Merge remote-tracking branch 'origin' into ms/use-inquirer

helpers/providers/anthropic.ts

@@ -1,6 +1,6 @@
-import prompts from "prompts";
+import inquirer from "inquirer";
 import { ModelConfigParams } from ".";
-import { questionHandlers, toChoice } from "../../questions/utils";
+import { toChoice } from "../../questions/utils";
 
 const MODELS = [
   "claude-3-opus",
@@ -57,41 +57,36 @@ export async function askAnthropicQuestions({
   };
 
   if (!config.apiKey) {
-    const { key } = await prompts(
+    const { key } = await inquirer.prompt([
       {
-        type: "text",
+        type: "input",
         name: "key",
         message:
           "Please provide your Anthropic API key (or leave blank to use ANTHROPIC_API_KEY env variable):",
       },
-      questionHandlers,
-    );
+    ]);
     config.apiKey = key || process.env.ANTHROPIC_API_KEY;
   }
 
   if (askModels) {
-    const { model } = await prompts(
+    const { model } = await inquirer.prompt([
       {
-        type: "select",
+        type: "list",
         name: "model",
         message: "Which LLM model would you like to use?",
         choices: MODELS.map(toChoice),
-        initial: 0,
       },
-      questionHandlers,
-    );
+    ]);
     config.model = model;
 
-    const { embeddingModel } = await prompts(
+    const { embeddingModel } = await inquirer.prompt([
       {
-        type: "select",
+        type: "list",
         name: "embeddingModel",
         message: "Which embedding model would you like to use?",
         choices: Object.keys(EMBEDDING_MODELS).map(toChoice),
-        initial: 0,
       },
-      questionHandlers,
-    );
+    ]);
     config.embeddingModel = embeddingModel;
     config.dimensions =
       EMBEDDING_MODELS[

helpers/providers/azure.ts

@@ -1,6 +1,5 @@
-import prompts from "prompts";
+import inquirer from "inquirer";
 import { ModelConfigParams, ModelConfigQuestionsParams } from ".";
-import { questionHandlers } from "../../questions/utils";
 
 const ALL_AZURE_OPENAI_CHAT_MODELS: Record<string, { openAIModel: string }> = {
   "gpt-35-turbo": { openAIModel: "gpt-3.5-turbo" },
@@ -67,28 +66,24 @@ export async function askAzureQuestions({
   };
 
   if (askModels) {
-    const { model } = await prompts(
+    const { model } = await inquirer.prompt([
       {
-        type: "select",
+        type: "list",
         name: "model",
         message: "Which LLM model would you like to use?",
         choices: getAvailableModelChoices(),
-        initial: 0,
       },
-      questionHandlers,
-    );
+    ]);
     config.model = model;
 
-    const { embeddingModel } = await prompts(
+    const { embeddingModel } = await inquirer.prompt([
       {
-        type: "select",
+        type: "list",
         name: "embeddingModel",
         message: "Which embedding model would you like to use?",
         choices: getAvailableEmbeddingModelChoices(),
-        initial: 0,
       },
-      questionHandlers,
-    );
+    ]);
     config.embeddingModel = embeddingModel;
     config.dimensions = getDimensions(embeddingModel);
   }
@@ -98,14 +93,14 @@ export async function askAzureQuestions({
 
 function getAvailableModelChoices() {
   return Object.keys(ALL_AZURE_OPENAI_CHAT_MODELS).map((key) => ({
-    title: key,
+    name: key,
     value: key,
   }));
 }
 
 function getAvailableEmbeddingModelChoices() {
   return Object.keys(ALL_AZURE_OPENAI_EMBEDDING_MODELS).map((key) => ({
-    title: key,
+    name: key,
     value: key,
   }));
 }

helpers/providers/gemini.ts

@@ -1,6 +1,6 @@
-import prompts from "prompts";
+import inquirer from "inquirer";
 import { ModelConfigParams } from ".";
-import { questionHandlers, toChoice } from "../../questions/utils";
+import { toChoice } from "../../questions/utils";
 
 const MODELS = ["gemini-1.5-pro-latest", "gemini-pro", "gemini-pro-vision"];
 type ModelData = {
@@ -41,41 +41,36 @@ export async function askGeminiQuestions({
   };
 
   if (!config.apiKey) {
-    const { key } = await prompts(
+    const { key } = await inquirer.prompt([
       {
-        type: "text",
+        type: "input",
         name: "key",
         message:
           "Please provide your Google API key (or leave blank to use GOOGLE_API_KEY env variable):",
       },
-      questionHandlers,
-    );
+    ]);
     config.apiKey = key || process.env.GOOGLE_API_KEY;
   }
 
   if (askModels) {
-    const { model } = await prompts(
+    const { model } = await inquirer.prompt([
       {
-        type: "select",
+        type: "list",
         name: "model",
         message: "Which LLM model would you like to use?",
         choices: MODELS.map(toChoice),
-        initial: 0,
       },
-      questionHandlers,
-    );
+    ]);
     config.model = model;
 
-    const { embeddingModel } = await prompts(
+    const { embeddingModel } = await inquirer.prompt([
       {
-        type: "select",
+        type: "list",
         name: "embeddingModel",
         message: "Which embedding model would you like to use?",
         choices: Object.keys(EMBEDDING_MODELS).map(toChoice),
-        initial: 0,
       },
-      questionHandlers,
-    );
+    ]);
     config.embeddingModel = embeddingModel;
     config.dimensions = EMBEDDING_MODELS[embeddingModel].dimensions;
   }

helpers/providers/groq.ts

@@ -1,6 +1,6 @@
-import prompts from "prompts";
+import inquirer from "inquirer";
 import { ModelConfigParams } from ".";
-import { questionHandlers, toChoice } from "../../questions/utils";
+import { toChoice } from "../../questions/utils";
 
 import got from "got";
 import ora from "ora";
@@ -97,43 +97,38 @@ export async function askGroqQuestions({
   };
 
   if (!config.apiKey) {
-    const { key } = await prompts(
+    const { key } = await inquirer.prompt([
       {
-        type: "text",
+        type: "input",
         name: "key",
         message:
           "Please provide your Groq API key (or leave blank to use GROQ_API_KEY env variable):",
       },
-      questionHandlers,
-    );
+    ]);
     config.apiKey = key || process.env.GROQ_API_KEY;
   }
 
   if (askModels) {
     const modelChoices = await getAvailableModelChoicesGroq(config.apiKey!);
 
-    const { model } = await prompts(
+    const { model } = await inquirer.prompt([
       {
-        type: "select",
+        type: "list",
         name: "model",
         message: "Which LLM model would you like to use?",
         choices: modelChoices,
-        initial: 0,
       },
-      questionHandlers,
-    );
+    ]);
     config.model = model;
 
