Files
LLeMbas-CLI/tests/fake-provider.ts
T
HomerandClaude Opus 5.5 6ec95fbd66
ci / check (push) Waiting to run
Teams in the CLI (harness spec 3.2.0, team.md)
The four team tools (tool/team_tools.ts) on the rules of team/team.ts,
driven from real turns by team/runtime.ts:

- Members run on the subagent job machinery (app.ts spawn with `member`):
  background, unattended, their own prompt from blocks/team_member.md
  (the whole of team_lead.md for one with lead: true), team_send and
  team_read (team_add and team_stop for one that leads). Not jobs to the
  model: job_list and the job_* tools skip them; a client over the link
  still sees them as subagent jobs named "<name>: <role>".
- The room: messages and reports with their marks, delivered at the next
  step boundary or waking a finished member or the idle lead; report
  posts to the manager.
- A manager's work calls answer the refusal before the permission check,
  by risk class (an MCP tool by its readOnlyHint); the tool list is
  unchanged. job_stop and reading bash stay.
- Slots: the lead waits for one before its turn (Esc stops the wait);
  members wait in order; task helpers in a team count toward the size
  and hold a slot; job_send restarting a helper is refused when full.
- The offer is decided with the prompt and kept with it: a resumed
  session takes it from its kept tool list.
- The size: agents.min/max settings, refused outside 1 <= min <= max <=
  cap, kept across /new and resume; said in a note on the first message,
  after a change, after a compaction and a rewind.
- TUI: /team (tree and room, size, stop a member, dialogs for both), an
  "agents" row beside the effort in /effort, "team n/max" in the status
  bar. /team works over ACP too.

tests/team.test.ts runs a lead, a member and its report through the app.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
2026-11-09 09:08:52 +00:00

69 lines
4.3 KiB
TypeScript

// A scripted OpenAI-compatible server. Each request takes the next scripted response.
export type Scripted =
| { status: number; body: string }
| { chunks: unknown[]; done?: boolean; raw?: string; gapMs?: number }
export interface Fake {
url: string
requests: any[]
/** Path (with query) and headers of each request, in order. */
calls: { path: string; headers: Record<string, string> }[]
stop(): void
}
/** `route`: another fake that answers for a model (by the id in the request), as one LLeMbas server
* serves models from several backends — the request is passed to it whole, and recorded there. */
/** `served`: what GET /v1/models lists, as a LLeMbas server lists its models (default two
* placeholders). Any other GET — the instance's own description, its personalization — is a 404,
* which a client reads as "this server does not have it". */
/** `script` may be a function of the request (and its number), for requests that race: a team's
* agents ask at once, and each is answered by who is asking. */
export function fakeProvider(script: Scripted[] | ((body: any, n: number) => Scripted | undefined), opts: { route?: (model: string) => Fake | undefined; served?: Record<string, unknown>[] } = {}): Fake {
const requests: any[] = []
const calls: { path: string; headers: Record<string, string> }[] = []
let i = 0
const server = Bun.serve({
port: 0,
async fetch(req) {
const url = new URL(req.url)
if (req.method !== "POST" || url.pathname.endsWith("/unload")) calls.push({ path: url.pathname + url.search, headers: Object.fromEntries(req.headers.entries()) })
if (url.pathname.endsWith("/models")) return Response.json({ data: opts.served ?? [{ id: "m1", meta: { n_ctx: 32768 } }, { id: "m2", max_model_len: 8192 }] })
if (url.pathname.endsWith("/props")) return url.pathname.includes("/upstream/swapped/") ? Response.json({ default_generation_settings: { n_ctx: 16384 } }) : new Response("no", { status: 404 })
if (url.pathname.endsWith("/unload")) return new Response("ok")
if (req.method === "GET") return new Response("not found", { status: 404 })
const body = (await req.json()) as any
const to = typeof body?.model === "string" ? opts.route?.(body.model) : undefined
if (to) return fetch(to.url.replace(/\/v1$/, "") + url.pathname + url.search, { method: "POST", headers: req.headers, body: JSON.stringify(body) })
requests.push(body)
calls.push({ path: url.pathname + url.search, headers: Object.fromEntries(req.headers.entries()) })
const r = typeof script === "function" ? script(body, i++) : script[i++]
if (!r) return new Response("script exhausted", { status: 500 })
if ("status" in r) return new Response(r.body, { status: r.status })
// gapMs: a pause between chunks, to look at the screen mid-stream.
if (r.gapMs && !r.raw) {
const gap = r.gapMs
const parts = [...r.chunks.map((c) => `data: ${JSON.stringify(c)}\n\n`), ...(r.done === false ? [] : ["data: [DONE]\n\n"])]
const stream = new ReadableStream({
async start(ctl) {
for (const [n, part] of parts.entries()) {
if (n) await Bun.sleep(gap)
ctl.enqueue(new TextEncoder().encode(part))
}
ctl.close()
},
})
return new Response(stream, { headers: { "content-type": "text/event-stream" } })
}
const text = r.raw ?? r.chunks.map((c) => `data: ${JSON.stringify(c)}\n\n`).join("") + (r.done === false ? "" : "data: [DONE]\n\n")
return new Response(text, { headers: { "content-type": "text/event-stream" } })
},
})
return { url: `http://127.0.0.1:${server.port}/v1`, requests, calls, stop: () => server.stop(true) }
}
/** Chunk helpers in the OpenAI shape. */
export const delta = (d: Record<string, unknown>, finish: string | null = null) => ({ choices: [{ index: 0, delta: d, finish_reason: finish }] })
export const usage = (p: number, c: number) => ({ choices: [], usage: { prompt_tokens: p, completion_tokens: c } })
export const toolCall = (index: number | undefined, id: string | undefined, name: string | undefined, args: unknown) =>
delta({ tool_calls: [{ ...(index === undefined ? {} : { index }), ...(id ? { id } : {}), function: { ...(name ? { name } : {}), arguments: args } }] })