
description: "Kill/remove a sub-agent.",
|
|
parameters: Type.Object({ id: Type.Number() }),
|
|
async execute(_cid, params) {
|
|
const a = agents.get(params.id);
|
|
if (!a) return { content: [{ type: "text", text: `No #${params.id}.` }] };
|
|
if (a.proc) try { a.proc.kill("SIGTERM"); } catch {}
|
|
if (a.timer) clearInterval(a.timer);
|
|
agents.delete(params.id);
|
|
flushWidget();
|
|
return { content: [{ type: "text", text: `#${params.id} removed.` }] };
|
|
},
|
|
});
|
|
|
|
pi.registerTool({
|
|
name: "nexus_collect",
|
|
label: "Collect Results",
|
|
description: "Collect results from all finished sub-agents.",
|
|
parameters: Type.Object({}),
|
|
async execute() {
|
|
const done = Array.from(agents.values()).filter(a => a.status === "done" || a.status === "error");
|
|
if (done.length === 0) return { content: [{ type: "text", text: "No results to collect." }] };
|
|
let totalCost = 0;
|
|
const parts = done.map(a => {
|
|
const out = a.textChunks.join("");
|
|
const trunc = out.length > 6000 ? out.slice(0, 6000) + "\n... [truncated]" : out;
|
|
totalCost += a.cost;
|
|
return `## ${a.status === "done" ? "✓" : "✗"} #${a.id} [${a.role}] ${Math.round(a.elapsed / 1000)}s\n${a.task}\n\n${trunc}`;
|
|
});
|
|
return { content: [{ type: "text", text: `${done.length} results ($${totalCost.toFixed(4)})\n\n${parts.join("\n\n---\n\n")}` }] };
|
|
},
|
|
});
|
|
|
|
// ══════════════════════════════════════════════════════════════════════
|
|
// CORE ROUTING LOGIC — LLM-POWERED
|
|
// ══════════════════════════════════════════════════════════════════════
|
|
|
|
pi.on("before_agent_start", async (event, ctx) => {
|
|
widgetCtx = ctx;
|
|
const usage = ctx.getContextUsage();
|
|
const contextPct = usage?.percent ?? null;
|
|
|
|
// ── Step 1: LLM Classification ─────────────────────────────────────
|
|
let classification: ClassificationResult | null = null;
|
|
|
|
if (!tierLocked || (autoDelegate && mode !== "interactive")) {
|
|
ctx.ui.setWorkingMessage("classifying task...");
|
|
classification = await classifyWithLLM(event.prompt, ctx, contextPct);
|
|
ctx.ui.setWorkingMessage(); // restore default
|
|
|
|
// Track classifier cost (Haiku: ~150 input + ~30 output tokens per call)
|
|
classifierCost += (150 * 0.80 + 30 * 4.00) / 1_000_000;
|
|
}
|
|
|
|
// ── Step 2: Model Routing ──────────────────────────────────────────
|
|
if (!tierLocked && classification) {
|
|
let target = classification.tier - 1; // Convert 1-3 to 0-2
|
|
let thinking = classification.thinking;
|
|
|
|
// Context-aware adjustments
|
|
// If we've been doing heavy tool work, don't drop to Haiku
|
|
if (target === 0 && totalToolCalls > 10) target = 1;
|
|
|
|
// Error escalation override
|
|
if (consecutiveErrors >= 2 && target < 2) {
|
|
target = Math.min(target + 1, 2);
|
|
if (thinking === "off" || thinking === "low") thinking = "medium";
|
|
}
|
|
|
|
// Context pressure: bump tier if context is getting full
|
|
if (contextPct !== null && contextPct > 80 && target < 1) {
|
|
target = 1; // At least Sonnet when context is pressured
|
|
}
|
|
|
|
await switchTier(target, classification.reason, ctx, thinking);
|
|
}
|
|
|
|
// ── Step 3: Auto-Delegation ────────────────────────────────────────
|
|
if (classification?.offload && autoDelegate && (mode === "hybrid" || mode === "delegator")) {
|
|
// Context pressure warning
|
|
if (contextPct !== null && contextPct > CONTEXT_WARN_PCT) {
|
|
ctx.ui.setStatus("nexus-ctx", `⚠️ Context ${Math.round(contextPct)}%`);
|
|
} else {
|
|
ctx.ui.setStatus("nexus-ctx", undefined);
|
|
}
|
|
|
|
const roles = getAllRoles().map(r => `${r.name}: ${r.description}`).join("\n");
|
|
const contextWarn = (contextPct !== null && contextPct > CONTEXT_WARN_PCT)
|
|
? `\n⚠️ CONTEXT AT ${Math.round(contextPct)}% — strongly prefer sub-agents for this work.\n`
|
|
: "";
|
|
|
|
return {
|
|
systemPrompt: event.systemPrompt + `\n\n## Nexus: Sub-Agent Delegation Recommended
|
|
The task classifier determined this task should be **offloaded to a sub-agent** (reason: "${classification.reason}").