-    const { embeddingModel } = await prompts(
+    const { embeddingModel } = await inquirer.prompt([
       {
-        type: "select",
+        type: "list",
         name: "embeddingModel",
         message: "Which embedding model would you like to use?",
         choices: Object.keys(EMBEDDING_MODELS).map(toChoice),
-        initial: 0,
       },
-      questionHandlers,
-    );
+    ]);
     config.embeddingModel = embeddingModel;
     config.dimensions =
       EMBEDDING_MODELS[

helpers/providers/huggingface.ts

@@ -1,6 +1,6 @@
-import prompts from "prompts";
+import inquirer from "inquirer";
 import { ModelConfigParams } from ".";
-import { questionHandlers, toChoice } from "../../questions/utils";
+import { toChoice } from "../../questions/utils";
 
 const MODELS = ["HuggingFaceH4/zephyr-7b-alpha"];
 type ModelData = {
@@ -38,28 +38,24 @@ export async function askHuggingfaceQuestions({
   };
 
   if (askModels) {
-    const { model } = await prompts(
+    const { model } = await inquirer.prompt([
       {
-        type: "select",
+        type: "list",
         name: "model",
         message: "Which Hugging Face model would you like to use?",
         choices: MODELS.map(toChoice),
-        initial: 0,
       },
-      questionHandlers,
-    );
+    ]);
     config.model = model;
 
-    const { embeddingModel } = await prompts(
+    const { embeddingModel } = await inquirer.prompt([
       {
-        type: "select",
+        type: "list",
         name: "embeddingModel",
         message: "Which embedding model would you like to use?",
         choices: Object.keys(EMBEDDING_MODELS).map(toChoice),
-        initial: 0,
       },
-      questionHandlers,
-    );
+    ]);
     config.embeddingModel = embeddingModel;
     config.dimensions = EMBEDDING_MODELS[embeddingModel].dimensions;
   }

helpers/providers/index.ts

@@ -1,5 +1,4 @@
-import prompts from "prompts";
-import { questionHandlers } from "../../questions/utils";
+import inquirer from "inquirer";
 import { ModelConfig, ModelProvider, TemplateFramework } from "../types";
 import { askAnthropicQuestions } from "./anthropic";
 import { askAzureQuestions } from "./azure";
@@ -29,29 +28,27 @@ export async function askModelConfig({
   let modelProvider: ModelProvider = DEFAULT_MODEL_PROVIDER;
   if (askModels) {
     let choices = [
-      { title: "OpenAI", value: "openai" },
-      { title: "Groq", value: "groq" },
-      { title: "Ollama", value: "ollama" },
-      { title: "Anthropic", value: "anthropic" },
-      { title: "Gemini", value: "gemini" },
-      { title: "Mistral", value: "mistral" },
-      { title: "AzureOpenAI", value: "azure-openai" },
+      { name: "OpenAI", value: "openai" },
+      { name: "Groq", value: "groq" },
+      { name: "Ollama", value: "ollama" },
+      { name: "Anthropic", value: "anthropic" },
+      { name: "Gemini", value: "gemini" },
+      { name: "Mistral", value: "mistral" },
+      { name: "AzureOpenAI", value: "azure-openai" },
     ];
 
     if (framework === "fastapi") {
-      choices.push({ title: "T-Systems", value: "t-systems" });
-      choices.push({ title: "Huggingface", value: "huggingface" });
+      choices.push({ name: "T-Systems", value: "t-systems" });
+      choices.push({ name: "Huggingface", value: "huggingface" });
     }
-    const { provider } = await prompts(
+    const { provider } = await inquirer.prompt([
       {
-        type: "select",
+        type: "list",
         name: "provider",
         message: "Which model provider would you like to use",
         choices: choices,
-        initial: 0,
       },
-      questionHandlers,
-    );
+    ]);
     modelProvider = provider;
   }
 

helpers/providers/llmhub.ts

@@ -1,9 +1,8 @@
 import got from "got";
+import inquirer from "inquirer";
 import ora from "ora";
 import { red } from "picocolors";
-import prompts from "prompts";
 import { ModelConfigParams } from ".";
-import { questionHandlers } from "../../questions/utils";
 
 export const TSYSTEMS_LLMHUB_API_URL =
   "https://llm-server.llmhub.t-systems.net/v2";
@@ -57,9 +56,9 @@ export async function askLLMHubQuestions({
   };
 
   if (!config.apiKey) {
-    const { key } = await prompts(
+    const { key } = await inquirer.prompt([
       {
-        type: "text",
+        type: "input",
         name: "key",
         message: askModels
           ? "Please provide your LLMHub API key (or leave blank to use T_SYSTEMS_LLMHUB_API_KEY env variable):"
@@ -74,34 +73,29 @@ export async function askLLMHubQuestions({
           return true;
         },
       },
-      questionHandlers,
-    );
+    ]);
     config.apiKey = key || process.env.T_SYSTEMS_LLMHUB_API_KEY;
   }
 
   if (askModels) {
-    const { model } = await prompts(
+    const { model } = await inquirer.prompt([
       {
-        type: "select",
+        type: "list",
         name: "model",
         message: "Which LLM model would you like to use?",
         choices: await getAvailableModelChoices(false, config.apiKey),
-        initial: 0,
       },
-      questionHandlers,
-    );
+    ]);
     config.model = model;
 
-    const { embeddingModel } = await prompts(
+    const { embeddingModel } = await inquirer.prompt([
       {
-        type: "select",
+        type: "list",
         name: "embeddingModel",
         message: "Which embedding model would you like to use?",
         choices: await getAvailableModelChoices(true, config.apiKey),
-        initial: 0,
       },
-      questionHandlers,
-    );
+    ]);
     config.embeddingModel = embeddingModel;
     config.dimensions = getDimensions(embeddingModel);
   }
@@ -141,7 +135,7 @@ async function getAvailableModelChoices(
       )
       .map((el: any) => {
         return {
-          title: el.id,
+          name: el.id,
           value: el.id,
         };
       });

helpers/providers/mistral.ts

@@ -1,6 +1,6 @@
-import prompts from "prompts";
+import inquirer from "inquirer";
 import { ModelConfigParams } from ".";
-import { questionHandlers, toChoice } from "../../questions/utils";
+import { toChoice } from "../../questions/utils";
 
 const MODELS = ["mistral-tiny", "mistral-small", "mistral-medium"];
 type ModelData = {
@@ -40,41 +40,36 @@ export async function askMistralQuestions({
   };
 
   if (!config.apiKey) {
-    const { key } = await prompts(
+    const { key } = await inquirer.prompt([
       {
-        type: "text",
+        type: "input",
         name: "key",
         message:
           "Please provide your Mistral API key (or leave blank to use MISTRAL_API_KEY env variable):",
       },
-      questionHandlers,
-    );
+    ]);
     config.apiKey = key || process.env.MISTRAL_API_KEY;
   }
 
   if (askModels) {
-    const { model } = await prompts(
+    const { model } = await inquirer.prompt([
       {
-        type: "select",
+        type: "list",
         name: "model",
         message: "Which LLM model would you like to use?",
         choices: MODELS.map(toChoice),
-        initial: 0,
       },
-      questionHandlers,
-    );
+    ]);
     config.model = model;
 
