HomerandClaude Opus 5.5
f9bad01ed7
ci / check (push) Canceled after 0s
The first public release of LLeMbas CLI: a terminal coding agent and project manager for any LLM API, with permission modes, git snapshots, memory and skills, knowledge bases, MCP, voice, and a link to a LLeMbas instance whose web UI can work its sessions too. Signed Linux binaries for x64 and arm64. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
78 lines
3.4 KiB
TypeScript
78 lines
3.4 KiB
TypeScript
import { createSignal, For, onCleanup } from "solid-js"
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import { duration } from "../../duration.ts"
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import { useTui } from "../context.ts"
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import { fmtTokens } from "./status.tsx"
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/** "reading the prompt 64% · 90k of 140k · ~2m left": the server's own count (llama.cpp's
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* return_progress). The time left is guessed from the reading so far, once there is enough of it;
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* a long prompt reads slower towards its end, so it is a floor more than a promise. */
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export function reading(p: { total: number; done: number; processed: number; ms: number }): string {
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const pct = Math.floor((p.done / p.total) * 100)
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const parts = [`reading the prompt ${pct}%`, `${fmtTokens(p.done)} of ${fmtTokens(p.total)}`]
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if (p.processed >= 2048 && p.ms >= 2000 && p.done < p.total) {
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const left = ((p.total - p.done) / p.processed) * p.ms
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parts.push(`~${duration(left, true)} left`)
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}
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return parts.join(" · ")
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}
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// Hermes' kawaii spinner: a braille frame, a face that changes every few seconds, what is going on
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// (a verb while it thinks), and the whole task's time and output tokens — from the prompt until
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// the last reply of the task, subagents included.
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export function Spinner() {
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const { theme, view } = useTui()
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const [tick, setTick] = createSignal(0)
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const t = setInterval(() => setTick((n) => n + 1), 100)
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onCleanup(() => clearInterval(t))
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const sp = () => theme().spinner
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const pick = (list: string[], every: number) => list[Math.floor(tick() / every) % list.length] ?? ""
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const elapsed = () => (tick(), view.state.busySince ? duration(Date.now() - view.state.busySince, true) : "0s")
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const tokens = () => {
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tick()
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const { n, estimated } = view.taskTokens()
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return `${estimated ? "~" : ""}${fmtTokens(n)} token${n === 1 ? "" : "s"}`
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}
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const what = () => {
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const s = view.state
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if (s.preparing) return `preparing ${s.preparing}`
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if (s.phase === "waiting" && s.progress) return reading(s.progress)
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if (s.phase === "thinking") return pick(sp().verbs, 30)
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if (s.phase === "tools") return "running tools"
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if (s.phase === "writing") return "writing"
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return "waiting for the model"
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}
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const face = () => (view.state.phase === "thinking" ? pick(sp().thinking, 30) : pick(sp().waiting, 30))
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return (
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<box paddingLeft={1} height={1}>
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<text wrapMode="none" truncate>
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<span style={{ fg: theme().colors.accent }}>{pick(sp().frames, 1)} </span>
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<span style={{ fg: theme().colors.label }}>{face()} </span>
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<span style={{ fg: theme().colors.muted }}>{what()}… </span>
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<span style={{ fg: theme().colors.dim }}>
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{elapsed()} · {tokens()} · esc to stop
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</span>
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</text>
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</box>
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)
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}
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/** Messages sent while the agent works and not given to it yet — one line each, above the input,
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* until the next step takes them (or the task ends, in queue mode). */
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export function Queued() {
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const { theme, view } = useTui()
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const when = () => (view.state.queued.mode === "queue" ? "after this task" : "at the next step")
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return (
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<For each={view.state.queued.texts}>
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{(text) => (
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<box paddingLeft={1} height={1}>
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<text wrapMode="none" truncate>
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<span style={{ fg: theme().colors.accent }}>↳ queued </span>
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<span style={{ fg: theme().colors.text }}>{text.split("\n")[0]}</span>
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<span style={{ fg: theme().colors.dim }}> · {when()}</span>
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</text>
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</box>
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)}
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</For>
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)
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}
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