|
|
|
|
You have these tools: nexus_spawn, nexus_continue, nexus_status, nexus_kill, nexus_collect.
|
|
${contextWarn}
|
|
**Strongly prefer spawning a sub-agent** for this task rather than doing it inline. This preserves the main chat context for continued interaction.
|
|
|
|
Available roles:\n${roles}
|
|
|
|
Sub-agents run in background with their own context. You can spawn multiple for parallel work. Results auto-deliver. Keep your main response brief — explain what you're delegating and why.`,
|
|
};
|
|
} else {
|
|
ctx.ui.setStatus("nexus-ctx", undefined);
|
|
}
|
|
});
|
|
|
|
// ── Turn & Tool Tracking (mid-conversation escalation) ─────────────────
|
|
|
|
pi.on("turn_start", async () => {
|
|
toolsThisTurn = 0;
|
|
editWriteThisTurn = 0;
|
|
turnCount++;
|
|
turnsSinceSwitch++;
|
|
});
|
|
|
|
pi.on("tool_execution_start", async (event) => {
|
|
toolsThisTurn++;
|
|
totalToolCalls++;
|
|
if (event.toolName === "edit" || event.toolName === "write") editWriteThisTurn++;
|
|
});
|
|
|
|
pi.on("tool_execution_end", async (event, ctx) => {
|
|
if (event.isError) {
|
|
consecutiveErrors++;
|
|
// Mid-turn escalation on repeated errors
|
|
if (consecutiveErrors >= 2 && !tierLocked && currentTier < 2) {
|
|
await switchTier(currentTier + 1, `${consecutiveErrors} consecutive errors`, ctx);
|
|
}
|
|
} else {
|
|
consecutiveErrors = 0;
|
|
}
|
|
});
|
|
|
|
pi.on("turn_end", async (_event, ctx) => {
|
|
if (!tierLocked) {
|
|
// Escalate on heavy tool usage
|
|
if (editWriteThisTurn >= 4 && currentTier < 2) {
|
|
await switchTier(2, `heavy: ${editWriteThisTurn} edits/writes`, ctx);
|
|
} else if (toolsThisTurn >= 6 && currentTier < 1) {
|
|
await switchTier(1, `busy: ${toolsThisTurn} tool calls`, ctx);
|
|
}
|
|
|
|
// De-escalate after quiet period (but only if classifier agrees next time)
|
|
// We just track turns since switch — the classifier handles de-escalation naturally
|
|
}
|
|
|
|
// Cost savings estimate
|
|
const opusCost = (2000 * TIERS[2].inputCost + 1000 * TIERS[2].outputCost) / 1e6;
|
|
const actualCost = (2000 * TIERS[currentTier].inputCost + 1000 * TIERS[currentTier].outputCost) / 1e6;
|
|
savedVsOpus += opusCost - actualCost;
|
|
});
|
|
|
|
// ── /nx Command ────────────────────────────────────────────────────────
|
|
|
|
pi.registerCommand("nx", {
|
|
description: "Nexus controls: /nx [spawn|kill|clear|mode|auto|lock|unlock|tier]",
|
|
getArgumentCompletions: (prefix: string): AutocompleteItem[] | null => {
|
|
const items = [
|
|
{ value: "spawn ", label: "spawn <task>" },
|
|
{ value: "kill ", label: "kill <id>" },
|
|
{ value: "clear", label: "clear all agents" },
|
|
{ value: "mode hybrid", label: "mode hybrid" },
|
|
{ value: "mode interactive", label: "mode interactive" },
|
|