-    const { embeddingModel } = await prompts(
+    const { embeddingModel } = await inquirer.prompt([
       {
-        type: "select",
+        type: "list",
         name: "embeddingModel",
         message: "Which embedding model would you like to use?",
         choices: Object.keys(EMBEDDING_MODELS).map(toChoice),
-        initial: 0,
       },
-      questionHandlers,
-    );
+    ]);
     config.embeddingModel = embeddingModel;
     config.dimensions = EMBEDDING_MODELS[embeddingModel].dimensions;
   }

helpers/providers/ollama.ts

@@ -1,8 +1,8 @@
+import inquirer from "inquirer";
 import ollama, { type ModelResponse } from "ollama";
 import { red } from "picocolors";
-import prompts from "prompts";
 import { ModelConfigParams } from ".";
-import { questionHandlers, toChoice } from "../../questions/utils";
+import { toChoice } from "../../questions/utils";
 
 type ModelData = {
   dimensions: number;
@@ -34,29 +34,25 @@ export async function askOllamaQuestions({
   };
 
   if (askModels) {
-    const { model } = await prompts(
+    const { model } = await inquirer.prompt([
       {
-        type: "select",
+        type: "list",
         name: "model",
         message: "Which LLM model would you like to use?",
         choices: MODELS.map(toChoice),
-        initial: 0,
       },
-      questionHandlers,
-    );
+    ]);
     await ensureModel(model);
     config.model = model;
 
-    const { embeddingModel } = await prompts(
+    const { embeddingModel } = await inquirer.prompt([
       {
-        type: "select",
+        type: "list",
         name: "embeddingModel",
         message: "Which embedding model would you like to use?",
         choices: Object.keys(EMBEDDING_MODELS).map(toChoice),
-        initial: 0,
       },
-      questionHandlers,
-    );
+    ]);
     await ensureModel(embeddingModel);
     config.embeddingModel = embeddingModel;
     config.dimensions = EMBEDDING_MODELS[embeddingModel].dimensions;

helpers/providers/openai.ts

@@ -1,10 +1,9 @@
 import got from "got";
+import inquirer from "inquirer";
 import ora from "ora";
 import { red } from "picocolors";
-import prompts from "prompts";
 import { ModelConfigParams, ModelConfigQuestionsParams } from ".";
 import { isCI } from "../../questions";
-import { questionHandlers } from "../../questions/utils";
 
 const OPENAI_API_URL = "https://api.openai.com/v1";
 
@@ -32,9 +31,9 @@ export async function askOpenAIQuestions({
   };
 
   if (!config.apiKey && !isCI) {
-    const { key } = await prompts(
+    const { key } = await inquirer.prompt([
       {
-        type: "text",
+        type: "input",
         name: "key",
         message: askModels
           ? "Please provide your OpenAI API key (or leave blank to use OPENAI_API_KEY env variable):"
@@ -49,34 +48,29 @@ export async function askOpenAIQuestions({
           return true;
         },
       },
-      questionHandlers,
-    );
+    ]);
     config.apiKey = key || process.env.OPENAI_API_KEY;
   }
 
   if (askModels) {
-    const { model } = await prompts(
+    const { model } = await inquirer.prompt([
       {
-        type: "select",
+        type: "list",
         name: "model",
         message: "Which LLM model would you like to use?",
         choices: await getAvailableModelChoices(false, config.apiKey),
-        initial: 0,
       },
-      questionHandlers,
-    );
+    ]);
     config.model = model;
 
-    const { embeddingModel } = await prompts(
+    const { embeddingModel } = await inquirer.prompt([
       {
-        type: "select",
+        type: "list",
         name: "embeddingModel",
         message: "Which embedding model would you like to use?",
         choices: await getAvailableModelChoices(true, config.apiKey),
-        initial: 0,
       },
-      questionHandlers,
-    );
+    ]);
     config.embeddingModel = embeddingModel;
     config.dimensions = getDimensions(embeddingModel);
   }
@@ -116,7 +110,7 @@ async function getAvailableModelChoices(
       )
       .map((el: any) => {
         return {
-          title: el.id,
+          name: el.id,
           value: el.id,
         };
       });

index.ts

@@ -2,9 +2,9 @@
 import { execSync } from "child_process";
 import { Command } from "commander";
 import fs from "fs";
+import inquirer from "inquirer";
 import path from "path";
 import { bold, cyan, green, red, yellow } from "picocolors";
-import prompts from "prompts";
 import terminalLink from "terminal-link";
 import checkForUpdate from "update-check";
 import { createApp } from "./create-app";
@@ -18,7 +18,6 @@ import { validateNpmName } from "./helpers/validate-pkg";
 import packageJson from "./package.json";
 import { askQuestions } from "./questions/index";
 import { QuestionArgs } from "./questions/types";
-import { onPromptState } from "./questions/utils";
 // Run the initialization function
 initializeGlobalAgent();
 
@@ -156,12 +155,11 @@ const program = new Command(packageJson.name)
 
   Specify the tools you want to use by providing a comma-separated list. For example, 'wikipedia.WikipediaToolSpec,google.GoogleSearchToolSpec'. Use 'none' to not using any tools.
 `,
-    (tools, _) => {
-      if (tools === "none") {
+    (tools) => {
+      if (!tools || tools === "none") {
         return [];
-      } else {
-        return getTools(tools.split(","));
       }
+      return getTools(tools.split(","));
     },
   )
   .option(
@@ -263,24 +261,22 @@ async function run(): Promise<void> {
   }
 
   if (!projectPath) {
-    const res = await prompts({
-      onState: onPromptState,
-      type: "text",
-      name: "path",
-      message: "What is your project named?",
-      initial: "my-app",
-      validate: (name) => {
-        const validation = validateNpmName(path.basename(path.resolve(name)));
-        if (validation.valid) {
-          return true;
-        }
-        return "Invalid project name: " + validation.problems![0];
+    const { path: projectPathAnswer } = await inquirer.prompt([
+      {
+        type: "input",
+        name: "path",
+        message: "What is your project named?",
+        default: "my-app",
+        validate(name) {
+          const validation = validateNpmName(path.basename(path.resolve(name)));
+          if (validation.valid) {
+            return true;
+          }
+          return "Invalid project name" + validation.problems![0];
+        },
       },
-    });
-
-    if (typeof res.path === "string") {
-      projectPath = res.path.trim();
-    }
+    ]);
+    projectPath = projectPathAnswer;
   }
 
   if (!projectPath) {

package.json

@@ -43,7 +43,7 @@
     "@types/cross-spawn": "6.0.0",
     "@types/fs-extra": "11.0.4",
     "@types/node": "^20.11.7",
-    "@types/prompts": "2.4.2",
+    "@types/inquirer": "^9.0.7",
     "@types/tar": "6.1.5",
     "@types/validate-npm-package-name": "3.0.0",
     "async-retry": "1.3.1",
@@ -58,7 +58,7 @@
     "ollama": "^0.5.0",
     "ora": "^8.0.1",
     "picocolors": "1.0.0",
-    "prompts": "2.4.2",
+    "inquirer": "^9.2.14",
     "smol-toml": "^1.1.4",
     "tar": "6.1.15",
     "terminal-link": "^3.0.0",

