akm-cli/dist/setup/steps/connection-shared.js

akm (Agent Knowledge Manager) — a portable, local-first capability library for AI agents. Discover, load, share, and improve reusable skills, scripts, workflows, and knowledge across any shell-capable coding agent, including Claude Code, OpenCode, and Cur

// This Source Code Form is subject to the terms of the Mozilla Public
// License, v. 2.0. If a copy of the MPL was not distributed with this
// file, You can obtain one at https://mozilla.org/MPL/2.0/.
/**
 * Shared collect-input / probe / derive-config helpers for the wizard's
 * connection steps (§4.6 dedup of the three near-identical steps in
 * connection.ts). Prompt copy, validation messages, and the probe's spinner
 * text are shared VERBATIM so the wizard's observable flow is unchanged;
 * each step keeps its own option assembly and branching.
 */
import * as p from "../../cli/clack.js";
import { probeLlmReachable } from "../../llm/client.js";
import { prompt, promptOrBack } from "../prompt.js";
// ── Derive-config ───────────────────────────────────────────────────────────
/** Standard chat-connection config shared by every provider branch. */
export function llmConnection(provider, endpoint, model, extra) {
    return {
        provider,
        endpoint,
        model,
        temperature: 0.3,
        ...(extra ?? {}),
    };
}
/** The "Keep current: ..." select option appended when a connection exists. */
export function keepCurrentOption(current) {
    return {
        value: "keep",
        label: `Keep current: ${current.provider ?? current.endpoint}`,
        hint: current.model,
    };
}
/** Hint text for the "LM Studio / local server" select option. */
export function lmStudioOptionHint(lmStudio) {
    return lmStudio?.available
        ? `${lmStudio.models.length} model${lmStudio.models.length === 1 ? "" : "s"} detected`
        : "http://localhost:1234";
}
// ── Collect-input ───────────────────────────────────────────────────────────
/** Non-empty model-name text prompt shared by every provider branch. */
export async function promptModelName(opts) {
    return prompt(() => p.text({
        message: opts.message ?? "Model name:",
        placeholder: opts.placeholder,
        ...(opts.defaultValue ? { defaultValue: opts.defaultValue } : {}),
        validate: (v) => (!v?.trim() ? "Model name cannot be empty" : undefined),
    }));
}
/** http(s)-validated endpoint text prompt shared by every endpoint branch. */
export async function promptEndpointUrl(opts) {
    const schemeMessage = opts.schemeMessage ?? "Must start with http:// or https://";
    return prompt(() => p.text({
        message: opts.message ?? "Endpoint URL:",
        placeholder: opts.placeholder,
        ...(opts.defaultValue ? { defaultValue: opts.defaultValue } : {}),
        validate: (v) => {
            if (!v?.trim())
                return "Endpoint cannot be empty";
            if (!v.startsWith("http://") && !v.startsWith("https://"))
                return schemeMessage;
        },
    }));
}
/**
 * LM Studio model selection: pick from the detected models (with an
 * "Enter manually..." escape hatch) or fall back to a free-text prompt when
 * nothing was detected.
 */
export async function promptLmStudioModel(lmStudio, currentModel) {
    const lmsModels = lmStudio?.available && lmStudio.models.length > 0 ? lmStudio.models : [];
    if (lmsModels.length > 0) {
        const modelChoice = await prompt(() => p.select({
            message: "Model name:",
            options: [
                ...lmsModels.map((m) => ({ value: m, label: m })),
                { value: "__manual__", label: "Enter manually..." },
            ],
            initialValue: currentModel && lmsModels.includes(currentModel) ? currentModel : lmsModels[0],
        }));
        if (modelChoice !== "__manual__")
            return modelChoice;
    }
    return promptModelName({ placeholder: currentModel ?? "local-model", defaultValue: currentModel });
}
/**
 * Optional API-key ENV VAR NAME prompt (never the key value — saveConfig()
 * strips secrets). Escape backs out with `null`.
 */
export async function promptApiKeyEnvVarName() {
    return promptOrBack(() => p.text({
        message: "API key environment variable name (optional):",
        placeholder: "CUSTOM_LLM_API_KEY",
        validate: (value) => value && !/^[A-Za-z_][A-Za-z0-9_]*$/.test(value)
            ? "Use an environment variable name, not a key value"
            : undefined,
    }));
}
// ── Probe ───────────────────────────────────────────────────────────────────
/**
 * Best-effort reachability probe — never blocks setup. Does NOT probe or
 * cache structured-output support: `chatCompletion` now attempts
 * `response_format: json_schema` fresh on every call that supplies a schema
 * and falls back once per call on a 4xx (see `llm/client.ts`), so there is
 * no verdict for setup to determine or persist here.
 */
export async function probeLlmConnection(llm) {
    const probeSpin = p.spinner();
    probeSpin.start("Probing LLM connectivity...");
    const probe = await probeLlmReachable(llm);
    if (probe.reachable) {
        probeSpin.stop("LLM reachable.");
    }
    else {
        probeSpin.stop("LLM not reachable.");
        p.log.warn(`Could not reach the LLM endpoint${probe.error ? ` (${probe.error})` : ""}. Configuration was saved; verify your endpoint and API key, then retry.`);
    }
}