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chore: import upstream snapshot with attribution
2026-07-13 12:43:05 +08:00

123 lines
4.1 KiB
TypeScript

/**
* LM Studio detection — probes `GET <baseURL>/models` and parses the OpenAI-shaped
* `{ object: "list", data: [...] }` response. The plugin uses this for two things:
*
* 1. Init-time logging: warn the operator if LM Studio is configured but unreachable.
* 2. The auto-enable predicate: turn the plugin on when the local server responds.
*
* Detection is kept side-effect free and accepts an injected `fetch` so unit tests
* can provide a fake implementation without touching network state.
*/
import type { LMStudioModelInfo, LMStudioModelsResponse } from "../types";
import { DEFAULT_LMSTUDIO_URL } from "./config";
export interface DetectionOptions {
baseURL?: string;
/** Override `fetch` (used by tests and the browser/sandbox build). */
fetcher?: typeof fetch;
/** Per-request timeout — LM Studio should answer instantly; bail fast otherwise. */
timeoutMs?: number;
/** Optional Bearer token (LM Studio behind an auth proxy). */
apiKey?: string;
}
export interface DetectionResult {
available: boolean;
baseURL: string;
/** Parsed model list when `available` is true. */
models?: LMStudioModelInfo[];
/** Last error encountered when `available` is false. */
error?: string;
}
function normalizeBaseURL(input: string | undefined): string {
const raw = (input ?? DEFAULT_LMSTUDIO_URL).replace(/\/+$/, "");
if (/\/v\d+$/.test(raw)) {
return raw;
}
return `${raw}/v1`;
}
/**
* Parses a `GET /v1/models` response body, defensively against
* implementations that return a bare array. Returns null when the body
* is not a recognizable shape.
*/
export function parseModelsResponse(body: unknown): LMStudioModelInfo[] | null {
if (Array.isArray(body)) {
return body.filter((entry): entry is LMStudioModelInfo => {
return Boolean(entry) && typeof (entry as LMStudioModelInfo).id === "string";
});
}
if (body && typeof body === "object") {
const shaped = body as Partial<LMStudioModelsResponse>;
if (Array.isArray(shaped.data)) {
return shaped.data.filter((entry): entry is LMStudioModelInfo => {
return Boolean(entry) && typeof entry.id === "string";
});
}
}
return null;
}
/**
* Probes the configured LM Studio endpoint. Always returns a result — never throws.
*
* Why catch all errors: this helper is called from auto-enable and the plugin `init`
* hook. A network error during init must not crash the runtime; we surface it via the
* returned `error` field and let the caller decide what to do.
*/
export async function detectLMStudio(options: DetectionOptions = {}): Promise<DetectionResult> {
const baseURL = normalizeBaseURL(options.baseURL);
const fetcher = options.fetcher ?? fetch;
const timeoutMs = options.timeoutMs ?? 1500;
const controller = new AbortController();
const timer = setTimeout(() => controller.abort(), timeoutMs);
try {
const headers: Record<string, string> = { "Content-Type": "application/json" };
if (options.apiKey) {
headers.Authorization = `Bearer ${options.apiKey}`;
}
const response = await fetcher(`${baseURL}/models`, {
method: "GET",
headers,
signal: controller.signal,
});
if (!response.ok) {
return {
available: false,
baseURL,
error: `HTTP ${response.status} ${response.statusText}`,
};
}
const body = (await response.json()) as unknown;
const models = parseModelsResponse(body);
if (!models) {
return {
available: false,
baseURL,
error: "unexpected /v1/models response shape",
};
}
return { available: true, baseURL, models };
} catch (err) {
// error-policy:J4 explicit degrade — this probe's contract (documented above)
// is to always return a result, never throw: a network/timeout failure IS the
// "not available" answer, carried in the typed `error` field, not a swallowed
// error. Callers (auto-enable, init) branch on `available`.
const message = err instanceof Error ? err.message : String(err);
return { available: false, baseURL, error: message };
} finally {
clearTimeout(timer);
}
}