pnpm-lock.yaml

@@ -20,12 +20,12 @@ importers:
       '@types/fs-extra':
         specifier: 11.0.4
         version: 11.0.4
+      '@types/inquirer':
+        specifier: ^9.0.7
+        version: 9.0.7
       '@types/node':
         specifier: ^20.11.7
         version: 20.12.10
-      '@types/prompts':
-        specifier: 2.4.2
-        version: 2.4.2
       '@types/tar':
         specifier: 6.1.5
         version: 6.1.5
@@ -59,6 +59,9 @@ importers:
       got:
         specifier: 10.7.0
         version: 10.7.0
+      inquirer:
+        specifier: ^9.2.14
+        version: 9.3.7
       ollama:
         specifier: ^0.5.0
         version: 0.5.0
@@ -68,9 +71,6 @@ importers:
       picocolors:
         specifier: 1.0.0
         version: 1.0.0
-      prompts:
-        specifier: 2.4.2
-        version: 2.4.2
       smol-toml:
         specifier: ^1.1.4
         version: 1.1.4
@@ -223,6 +223,10 @@ packages:
   '@humanwhocodes/object-schema@2.0.3':
     resolution: {integrity: sha512-93zYdMES/c1D69yZiKDBj0V24vqNzB/koF26KPaagAfd3P/4gUlh3Dys5ogAK+Exi9QyzlD8x/08Zt7wIKcDcA==}
 
+  '@inquirer/figures@1.0.9':
+    resolution: {integrity: sha512-BXvGj0ehzrngHTPTDqUoDT3NXL8U0RxUk2zJm2A66RhCEIWdtU1v6GuUqNAgArW4PQ9CinqIWyHdQgdwOj06zQ==}
+    engines: {node: '>=18'}
+
   '@isaacs/cliui@8.0.2':
     resolution: {integrity: sha512-O8jcjabXaleOG9DQ0+ARXWZBTfnP4WNAqzuiJK7ll44AmxGKv/J2M4TPjxjY3znBCfvBXFzucm1twdyFybFqEA==}
     engines: {node: '>=12'}
@@ -280,6 +284,9 @@ packages:
   '@types/http-cache-semantics@4.0.4':
     resolution: {integrity: sha512-1m0bIFVc7eJWyve9S0RnuRgcQqF/Xd5QsUZAZeQFr1Q3/p9JWoQQEqmVy+DPTNpGXwhgIetAoYF8JSc33q29QA==}
 
+  '@types/inquirer@9.0.7':
+    resolution: {integrity: sha512-Q0zyBupO6NxGRZut/JdmqYKOnN95Eg5V8Csg3PGKkP+FnvsUZx1jAyK7fztIszxxMuoBA6E3KXWvdZVXIpx60g==}
+
   '@types/jsonfile@6.1.4':
     resolution: {integrity: sha512-D5qGUYwjvnNNextdU59/+fI+spnwtTFmyQP0h+PfIOSkNfpU6AOICUOkm4i0OnSk+NyjdPJrxCDro0sJsWlRpQ==}
 
@@ -298,9 +305,6 @@ packages:
   '@types/normalize-package-data@2.4.4':
     resolution: {integrity: sha512-37i+OaWTh9qeK4LSHPsyRC7NahnGotNuZvjLSgcPzblpHB3rrCJxAOgI5gCdKm7coonsaX1Of0ILiTcnZjbfxA==}
 
-  '@types/prompts@2.4.2':
-    resolution: {integrity: sha512-TwNx7qsjvRIUv/BCx583tqF5IINEVjCNqg9ofKHRlSoUHE62WBHrem4B1HGXcIrG511v29d1kJ9a/t2Esz7MIg==}
-
   '@types/responselike@1.0.3':
     resolution: {integrity: sha512-H/+L+UkTV33uf49PH5pCAUBVPNj2nDBXTN+qS1dOwyyg24l3CcicicCA7ca+HMvJBZcFgl5r8e+RR6elsb4Lyw==}
 
@@ -313,6 +317,9 @@ packages:
   '@types/tar@6.1.5':
     resolution: {integrity: sha512-qm2I/RlZij5RofuY7vohTpYNaYcrSQlN2MyjucQc7ZweDwaEWkdN/EeNh6e9zjK6uEm6PwjdMXkcj05BxZdX1Q==}
 
+  '@types/through@0.0.33':
+    resolution: {integrity: sha512-HsJ+z3QuETzP3cswwtzt2vEIiHBk/dCcHGhbmG5X3ecnwFD/lPrMpliGXxSCg03L9AhrdwA4Oz/qfspkDW+xGQ==}
+
   '@types/validate-npm-package-name@3.0.0':
     resolution: {integrity: sha512-iFNNIrEaJH1lbPiyX+O/QyxSbKxrTjdNBVZGckt+iEL9So0hdZNBL68sOfHnt2txuUD8UJXvmKv/1DkgkebgUg==}
 
@@ -340,6 +347,10 @@ packages:
     resolution: {integrity: sha512-/6w/C21Pm1A7aZitlI5Ni/2J6FFQN8i1Cvz3kHABAAbw93v/NlvKdVOqz7CCWz/3iv/JplRSEEZ83XION15ovw==}
     engines: {node: '>=6'}
 
+  ansi-escapes@4.3.2:
+    resolution: {integrity: sha512-gKXj5ALrKWQLsYG9jlTRmR/xKluxHV+Z9QEwNIgCfM1/uwPMCuzVVnh5mwTd+OuBZcwSIMbqssNWRm1lE51QaQ==}
+    engines: {node: '>=8'}
+
   ansi-escapes@5.0.0:
     resolution: {integrity: sha512-5GFMVX8HqE/TB+FuBJGuO5XG0WrsA6ptUqoODaT/n9mmUaZFkqnBueB4leqGBCmrUHnCnC4PCZTCd0E7QQ83bA==}
     engines: {node: '>=12'}
@@ -403,10 +414,16 @@ packages:
   balanced-match@1.0.2:
     resolution: {integrity: sha512-3oSeUO0TMV67hN1AmbXsK4yaqU7tjiHlbxRDZOpH0KW9+CeX4bRAaX0Anxt0tx2MrpRpWwQaPwIlISEJhYU5Pw==}
 
+  base64-js@1.5.1:
+    resolution: {integrity: sha512-AKpaYlHn8t4SVbOHCy+b5+KKgvR4vrsD8vbvrbiQJps7fKDTkjkDry6ji0rUJjC0kzbNePLwzxq8iypo41qeWA==}
+
   better-path-resolve@1.0.0:
     resolution: {integrity: sha512-pbnl5XzGBdrFU/wT4jqmJVPn2B6UHPBOhzMQkY/SPUPB6QtUXtmBHBIwCbXJol93mOpGMnQyP/+BB19q04xj7g==}
     engines: {node: '>=4'}
 
