mirror of
https://github.com/openclaw/openclaw.git
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242 lines
9.2 KiB
TypeScript
242 lines
9.2 KiB
TypeScript
// Lmstudio plugin entrypoint registers its OpenClaw integration.
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import {
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definePluginEntry,
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type OpenClawPluginApi,
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type ProviderAuthContext,
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type ProviderAuthMethod,
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type ProviderAuthMethodNonInteractiveContext,
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type ProviderAuthResult,
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type ProviderRuntimeModel,
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} from "openclaw/plugin-sdk/plugin-entry";
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import type { OpenClawConfig } from "openclaw/plugin-sdk/plugin-entry";
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import {
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CUSTOM_LOCAL_AUTH_MARKER,
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normalizeOptionalSecretInput,
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} from "openclaw/plugin-sdk/provider-auth";
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import { buildProviderToolCompatFamilyHooks } from "openclaw/plugin-sdk/provider-tools";
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import { lmstudioMemoryEmbeddingProviderAdapter } from "./memory-embedding-adapter.js";
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import {
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LMSTUDIO_DEFAULT_API_KEY_ENV_VAR,
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LMSTUDIO_DEFAULT_INFERENCE_BASE_URL,
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LMSTUDIO_DOCKER_HOST_INFERENCE_BASE_URL,
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LMSTUDIO_LOCAL_API_KEY_PLACEHOLDER,
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LMSTUDIO_PROVIDER_LABEL,
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} from "./src/defaults.js";
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import {
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normalizeLmstudioConfiguredCatalogEntries,
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normalizeLmstudioProviderConfig,
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resolveLmstudioInferenceBase,
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} from "./src/models.js";
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import { shouldUseLmstudioSyntheticAuth } from "./src/provider-auth.js";
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import { wrapLmstudioInferencePreload } from "./src/stream.js";
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const PROVIDER_ID = "lmstudio";
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// Intentional: dynamic models are cached per LM Studio endpoint (`baseUrl`) only.
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const cachedDynamicModels = new Map<string, ProviderRuntimeModel[]>();
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type LmstudioNonInteractiveValidationContext = Parameters<
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NonNullable<ProviderAuthMethod["validateNonInteractive"]>
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>[0];
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async function validateLmstudioNonInteractive(
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ctx: LmstudioNonInteractiveValidationContext,
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): Promise<boolean> {
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const configuredBaseUrl = normalizeOptionalSecretInput(ctx.opts.customBaseUrl);
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const dockerSetup = ["1", "true", "yes", "on"].includes(
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process.env.OPENCLAW_DOCKER_SETUP?.trim().toLowerCase() ?? "",
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);
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const baseUrl = resolveLmstudioInferenceBase(
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configuredBaseUrl ||
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(dockerSetup ? LMSTUDIO_DOCKER_HOST_INFERENCE_BASE_URL : LMSTUDIO_DEFAULT_INFERENCE_BASE_URL),
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);
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const providerApiKey = normalizeOptionalSecretInput(ctx.opts.lmstudioApiKey);
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const resolvedApiKey = await ctx.resolveApiKey({
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provider: PROVIDER_ID,
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flagValue: providerApiKey ?? normalizeOptionalSecretInput(ctx.opts.customApiKey),
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flagName: providerApiKey === undefined ? "--custom-api-key" : "--lmstudio-api-key",
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envVar: LMSTUDIO_DEFAULT_API_KEY_ENV_VAR,
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envVarName: LMSTUDIO_DEFAULT_API_KEY_ENV_VAR,
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required: false,
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});
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// A reset preflight may inspect the model catalog but must never invoke
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// setup, write credentials, load a model, or mutate the model server.
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const { fetchLmstudioModels } = await import("./src/models.fetch.js");
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const discovery = await fetchLmstudioModels({
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baseUrl,
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apiKey: resolvedApiKey?.key ?? LMSTUDIO_LOCAL_API_KEY_PLACEHOLDER,
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timeoutMs: 5000,
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});
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if (!discovery.reachable) {
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ctx.runtime.error(
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`LM Studio could not be reached at ${baseUrl}.\nStart LM Studio (or run lms server start) and re-run setup.`,
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);
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ctx.runtime.exit(1);
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return false;
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}
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if (discovery.status !== undefined && discovery.status >= 400) {
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ctx.runtime.error(
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`LM Studio returned HTTP ${discovery.status} while listing models at ${baseUrl}.\nCheck the base URL and API key, then re-run setup.`,
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);
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ctx.runtime.exit(1);
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return false;
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}
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const availableModels = discovery.models
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.filter((model) => model.type === "llm")
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.map((model) => model.key?.trim())
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.filter((model): model is string => Boolean(model));
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// Setup matches the requested wire key unchanged. Accepting provider-
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// qualified refs here would permit reset before setup rejects the model.