{ value: "mode delegator", label: "mode delegator" },
|
|
{ value: "auto on", label: "auto on" },
|
|
{ value: "auto off", label: "auto off" },
|
|
{ value: "lock", label: "lock model" },
|
|
{ value: "unlock", label: "unlock model" },
|
|
{ value: "tier ", label: "tier 1|2|3" },
|
|
];
|
|
return items.filter(i => i.value.startsWith(prefix));
|
|
},
|
|
|
|
async handler(args, ctx) {
|
|
widgetCtx = ctx;
|
|
const parts = (args || "").trim().split(/\s+/);
|
|
const sub = parts[0]?.toLowerCase();
|
|
|
|
if (!sub) {
|
|
const tier = TIERS[currentTier];
|
|
const modeIcon = mode === "hybrid" ? "⚡" : mode === "delegator" ? "📡" : "💬";
|
|
const usage = ctx.getContextUsage();
|
|
const pct = usage?.percent ? Math.round(usage.percent) : "?";
|
|
const agentLines = agents.size === 0 ? " (none)" : Array.from(agents.values()).map(a => {
|
|
const e = a.status === "running" ? Math.round((Date.now() - a.startTime) / 1000) : Math.round(a.elapsed / 1000);
|
|
return ` #${a.id} [${a.role}] ${a.status} ${e}s $${a.cost.toFixed(4)} — ${a.task.slice(0, 50)}`;
|
|
}).join("\n");
|
|
|
|
const lastRoute = tierHistory.length > 0
|
|
? tierHistory.slice(-3).map(h => ` Turn ${h.turn}: ${h.reason}`).join("\n")
|
|
: " (none yet)";
|
|
|
|
pi.sendMessage({
|
|
customType: "nexus-dashboard",
|
|
content: [
|
|
``,
|
|
`✦ Nexus Dashboard`,
|
|
` Model: ${tier.icon} ${tier.name} [${lastThinking}]${tierLocked ? " 🔒" : ""}`,
|
|
` Mode: ${modeIcon} ${mode} | Auto: ${autoDelegate ? "on" : "off"} | Context: ${pct}%`,
|
|
` Switches: ${totalSwitches} | Saved: $${savedVsOpus.toFixed(4)} | Classifier: $${classifierCost.toFixed(4)}`,
|
|
``,
|
|
` Sub-Agents (${agents.size}):`,
|
|
agentLines,
|
|
``,
|
|
` Recent Routing:`,
|
|
lastRoute,
|
|
``,
|
|
` /nx spawn|kill|clear|mode|auto|lock|unlock|tier`,
|
|
``,
|
|
].join("\n"),
|
|
display: "assistant",
|
|
});
|
|
return;
|
|
}
|
|
|
|
if (sub === "spawn") {
|
|
const task = parts.slice(1).join(" ").trim();
|
|
if (!task) { ctx.ui.notify("Usage: /nx spawn <task>", "error"); return; }
|
|
const id = nextId++;
|
|
const a: SubAgent = { id, status: "queued", task, role: "general", tools: ROLES[0].tools, textChunks: [], toolCount: 0, elapsed: 0, startTime: Date.now(), sessionFile: makeSessionFile(id), turnCount: 1, inputTokens: 0, outputTokens: 0, cost: 0 };
|
|
agents.set(id, a);
|
|
spawnAndDeliver(a, task, ctx, false);
|
|
ctx.ui.notify(`#${id} spawned`, "info");
|
|
} else if (sub === "kill") {
|
|
const id = parseInt(parts[1], 10);
|
|
const a = agents.get(id);
|
|
if (!a) { ctx.ui.notify(`No #${id}`, "error"); return; }
|
|
if (a.proc) try { a.proc.kill("SIGTERM"); } catch {}
|
|
if (a.timer) clearInterval(a.timer);
|
|
agents.delete(id);
|
|
flushWidget();
|
|
ctx.ui.notify(`#${id} killed`, "info");
|
|
} else if (sub === "clear") {