+  bl@4.1.0:
+    resolution: {integrity: sha512-1W07cM9gS6DcLperZfFSj+bWLtaPGSOHWhPiGzXmvVJbRLdG82sH/Kn8EtW1VqWVA54AKf2h5k5BbnIbwF3h6w==}
+
   boolean@3.2.0:
     resolution: {integrity: sha512-d0II/GO9uf9lfUHH2BQsjxzRJZBdsjgsBiW4BvhWk/3qoKwQFjIDVN19PfX8F2D/r9PCMTtLWjYVCFrpeYUzsw==}
 
@@ -423,6 +440,9 @@ packages:
   breakword@1.0.6:
     resolution: {integrity: sha512-yjxDAYyK/pBvws9H4xKYpLDpYKEH6CzrBPAuXq3x18I+c/2MkVtT3qAr7Oloi6Dss9qNhPVueAAVU1CSeNDIXw==}
 
+  buffer@5.7.1:
+    resolution: {integrity: sha512-EHcyIPBQ4BSGlvjB16k5KgAJ27CIsHY/2JBmCRReo48y9rQ3MaUzWX3KVlBa4U7MyX02HdVj0K7C3WaB3ju7FQ==}
+
   builtins@1.0.3:
     resolution: {integrity: sha512-uYBjakWipfaO/bXI7E8rq6kpwHRZK5cNYrUv2OzZSI/FvmdMyXJ2tG9dKcjEC5YHmHpUAwsargWIZNWdxb/bnQ==}
 
@@ -477,6 +497,10 @@ packages:
     resolution: {tarball: https://codeload.github.com/watson/ci-info/tar.gz/f43f6a1cefff47fb361c88cf4b943fdbcaafe540}
     version: 2.0.0
 
+  cli-cursor@3.1.0:
+    resolution: {integrity: sha512-I/zHAwsKf9FqGoXM4WWRACob9+SNukZTd94DWF57E4toouRulbCxcUh6RKUEOQlYTHJnzkPMySvPNaaSLNfLZw==}
+    engines: {node: '>=8'}
+
   cli-cursor@4.0.0:
     resolution: {integrity: sha512-VGtlMu3x/4DOtIUwEkRezxUZ2lBacNJCHash0N0WeZDBS+7Ux1dm3XWAgWYxLJFMMdOeXMHXorshEFhbMSGelg==}
     engines: {node: ^12.20.0 || ^14.13.1 || >=16.0.0}
@@ -485,6 +509,10 @@ packages:
     resolution: {integrity: sha512-ywqV+5MmyL4E7ybXgKys4DugZbX0FC6LnwrhjuykIjnK9k8OQacQ7axGKnjDXWNhns0xot3bZI5h55H8yo9cJg==}
     engines: {node: '>=6'}
 
+  cli-width@4.1.0:
+    resolution: {integrity: sha512-ouuZd4/dm2Sw5Gmqy6bGyNNNe1qt9RpmxveLSO7KcgsTnU7RXfsw+/bukWGo1abgBiMAic068rclZsO4IWmmxQ==}
+    engines: {node: '>= 12'}
+
   cliui@6.0.0:
     resolution: {integrity: sha512-t6wbgtoCXvAzst7QgXxJYqPt0usEfbgQdftEPbLL/cvv6HPE5VgvqCuAIDR0NgU52ds6rFwqrgakNLrHEjCbrQ==}
 
@@ -934,6 +962,9 @@ packages:
     resolution: {integrity: sha512-v3MXnZAcvnywkTUEZomIActle7RXXeedOR31wwl7VlyoXO4Qi9arvSenNQWne1TcRwhCL1HwLI21bEqdpj8/rA==}
     engines: {node: '>=0.10.0'}
 
+  ieee754@1.2.1:
+    resolution: {integrity: sha512-dcyqhDvX1C46lXZcVqCpK+FtMRQVdIMN6/Df5js2zouUsqG7I6sFxitIC+7KYK29KdXOLHdu9zL4sFnoVQnqaA==}
+
   ignore@5.3.1:
     resolution: {integrity: sha512-5Fytz/IraMjqpwfd34ke28PTVMjZjJG2MPn5t7OE4eUCUNf8BAa7b5WUS9/Qvr6mwOQS7Mk6vdsMno5he+T8Xw==}
     engines: {node: '>= 4'}
@@ -959,6 +990,10 @@ packages:
   ini@1.3.8:
     resolution: {integrity: sha512-JV/yugV2uzW5iMRSiZAyDtQd+nxtUnjeLt0acNdw98kKLrvuRVyB80tsREOE7yvGVgalhZ6RNXCmEHkUKBKxew==}
 
+  inquirer@9.3.7:
+    resolution: {integrity: sha512-LJKFHCSeIRq9hanN14IlOtPSTe3lNES7TYDTE2xxdAy1LS5rYphajK1qtwvj3YmQXvvk0U2Vbmcni8P9EIQW9w==}
+    engines: {node: '>=18'}
+
   internal-slot@1.0.7:
     resolution: {integrity: sha512-NGnrKwXzSms2qUUih/ILZ5JBqNTSa1+ZmP6flaIp6KmSElgE9qdndzS3cqjrDovwFdmwsGsLdeFgB6suw+1e9g==}
     engines: {node: '>= 0.4'}
@@ -1004,6 +1039,10 @@ packages:
     resolution: {integrity: sha512-xelSayHH36ZgE7ZWhli7pW34hNbNl8Ojv5KVmkJD4hBdD3th8Tfk9vYasLM+mXWOZhFkgZfxhLSnrwRr4elSSg==}
     engines: {node: '>=0.10.0'}
 
+  is-interactive@1.0.0:
+    resolution: {integrity: sha512-2HvIEKRoqS62guEC+qBjpvRubdX910WCMuJTZ+I9yvqKU2/12eSL549HMwtabb4oupdj2sMP50k+XJfB/8JE6w==}
+    engines: {node: '>=8'}
+
   is-interactive@2.0.0:
     resolution: {integrity: sha512-qP1vozQRI+BMOPcjFzrjXuQvdak2pHNUMZoeG2eRbiSqyvbEf/wQtEOTOX1guk6E3t36RkaqiSt8A/6YElNxLQ==}
     engines: {node: '>=12'}
@@ -1052,6 +1091,10 @@ packages:
     resolution: {integrity: sha512-uZ25/bUAlUY5fR4OKT4rZQEBrzQWYV9ZJYGGsUmEJ6thodVJ1HX64ePQ6Z0qPWP+m+Uq6e9UugrE38jeYsDSMw==}
     engines: {node: '>= 0.4'}
 