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const requestedModel = normalizeOptionalSecretInput(ctx.opts.customModelId);
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if (requestedModel && !availableModels.includes(requestedModel)) {
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ctx.runtime.error(
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`LM Studio model ${requestedModel} was not found at ${baseUrl}.\nAvailable models: ${availableModels.join(", ")}`,
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);
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ctx.runtime.exit(1);
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return false;
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}
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if (availableModels.length === 0) {
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ctx.runtime.error(
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`No LM Studio LLM models were found at ${baseUrl}.\nLoad at least one model in LM Studio (or run lms load), then re-run setup.`,
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);
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ctx.runtime.exit(1);
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return false;
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}
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return true;
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}
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function resolveLmstudioAugmentedCatalogEntries(config: OpenClawConfig | undefined) {
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if (!config) {
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return [];
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}
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return normalizeLmstudioConfiguredCatalogEntries(config.models?.providers?.lmstudio?.models).map(
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(entry) => ({
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provider: PROVIDER_ID,
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id: entry.id,
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name: entry.name ?? entry.id,
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compat: { ...entry.compat, supportsUsageInStreaming: true },
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contextWindow: entry.contextWindow,
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contextTokens: entry.contextTokens,
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reasoning: entry.reasoning,
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input: entry.input,
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}),
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);
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}
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/** Lazily loads setup helpers so provider wiring stays lightweight at startup. */
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async function loadProviderSetup() {
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return await import("./api.js");
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}
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export default definePluginEntry({
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id: PROVIDER_ID,
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name: "LM Studio Provider",
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description: "Bundled LM Studio provider plugin",
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register(api: OpenClawPluginApi) {
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api.registerMemoryEmbeddingProvider(lmstudioMemoryEmbeddingProviderAdapter);
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api.registerProvider({
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id: PROVIDER_ID,
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label: "LM Studio",
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docsPath: "/providers/lmstudio",
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envVars: [LMSTUDIO_DEFAULT_API_KEY_ENV_VAR],
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auth: [
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{
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id: "custom",
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label: LMSTUDIO_PROVIDER_LABEL,
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hint: "Connect to a running LM Studio server and use an already loaded model",
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kind: "custom",
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appGuidedSetup: {
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detect: async (ctx) => {
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const providerSetup = await loadProviderSetup();
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const result = await providerSetup.prepareAppGuidedLmstudioSetup(ctx);
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if (!result?.defaultModel) {
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return null;
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}
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const provider = result.configPatch?.models?.providers?.[PROVIDER_ID];
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return {
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modelRef: result.defaultModel,
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detail: `${result.defaultModel.slice(`${PROVIDER_ID}/`.length)} at ${provider?.baseUrl ?? "LM Studio"}`,
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};
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},
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prepare: async (ctx) => {
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const providerSetup = await loadProviderSetup();
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return await providerSetup.prepareAppGuidedLmstudioSetup(ctx);
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},
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},
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run: async (ctx: ProviderAuthContext): Promise<ProviderAuthResult> => {
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const providerSetup = await loadProviderSetup();
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return await providerSetup.promptAndConfigureLmstudioInteractive({
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config: ctx.config,
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agentDir: ctx.agentDir,
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prompter: ctx.prompter,
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secretInputMode: ctx.secretInputMode,
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allowSecretRefPrompt: ctx.allowSecretRefPrompt,
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isRemote: ctx.isRemote,
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signal: ctx.signal,
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});
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},
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validateNonInteractive: validateLmstudioNonInteractive,
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runNonInteractive: async (ctx: ProviderAuthMethodNonInteractiveContext) => {
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const providerSetup = await loadProviderSetup();
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return await providerSetup.configureLmstudioNonInteractive(ctx);
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},
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},
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],
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catalog: {
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// Run after early providers so local LM Studio detection does not dominate resolution.
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order: "late",
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run: async (ctx) => {
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const providerSetup = await loadProviderSetup();
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return await providerSetup.discoverLmstudioProvider(ctx);
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},
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},
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resolveSyntheticAuth: ({ providerConfig }) => {
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if (!shouldUseLmstudioSyntheticAuth(providerConfig)) {
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return undefined;
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}
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return {
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apiKey: CUSTOM_LOCAL_AUTH_MARKER,
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source: "models.providers.lmstudio (synthetic local key)",
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mode: "api-key" as const,
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};
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},
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shouldDeferSyntheticProfileAuth: ({ resolvedApiKey }) =>
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resolvedApiKey?.trim() === LMSTUDIO_LOCAL_API_KEY_PLACEHOLDER ||
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resolvedApiKey?.trim() === CUSTOM_LOCAL_AUTH_MARKER,
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normalizeConfig: ({ providerConfig }) => normalizeLmstudioProviderConfig(providerConfig),
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prepareDynamicModel: async (ctx) => {
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const providerSetup = await loadProviderSetup();
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cachedDynamicModels.set(
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ctx.providerConfig?.baseUrl ?? "",
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await providerSetup.prepareLmstudioDynamicModels(ctx),
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);
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},
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resolveDynamicModel: (ctx) =>
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cachedDynamicModels
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.get(ctx.providerConfig?.baseUrl ?? "")
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?.find((model) => model.id === ctx.modelId),
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augmentModelCatalog: (ctx) => resolveLmstudioAugmentedCatalogEntries(ctx.config),
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wrapStreamFn: wrapLmstudioInferencePreload,
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...buildProviderToolCompatFamilyHooks("llamacpp-gbnf"),
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wizard: {
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setup: {
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choiceId: PROVIDER_ID,
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choiceLabel: "LM Studio",
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choiceHint: "Connect to a running LM Studio server and use an already loaded model",
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groupId: PROVIDER_ID,
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groupLabel: "LM Studio",
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groupHint: "Self-hosted open-weight models",
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methodId: "custom",
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},
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modelPicker: {
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label: "LM Studio (custom)",
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hint: "Detect models from LM Studio /api/v1/models",
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methodId: "custom",
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},
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},
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});
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},
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});
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