@juspay/neurolink/dist/providers/lmStudio.js

The pipe layer of an AI nervous system: one interface connecting provider neurons to your application, across three inference types — generate, stream and decide. `decide` returns typed, calibrated judgements from a non-generative model (~400ms, ~$0.00002

import { InvalidModelError } from "../types/index.js";
import { classifyProviderError, DEFAULT_ERROR_RULES, } from "../utils/errorClassifier.js";
import { logger } from "../utils/logger.js";
import { redactUrlCredentials } from "../utils/logSanitize.js";
import { OpenAIChatCompletionsProvider } from "./openaiChatCompletionsBase.js";
import { buildLocalUnreachableErrorRule } from "./localRuntimeOpenAICompat.js";
const LM_STUDIO_DEFAULT_BASE_URL = "http://localhost:1234/v1";
const LM_STUDIO_PLACEHOLDER_KEY = "lm-studio";
const FALLBACK_MODEL = "local-model";
const getLmStudioBaseURL = () => {
    return process.env.LM_STUDIO_BASE_URL || LM_STUDIO_DEFAULT_BASE_URL;
};
/**
 * LM Studio Provider — direct HTTP, no AI SDK.
 *
 * Wraps the LM Studio local server (https://lmstudio.ai/) which exposes an
 * OpenAI-compatible API at http://localhost:1234/v1 by default.
 * Auto-discovers the loaded model via /v1/models if no model is specified.
 * All request/stream/tool-loop orchestration lives in
 * `OpenAIChatCompletionsProvider`; this class only declares configuration
 * and provider-specific error mapping.
 *
 * @see https://lmstudio.ai/
 */
export class LMStudioProvider extends OpenAIChatCompletionsProvider {
    constructor(modelName, sdk, _region, credentials) {
        // LM Studio's local server doesn't authenticate, but the base HTTP client
        // requires an apiKey. Allow override via credentials/env for users who
        // run LM Studio behind an auth-proxying reverse-proxy.
        const apiKey = credentials?.apiKey ??
            process.env.LM_STUDIO_API_KEY ??
            LM_STUDIO_PLACEHOLDER_KEY;
        const baseURL = credentials?.baseURL ?? getLmStudioBaseURL();
        super("lm-studio", modelName, sdk, { baseURL, apiKey });
        logger.debug("LM Studio Provider initialized", {
            modelName: this.modelName,
            providerName: this.providerName,
            baseURL: redactUrlCredentials(this.config.baseURL),
        });
    }
    getProviderName() {
        return "lm-studio";
    }
    getDefaultModel() {
        return process.env.LM_STUDIO_MODEL || "";
    }
    getFallbackModelName() {
        return FALLBACK_MODEL;
    }
    formatProviderError(error) {
        const rules = [
            buildLocalUnreachableErrorRule(error, () => `LM Studio server not reachable at ${redactUrlCredentials(this.config.baseURL)}. ` +
                `Open the LM Studio app, load a model, and click "Start Server".`),
            {
                match: (ctx) => /model_not_found|404/.test(ctx.message),
                errorClass: InvalidModelError,
                message: () => `LM Studio model '${this.modelName}' is not loaded. Load it in the LM Studio app first.`,
            },
            ...DEFAULT_ERROR_RULES,
        ];
        return classifyProviderError(error, rules, this.providerName, this.modelName);
    }
    async validateConfiguration() {
        return this.probeModelsEndpoint(this.config.apiKey && this.config.apiKey !== LM_STUDIO_PLACEHOLDER_KEY
            ? { Authorization: `Bearer ${this.config.apiKey}` }
            : {});
    }
    getConfiguration() {
        return {
            provider: this.providerName,
            model: this.modelName || this.resolvedModel || FALLBACK_MODEL,
            defaultModel: this.getDefaultModel(),
            baseURL: this.config.baseURL,
        };
    }
}