+  is-unicode-supported@0.1.0:
+    resolution: {integrity: sha512-knxG2q4UC3u8stRGyAVJCOdxFmv5DZiRcdlIaAQXAbSfJya+OhopNotLQrstBhququ4ZpuKbDc/8S6mgXgPFPw==}
+    engines: {node: '>=10'}
+
   is-unicode-supported@1.3.0:
     resolution: {integrity: sha512-43r2mRvz+8JRIKnWJ+3j8JtjRKZ6GmjzfaE/qiBJnikNnYv/6bagRJ1kUhNk8R5EX/GkobD+r+sfxCPJsiKBLQ==}
     engines: {node: '>=12'}
@@ -1116,10 +1159,6 @@ packages:
     resolution: {integrity: sha512-dcS1ul+9tmeD95T+x28/ehLgd9mENa3LsvDTtzm3vyBEO7RPptvAD+t44WVXaUjTBRcrpFeFlC8WCruUR456hw==}
     engines: {node: '>=0.10.0'}
 
-  kleur@3.0.3:
-    resolution: {integrity: sha512-eTIzlVOSUR+JxdDFepEYcBMtZ9Qqdef+rnzWdRZuMbOywu5tO2w2N7rqjoANZ5k9vywhL6Br1VRjUIgTQx4E8w==}
-    engines: {node: '>=6'}
-
   kleur@4.1.5:
     resolution: {integrity: sha512-o+NO+8WrRiQEE4/7nwRJhN1HWpVmJm511pBHUxPLtp0BUISzlBplORYSmTclCnJvQq2tKu/sgl3xVpkc7ZWuQQ==}
     engines: {node: '>=6'}
@@ -1149,6 +1188,10 @@ packages:
   lodash.startcase@4.4.0:
     resolution: {integrity: sha512-+WKqsK294HMSc2jEbNgpHpd0JfIBhp7rEV4aqXWqFr6AlXov+SlcgB1Fv01y2kGe3Gc8nMW7VA0SrGuSkRfIEg==}
 
+  log-symbols@4.1.0:
+    resolution: {integrity: sha512-8XPvpAA8uyhfteu8pIvQxpJZ7SYYdpUivZpGy6sFsBuKRY/7rQGavedeB8aK+Zkyq6upMFVL/9AW6vOYzfRyLg==}
+    engines: {node: '>=10'}
+
   log-symbols@6.0.0:
     resolution: {integrity: sha512-i24m8rpwhmPIS4zscNzK6MSEhk0DUWa/8iYQWxhffV8jkI4Phvs3F+quL5xvS0gdQR0FyTCMMH33Y78dDTzzIw==}
     engines: {node: '>=18'}
@@ -1250,6 +1293,10 @@ packages:
   ms@2.1.2:
     resolution: {integrity: sha512-sGkPx+VjMtmA6MX27oA4FBFELFCZZ4S4XqeGOXCv68tT+jb3vk/RyaKWP0PTKyWtmLSM0b+adUTEvbs1PEaH2w==}
 
+  mute-stream@1.0.0:
+    resolution: {integrity: sha512-avsJQhyd+680gKXyG/sQc0nXaC6rBkPOfyHYcFb9+hdkqQkR9bdnkJ0AMZhke0oesPqIO+mFFJ+IdBc7mst4IA==}
+    engines: {node: ^14.17.0 || ^16.13.0 || >=18.0.0}
+
   natural-compare@1.4.0:
     resolution: {integrity: sha512-OWND8ei3VtNC9h7V60qff3SVobHr996CTwgxubgyQYEpg290h9J0buyECNNJexkFm5sOajh5G116RYA1c8ZMSw==}
 
@@ -1285,6 +1332,10 @@ packages:
     resolution: {integrity: sha512-6IpQ7mKUxRcZNLIObR0hz7lxsapSSIYNZJwXPGeF0mTVqGKFIXj1DQcMoT22S3ROcLyY/rz0PWaWZ9ayWmad9g==}
     engines: {node: '>= 0.8.0'}
 
+  ora@5.4.1:
+    resolution: {integrity: sha512-5b6Y85tPxZZ7QytO+BQzysW31HJku27cRIlkbAXaNx+BdcVi+LlRFmVXzeF6a7JCwJpyw5c4b+YSVImQIrBpuQ==}
+    engines: {node: '>=10'}
+
   ora@8.0.1:
     resolution: {integrity: sha512-ANIvzobt1rls2BDny5fWZ3ZVKyD6nscLvfFRpQgfWsythlcsVUC9kL0zq6j2Z5z9wwp1kd7wpsD/T9qNPVLCaQ==}
     engines: {node: '>=18'}
@@ -1431,10 +1482,6 @@ packages:
     engines: {node: '>=14'}
     hasBin: true
 
-  prompts@2.4.2:
-    resolution: {integrity: sha512-NxNv/kLguCA7p3jE8oL2aEBsrJWgAakBpgmgK6lpPWV+WuOmY6r2/zbAVnP+T8bQlA0nzHXSJSJW0Hq7ylaD2Q==}
-    engines: {node: '>= 6'}
-
   pseudomap@1.0.2:
     resolution: {integrity: sha512-b/YwNhb8lk1Zz2+bXXpS/LK9OisiZZ1SNsSLxN1x2OXVEhW2Ckr/7mWE5vrC1ZTiJlD9g19jWszTmJsB+oEpFQ==}
 
@@ -1468,6 +1515,10 @@ packages:
     resolution: {integrity: sha512-VIMnQi/Z4HT2Fxuwg5KrY174U1VdUIASQVWXXyqtNRtxSr9IYkn1rsI6Tb6HsrHCmB7gVpNwX6JxPTHcH6IoTA==}
     engines: {node: '>=6'}
 
+  readable-stream@3.6.2:
+    resolution: {integrity: sha512-9u/sniCrY3D5WdsERHzHE4G2YCXqoG5FTHUiCC4SIbr6XcLZBY05ya9EKjYek9O5xOAwjGq+1JdGBAS7Q9ScoA==}
+    engines: {node: '>= 6'}
+
   redent@3.0.0:
     resolution: {integrity: sha512-6tDA8g98We0zd0GvVeMT9arEOnTw9qM03L9cJXaCjrip1OO764RDBLBfrB4cwzNGDj5OA5ioymC9GkizgWJDUg==}
     engines: {node: '>=8'}
@@ -1508,6 +1559,10 @@ packages:
   responselike@2.0.1:
     resolution: {integrity: sha512-4gl03wn3hj1HP3yzgdI7d3lCkF95F21Pz4BPGvKHinyQzALR5CapwC8yIi0Rh58DEMQ/SguC03wFj2k0M/mHhw==}
 
+  restore-cursor@3.1.0:
+    resolution: {integrity: sha512-l+sSefzHpj5qimhFSE5a8nufZYAM3sBSVMAPtYkmC+4EH2anSGaEMXSD0izRQbu9nfyQ9y5JrVmp7E8oZrUjvA==}
+    engines: {node: '>=8'}
+
   restore-cursor@4.0.0:
     resolution: {integrity: sha512-I9fPXU9geO9bHOt9pHHOhOkYerIMsmVaWB0rA2AI9ERh/+x/i7MV5HKBNrg+ljO5eoPVgCcnFuRjJ9uH6I/3eg==}
     engines: {node: ^12.20.0 || ^14.13.1 || >=16.0.0}
@@ -1533,9 +1588,16 @@ packages:
     resolution: {integrity: sha512-CHhPh+UNHD2GTXNYhPWLnU8ONHdI+5DI+4EYIAOaiD63rHeYlZvyh8P+in5999TTSFgUYuKUAjzRI4mdh/p+2A==}
     engines: {node: '>=8.0'}
 