|
|
for (const [, a] of agents) {
|
|
if (a.proc) try { a.proc.kill("SIGTERM"); } catch {}
|
|
if (a.timer) clearInterval(a.timer);
|
|
}
|
|
agents.clear();
|
|
nextId = 1;
|
|
flushWidget();
|
|
ctx.ui.notify("Cleared", "info");
|
|
} else if (sub === "mode") {
|
|
const v = parts[1]?.toLowerCase() as AgentMode;
|
|
if (["interactive", "hybrid", "delegator"].includes(v)) { mode = v; ctx.ui.notify(`Mode: ${v}`, "info"); }
|
|
else ctx.ui.notify("Usage: /nx mode interactive|hybrid|delegator", "error");
|
|
} else if (sub === "auto") {
|
|
if (parts[1] === "on") { autoDelegate = true; ctx.ui.notify("Auto ON", "info"); }
|
|
else if (parts[1] === "off") { autoDelegate = false; ctx.ui.notify("Auto OFF", "info"); }
|
|
else ctx.ui.notify("Usage: /nx auto on|off", "error");
|
|
} else if (sub === "lock") {
|
|
tierLocked = true; ctx.ui.notify("🔒 Model locked", "info");
|
|
} else if (sub === "unlock") {
|
|
tierLocked = false; ctx.ui.notify("🔓 Model unlocked", "info");
|
|
} else if (sub === "tier") {
|
|
const n = parseInt(parts[1], 10);
|
|
if (n >= 1 && n <= 3) {
|
|
await switchTier(n - 1, `manual /nx tier ${n}`, ctx);
|
|
ctx.ui.notify(`${TIERS[n - 1].icon} ${TIERS[n - 1].name}`, "info");
|
|
} else ctx.ui.notify("Usage: /nx tier 1|2|3", "error");
|
|
} else {
|
|
ctx.ui.notify("Unknown. Try: /nx spawn|kill|clear|mode|auto|lock|unlock|tier", "error");
|
|
}
|
|
},
|
|
});
|
|
|
|
// ── Session Start ──────────────────────────────────────────────────────
|
|
|
|
pi.on("session_start", async (_event, ctx) => {
|
|
applyExtensionDefaults(import.meta.url, ctx);
|
|
widgetCtx = ctx;
|
|
sessionDir = join(ctx.cwd, ".pi", "agent-sessions", "nexus");
|
|
loadCustomRoles(ctx.cwd);
|
|
|
|
// Cleanup previous
|
|
for (const [, a] of agents) {
|
|
if (a.proc) try { a.proc.kill("SIGTERM"); } catch {}
|
|
if (a.timer) clearInterval(a.timer);
|
|
}
|
|
agents.clear();
|
|
nextId = 1;
|
|
|
|
// Set initial model (Sonnet = balanced start)
|
|
const init = TIERS[1];
|
|
const model = ctx.modelRegistry.find(init.provider, init.modelId);
|
|
if (model) {
|
|
await pi.setModel(model);
|
|
pi.setThinkingLevel(init.thinking);
|
|
}
|
|
currentTier = 1;
|
|
|
|
// Footer
|
|
ctx.ui.setFooter((_tui, theme, footerData) => {
|
|
const unsub = footerData.onBranchChange(() => _tui.requestRender());
|
|
return {
|
|
dispose: unsub,
|
|
invalidate() {},
|
|
render(width: number): string[] {
|
|
const tier = TIERS[currentTier];
|
|
const lockStr = tierLocked ? " 🔒" : "";
|
|
const usage = ctx.getContextUsage();
|
|
const pct = usage?.percent ?? 0;
|
|
const filled = Math.round(pct / 10) || 1;
|
|
|
|
let tokIn = 0, tokOut = 0, cost = 0;
|
|
for (const entry of ctx.sessionManager.getBranch()) {
|
|
if (entry.type === "message" && entry.message.role === "assistant") {
