@juspay/neurolink
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Universal AI Development Platform with working MCP integration, multi-provider support, voice (TTS/STT/realtime), and professional CLI. 58+ external MCP servers discoverable, multimodal file processing, RAG pipelines. Build, test, and deploy AI applicatio
289 lines • 11.3 kB
JavaScript
import { spawnSync } from "child_process";
import chalk from "chalk";
import ora from "ora";
import inquirer from "inquirer";
import { logger } from "../../lib/utils/logger.js";
import { OllamaUtils } from "../utils/ollamaUtils.js";
export function addOllamaCommands(cli) {
cli.command("ollama <command>", "Manage Ollama local AI models", (yargs) => {
return yargs
.command("list-models", "List installed Ollama models", {}, listModelsHandler)
.command("pull <model>", "Download an Ollama model", {
model: {
describe: "Model name to download",
type: "string",
demandOption: true,
},
}, pullModelHandler)
.command("remove <model>", "Remove an Ollama model", {
model: {
describe: "Model name to remove",
type: "string",
demandOption: true,
},
}, removeModelHandler)
.command("status", "Check Ollama service status", {}, statusHandler)
.command("start", "Start Ollama service", {}, startHandler)
.command("stop", "Stop Ollama service", {}, stopHandler)
.command("setup", "Interactive Ollama setup", {}, setupHandler)
.demandCommand(1, "Please specify a command");
}, () => { });
}
async function listModelsHandler() {
const spinner = ora("Fetching installed models...").start();
try {
const res = spawnSync("ollama", ["list"], { encoding: "utf8" });
if (res.error) {
throw res.error;
}
spinner.succeed("Installed models:");
const output = res.stdout?.toString().trim();
if (output) {
logger.always(output);
}
else {
logger.always(chalk.yellow('No models installed. Use "neurolink ollama pull <model>" to download a model.'));
}
}
catch (error) {
spinner.fail("Failed to list models. Is Ollama installed?");
const errorMessage = error instanceof Error ? error.message : String(error);
logger.error(chalk.red("Error:", errorMessage));
logger.always(chalk.blue("\nTip: Install Ollama from https://ollama.ai"));
process.exit(1);
}
}
async function pullModelHandler(argv) {
const { model } = argv;
logger.always(chalk.blue(`Downloading model: ${model}`));
logger.always(chalk.gray("This may take several minutes..."));
try {
const res = spawnSync("ollama", ["pull", model], { stdio: "inherit" });
if (res.error) {
throw res.error;
}
if (res.status !== 0) {
throw new Error(`ollama pull exited with code ${res.status}`);
}
logger.always(chalk.green(`\n✅ Successfully downloaded ${model}`));
logger.always(chalk.blue(`\nTest it with: npx @juspay/neurolink generate "Hello!" --provider ollama --model ${model}`));
}
catch (error) {
logger.error(chalk.red(`\n❌ Failed to download ${model}`));
const errorMessage = error instanceof Error ? error.message : String(error);
logger.error(chalk.red("Error:", errorMessage));
process.exit(1);
}
}
async function removeModelHandler(argv) {
const { model } = argv;
const { confirm } = await inquirer.prompt([
{
type: "confirm",
name: "confirm",
message: `Are you sure you want to remove model "${model}"?`,
default: false,
},
]);
if (!confirm) {
logger.always(chalk.yellow("Removal cancelled."));
return;
}
const spinner = ora(`Removing model ${model}...`).start();
try {
const res = spawnSync("ollama", ["rm", model], { encoding: "utf8" });
if (res.error) {
throw res.error;
}
if (res.status !== 0) {
throw new Error(`ollama rm exited with ${res.status}`);
}
spinner.succeed(`Successfully removed ${model}`);
}
catch (_error) {
spinner.fail(`Failed to remove ${model}`);
const errorMessage = _error instanceof Error ? _error.message : String(_error);
logger.error(chalk.red("Error:", errorMessage));
process.exit(1);
}
}
async function statusHandler() {
const spinner = ora("Checking Ollama service status...").start();
try {
const res = spawnSync("ollama", ["list"], { encoding: "utf8" });
if (res.error) {
throw res.error;
}
if (res.status !== 0) {
throw new Error("Ollama not running");
}
spinner.succeed("Ollama service is running");
}
catch (error) {
spinner.fail("Ollama service is not running");
logger.debug("Ollama status check failed:", error);
logger.always(chalk.yellow("\nStart Ollama with: ollama serve"));
process.exit(1);
}
}
async function startHandler() {
await OllamaUtils.startOllamaService();
}
async function stopHandler() {
const spinner = ora("Stopping Ollama service...").start();
try {