+  run-async@3.0.0:
+    resolution: {integrity: sha512-540WwVDOMxA6dN6We19EcT9sc3hkXPw5mzRNGM3FkdN/vtE9NFvj5lFAPNwUDmJjXidm3v7TC1cTE7t17Ulm1Q==}
+    engines: {node: '>=0.12.0'}
+
   run-parallel@1.2.0:
     resolution: {integrity: sha512-5l4VyZR86LZ/lDxZTR6jqL8AFE2S0IFLMP26AbjsLVADxHdhB/c0GUsH+y39UfCi3dzz8OlQuPmnaJOMoDHQBA==}
 
+  rxjs@7.8.1:
+    resolution: {integrity: sha512-AA3TVj+0A2iuIoQkWEK/tqFjBq2j+6PO6Y0zJcvzLAFhEFIO3HL0vls9hWLncZbAAbK0mar7oZ4V079I/qPMxg==}
+
   safe-array-concat@1.1.2:
     resolution: {integrity: sha512-vj6RsCsWBCf19jIeHEfkRMw8DPiBb+DMXklQ/1SGDHOMlHdPUkZXFQ2YdplS23zESTijAcurb1aSgJA3AgMu1Q==}
     engines: {node: '>=0.4'}
@@ -1604,9 +1666,6 @@ packages:
     resolution: {integrity: sha512-bzyZ1e88w9O1iNJbKnOlvYTrWPDl46O1bG0D3XInv+9tkPrxrN8jUUTiFlDkkmKWgn1M6CfIA13SuGqOa9Korw==}
     engines: {node: '>=14'}
 
-  sisteransi@1.0.5:
-    resolution: {integrity: sha512-bLGGlR1QxBcynn2d5YmDX4MGjlZvy2MRBDRNHLJ8VI6l6+9FUiyTFNJ0IveOSP0bcXgVDPRcfGqA0pjaqUpfVg==}
-
   slash@3.0.0:
     resolution: {integrity: sha512-g9Q1haeby36OSStwb4ntCGGGaKsaVSjQ68fBxoQcutl5fS1vuY18H3wSt3jFyFtrkx+Kz0V1G85A4MyAdDMi2Q==}
     engines: {node: '>=8'}
@@ -1671,6 +1730,9 @@ packages:
     resolution: {integrity: sha512-UXSH262CSZY1tfu3G3Secr6uGLCFVPMhIqHjlgCUtCCcgihYc/xKs9djMTMUOb2j1mVSeU8EU6NWc/iQKU6Gfg==}
     engines: {node: '>= 0.4'}
 
+  string_decoder@1.3.0:
+    resolution: {integrity: sha512-hkRX8U1WjJFd8LsDJ2yQ/wWWxaopEsABU1XfkM8A+j0+85JAGppt16cr1Whg6KIbb4okU6Mql6BOj+uup/wKeA==}
+
   strip-ansi@6.0.1:
     resolution: {integrity: sha512-Y38VPSHcqkFrCpFnQ9vuSXmquuv5oXOKpGeT6aGrr3o3Gc9AlVa6JBfUSOCnbxGGZF+/0ooI7KrPuUSztUdU5A==}
     engines: {node: '>=8'}
@@ -1742,6 +1804,9 @@ packages:
     resolution: {integrity: sha512-c1PTsA3tYrIsLGkJkzHF+w9F2EyxfXGo4UyJc4pFL++FMjnq0HJS69T3M7d//gKrFKwy429bouPescbjecU+Zw==}
     engines: {node: '>=8'}
 
+  tslib@2.8.1:
+    resolution: {integrity: sha512-oJFu94HQb+KVduSUQL7wnpmqnfmLsOA/nAh6b6EH0wCEoK0/mPeXU6c3wKDV83MkOuHPRHtSXKKU99IBazS/2w==}
+
   tty-table@4.2.3:
     resolution: {integrity: sha512-Fs15mu0vGzCrj8fmJNP7Ynxt5J7praPXqFN0leZeZBXJwkMxv9cb2D454k1ltrtUSJbZ4yH4e0CynsHLxmUfFA==}
     engines: {node: '>=8.0.0'}
@@ -1763,6 +1828,10 @@ packages:
     resolution: {integrity: sha512-Ne+eE4r0/iWnpAxD852z3A+N0Bt5RN//NjJwRd2VFHEmrywxf5vsZlh4R6lixl6B+wz/8d+maTSAkN1FIkI3LQ==}
     engines: {node: '>=10'}
 
+  type-fest@0.21.3:
+    resolution: {integrity: sha512-t0rzBq87m3fVcduHDUFhKmyyX+9eo6WQjZvf51Ea/M0Q7+T374Jp1aUiyUl0GKxp8M/OETVHSDvmkyPgvX+X2w==}
+    engines: {node: '>=10'}
+
   type-fest@0.6.0:
     resolution: {integrity: sha512-q+MB8nYR1KDLrgr4G5yemftpMC7/QLqVndBmEEdqzmNj5dcFOO4Oo8qlwZE3ULT3+Zim1F8Kq4cBnikNhlCMlg==}
     engines: {node: '>=8'}
@@ -1816,6 +1885,9 @@ packages:
   uri-js@4.4.1:
     resolution: {integrity: sha512-7rKUyy33Q1yc98pQ1DAmLtwX109F7TIfWlW1Ydo8Wl1ii1SeHieeh0HHfPeL2fMXK6z0s8ecKs9frCuLJvndBg==}
 
+  util-deprecate@1.0.2:
+    resolution: {integrity: sha512-EPD5q1uXyFxJpCrLnCc1nHnq3gOa6DZBocAIiI2TaSCA7VCJ1UJDMagCzIkXNsUYfD1daK//LTEQ8xiIbrHtcw==}
+
   validate-npm-package-license@3.0.4:
     resolution: {integrity: sha512-DpKm2Ui/xN7/HQKCtpZxoRWBhZ9Z0kqtygG8XCgNQ8ZlDnxuQmWhj566j8fN4Cu3/JmbhsDo7fcAJq4s9h27Ew==}
 
@@ -1913,6 +1985,10 @@ packages:
     resolution: {integrity: sha512-rVksvsnNCdJ/ohGc6xgPwyN8eheCxsiLM8mxuE/t/mOVqJewPuO1miLpTHQiRgTKCLexL4MeAFVagts7HmNZ2Q==}
     engines: {node: '>=10'}
 