|
|
const m = entry.message as AssistantMsg;
|
|
tokIn += m.usage.input;
|
|
tokOut += m.usage.output;
|
|
cost += m.usage.cost.total;
|
|
}
|
|
}
|
|
// Add sub-agent costs + classifier cost
|
|
for (const [, a] of agents) cost += a.cost;
|
|
cost += classifierCost;
|
|
const fmt = (n: number) => n < 1000 ? `${n}` : `${(n / 1000).toFixed(1)}k`;
|
|
|
|
const l1L = theme.fg("dim", " ") + theme.fg("accent", `${tier.icon} ${tier.name}`) +
|
|
theme.fg("dim", ` [${lastThinking}]${lockStr} `) +
|
|
theme.fg("warning", "[") + theme.fg("success", "#".repeat(filled)) +
|
|
theme.fg("dim", "-".repeat(10 - filled)) + theme.fg("warning", "]") +
|
|
theme.fg("dim", " ") + theme.fg("accent", `${Math.round(pct)}%`);
|
|
const l1R = theme.fg("success", fmt(tokIn)) + theme.fg("dim", " in ") +
|
|
theme.fg("accent", fmt(tokOut)) + theme.fg("dim", " out ") +
|
|
theme.fg("warning", `$${cost.toFixed(4)} `);
|
|
const p1 = " ".repeat(Math.max(1, width - visibleWidth(l1L) - visibleWidth(l1R)));
|
|
|
|
const dir = basename(ctx.cwd);
|
|
const branch = footerData.getGitBranch();
|
|
const modeIcon = mode === "hybrid" ? "⚡" : mode === "delegator" ? "📡" : "💬";
|
|
const running = Array.from(agents.values()).filter(a => a.status === "running").length;
|
|
|
|
const l2L = theme.fg("dim", ` ${dir}`) +
|
|
(branch ? theme.fg("dim", " ") + theme.fg("warning", "(") + theme.fg("success", branch) + theme.fg("warning", ")") : "") +
|
|
theme.fg("dim", ` · ${modeIcon} ${mode}`);
|
|
const l2R = (running > 0 ? theme.fg("accent", `● ${running} running `) : "") +
|
|
(agents.size > 0 ? theme.fg("dim", `${agents.size} agents `) : "") +
|
|
(savedVsOpus > 0 ? theme.fg("success", `saved $${savedVsOpus.toFixed(3)} `) : "");
|
|
const p2 = " ".repeat(Math.max(1, width - visibleWidth(l2L) - visibleWidth(l2R)));
|
|
|
|
return [
|
|
truncateToWidth(l1L + p1 + l1R, width, ""),
|
|
truncateToWidth(l2L + p2 + l2R, width, ""),
|
|
];
|
|
},
|
|
};
|
|
});
|
|
|
|
const roles = getAllRoles().map(r => r.name).join(", ");
|
|
ctx.ui.notify(
|
|
`✦ Nexus active [${mode}] — LLM-powered routing\n` +
|
|
`Model: ${TIERS[1].icon} ${TIERS[1].name} (Haiku classifies → auto-routes)\n` +
|
|
`Roles: ${roles}\n` +
|
|
`/nx — Dashboard & controls`,
|
|
"info",
|
|
);
|
|
});
|
|
|
|
// ── Cleanup ────────────────────────────────────────────────────────────
|
|
|
|
function killAll() {
|
|
for (const p of activeProcs) try { p.kill("SIGTERM"); } catch {}
|
|
setTimeout(() => { for (const p of activeProcs) try { p.kill("SIGKILL"); } catch {} }, 3000);
|
|
}
|
|
pi.on("session_shutdown", async () => killAll());
|
|
process.on("exit", killAll);
|
|
process.on("SIGINT", () => { killAll(); process.exit(0); });
|
|
process.on("SIGTERM", () => { killAll(); process.exit(0); });
|
|
}
|