if (process.platform === "darwin") {
try {
spawnSync("pkill", ["ollama"], { encoding: "utf8" });
}
catch {
spawnSync("killall", ["Ollama"], { encoding: "utf8" });
}
}
else if (process.platform === "linux") {
try {
spawnSync("systemctl", ["stop", "ollama"], { encoding: "utf8" });
}
catch {
spawnSync("pkill", ["ollama"], { encoding: "utf8" });
}
}
else {
spawnSync("taskkill", ["/F", "/IM", "ollama.exe"], { encoding: "utf8" });
}
spinner.succeed("Ollama service stopped");
}
catch (err) {
spinner.fail("Failed to stop Ollama service");
logger.error(chalk.red("It may not be running or requires manual stop"));
logger.error(chalk.red(`Error details: ${err}`));
}
}
async function setupHandler() {
logger.always(chalk.blue("🦙 Welcome to Ollama Setup!\n"));
// Check installation
const checkSpinner = ora("Checking Ollama installation...").start();
let isInstalled = false;
try {
spawnSync("ollama", ["--version"], { encoding: "utf8" });
isInstalled = true;
checkSpinner.succeed("Ollama is installed");
}
catch {
checkSpinner.fail("Ollama is not installed");
}
if (!isInstalled) {
logger.always(chalk.yellow("\nOllama needs to be installed first."));
logger.always(chalk.blue("\nInstallation instructions:"));
if (process.platform === "darwin") {
logger.always("\nFor macOS:");
logger.always(chalk.gray(" brew install ollama"));
logger.always(chalk.gray(" # or download from https://ollama.ai"));
}
else if (process.platform === "linux") {
logger.always("\nFor Linux:");
logger.always(chalk.gray(" curl -fsSL https://ollama.ai/install.sh | sh"));
}
else {
logger.always("\nFor Windows:");
logger.always(chalk.gray(" Download from https://ollama.ai"));
}
const { proceedAnyway } = await inquirer.prompt([
{
type: "confirm",
name: "proceedAnyway",
message: "Would you like to continue with setup anyway?",
default: false,
},
]);
if (!proceedAnyway) {
logger.always(chalk.blue("\nInstall Ollama and run setup again!"));
return;
}
}
// Check if service is running
let serviceRunning = false;
try {
spawnSync("ollama", ["list"], { encoding: "utf8" });
serviceRunning = true;
logger.always(chalk.green("\n✅ Ollama service is running"));
}
catch {
logger.always(chalk.yellow("\n⚠️ Ollama service is not running"));
const { startService } = await inquirer.prompt([
{
type: "confirm",
name: "startService",
message: "Would you like to start the Ollama service?",
default: true,
},
]);
if (startService) {
await startHandler();
serviceRunning = true;
}
}
if (serviceRunning) {
// List available models
logger.always(chalk.blue("\n📦 Popular Ollama models:"));
logger.always(" • llama2 (7B) - General purpose");
logger.always(" • codellama (7B) - Code generation");
logger.always(" • mistral (7B) - Fast and efficient");
logger.always(" • tinyllama (1B) - Lightweight");
logger.always(" • phi (2.7B) - Microsoft's compact model");
const { downloadModel } = await inquirer.prompt([
{
type: "confirm",
name: "downloadModel",
message: "Would you like to download a model?",
default: true,
},
]);
if (downloadModel) {
const { selectedModel } = await inquirer.prompt([
{
type: "select",
name: "selectedModel",
message: "Select a model to download:",
choices: [
{
name: "llama2 (7B) - Recommended for general use",
value: "llama2",
},
{
name: "codellama (7B) - Best for code generation",
value: "codellama",
},
{ name: "mistral (7B) - Fast and efficient", value: "mistral" },
{ name: "tinyllama (1B) - Lightweight, fast", value: "tinyllama" },
{ name: "phi (2.7B) - Microsoft's compact model", value: "phi" },
{ name: "Other (enter manually)", value: "other" },
],
},
]);
let modelToDownload = selectedModel;
if (selectedModel === "other") {
const { customModel } = await inquirer.prompt([
{
type: "input",
name: "customModel",
message: "Enter the model name:",
validate: (input) => input.trim().length > 0 || "Model name is required",
},
]);
modelToDownload = customModel;
}
await pullModelHandler({ model: modelToDownload });
}
}
logger.always(chalk.green("\n✅ Setup complete!\n"));
logger.always(chalk.blue("Next steps:"));
logger.always("1. List models: " + chalk.gray("neurolink ollama list-models"));
logger.always("2. Generate text: " +
chalk.gray('neurolink generate "Hello!" --provider ollama'));
logger.always("3. Use specific model: " +
chalk.gray('neurolink generate "Hello!" --provider ollama --model codellama'));
logger.always(chalk.gray("\nFor more information, see: https://docs.neurolink.ai/providers/ollama"));
}
export default addOllamaCommands;
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