+  yoctocolors-cjs@2.1.2:
+    resolution: {integrity: sha512-cYVsTjKl8b+FrnidjibDWskAv7UKOfcwaVZdp/it9n1s9fU3IkgDbhdIRKCW4JDsAlECJY0ytoVPT3sK6kideA==}
+    engines: {node: '>=18'}
+
 snapshots:
 
   '@babel/code-frame@7.24.2':
@@ -2116,6 +2192,8 @@ snapshots:
 
   '@humanwhocodes/object-schema@2.0.3': {}
 
+  '@inquirer/figures@1.0.9': {}
+
   '@isaacs/cliui@8.0.2':
     dependencies:
       string-width: 5.1.2
@@ -2190,6 +2268,11 @@ snapshots:
 
   '@types/http-cache-semantics@4.0.4': {}
 
+  '@types/inquirer@9.0.7':
+    dependencies:
+      '@types/through': 0.0.33
+      rxjs: 7.8.1
+
   '@types/jsonfile@6.1.4':
     dependencies:
       '@types/node': 20.12.10
@@ -2208,11 +2291,6 @@ snapshots:
 
   '@types/normalize-package-data@2.4.4': {}
 
-  '@types/prompts@2.4.2':
-    dependencies:
-      '@types/node': 20.12.10
-      kleur: 3.0.3
-
   '@types/responselike@1.0.3':
     dependencies:
       '@types/node': 20.12.10
@@ -2226,6 +2304,10 @@ snapshots:
       '@types/node': 20.12.10
       minipass: 4.2.8
 
+  '@types/through@0.0.33':
+    dependencies:
+      '@types/node': 20.12.10
+
   '@types/validate-npm-package-name@3.0.0': {}
 
   '@ungap/structured-clone@1.2.0': {}
@@ -2247,6 +2329,10 @@ snapshots:
 
   ansi-colors@4.1.3: {}
 
+  ansi-escapes@4.3.2:
+    dependencies:
+      type-fest: 0.21.3
+
   ansi-escapes@5.0.0:
     dependencies:
       type-fest: 1.4.0
@@ -2310,10 +2396,18 @@ snapshots:
 
   balanced-match@1.0.2: {}
 
+  base64-js@1.5.1: {}
+
   better-path-resolve@1.0.0:
     dependencies:
       is-windows: 1.0.2
 
+  bl@4.1.0:
+    dependencies:
+      buffer: 5.7.1
+      inherits: 2.0.4
+      readable-stream: 3.6.2
+
   boolean@3.2.0: {}
 
   brace-expansion@1.1.11:
@@ -2333,6 +2427,11 @@ snapshots:
     dependencies:
       wcwidth: 1.0.1
 
+  buffer@5.7.1:
+    dependencies:
+      base64-js: 1.5.1
+      ieee754: 1.2.1
+
   builtins@1.0.3: {}
 
   cacheable-lookup@2.0.1:
@@ -2389,12 +2488,18 @@ snapshots:
 
   ci-info@https://codeload.github.com/watson/ci-info/tar.gz/f43f6a1cefff47fb361c88cf4b943fdbcaafe540: {}
 
+  cli-cursor@3.1.0:
+    dependencies:
+      restore-cursor: 3.1.0
+
   cli-cursor@4.0.0:
     dependencies:
       restore-cursor: 4.0.0
 
   cli-spinners@2.9.2: {}
 
+  cli-width@4.1.0: {}
+
   cliui@6.0.0:
     dependencies:
       string-width: 4.2.3
@@ -2947,6 +3052,8 @@ snapshots:
     dependencies:
       safer-buffer: 2.1.2
 
+  ieee754@1.2.1: {}
+
   ignore@5.3.1: {}
 
   import-fresh@3.3.0:
@@ -2967,6 +3074,21 @@ snapshots:
 
   ini@1.3.8: {}
 
+  inquirer@9.3.7:
+    dependencies:
+      '@inquirer/figures': 1.0.9
+      ansi-escapes: 4.3.2
+      cli-width: 4.1.0
+      external-editor: 3.1.0
+      mute-stream: 1.0.0
+      ora: 5.4.1
+      run-async: 3.0.0
+      rxjs: 7.8.1
+      string-width: 4.2.3
+      strip-ansi: 6.0.1
+      wrap-ansi: 6.2.0
+      yoctocolors-cjs: 2.1.2
+
   internal-slot@1.0.7:
     dependencies:
       es-errors: 1.3.0
@@ -3011,6 +3133,8 @@ snapshots:
     dependencies:
       is-extglob: 2.1.1
 
+  is-interactive@1.0.0: {}
+
   is-interactive@2.0.0: {}
 
   is-negative-zero@2.0.3: {}
@@ -3050,6 +3174,8 @@ snapshots:
     dependencies:
       which-typed-array: 1.1.15
 
+  is-unicode-supported@0.1.0: {}
+
   is-unicode-supported@1.3.0: {}
 
   is-unicode-supported@2.0.0: {}
@@ -3107,8 +3233,6 @@ snapshots:
 
   kind-of@6.0.3: {}
 
-  kleur@3.0.3: {}
-
   kleur@4.1.5: {}
 
   levn@0.4.1:
@@ -3137,6 +3261,11 @@ snapshots:
 
   lodash.startcase@4.4.0: {}
 
+  log-symbols@4.1.0:
+    dependencies:
+      chalk: 4.1.2
+      is-unicode-supported: 0.1.0
+
   log-symbols@6.0.0:
     dependencies:
       chalk: 5.3.0
@@ -3225,6 +3354,8 @@ snapshots:
 
   ms@2.1.2: {}
 
+  mute-stream@1.0.0: {}
+
   natural-compare@1.4.0: {}
 
   normalize-package-data@2.5.0:
@@ -3268,6 +3399,18 @@ snapshots:
       type-check: 0.4.0
       word-wrap: 1.2.5
 
+  ora@5.4.1:
+    dependencies:
+      bl: 4.1.0
+      chalk: 4.1.2
+      cli-cursor: 3.1.0
+      cli-spinners: 2.9.2
+      is-interactive: 1.0.0
+      is-unicode-supported: 0.1.0
+      log-symbols: 4.1.0
+      strip-ansi: 6.0.1
+      wcwidth: 1.0.1
+
   ora@8.0.1:
     dependencies:
       chalk: 5.3.0
@@ -3384,11 +3527,6 @@ snapshots:
 
   prettier@3.2.5: {}
 
-  prompts@2.4.2:
-    dependencies:
-      kleur: 3.0.3
-      sisteransi: 1.0.5
-
   pseudomap@1.0.2: {}
 
   pump@3.0.0:
@@ -3429,6 +3567,12 @@ snapshots:
       pify: 4.0.1
       strip-bom: 3.0.0
 
+  readable-stream@3.6.2:
+    dependencies:
+      inherits: 2.0.4
+      string_decoder: 1.3.0
+      util-deprecate: 1.0.2
+
   redent@3.0.0:
     dependencies:
       indent-string: 4.0.0
@@ -3470,6 +3614,11 @@ snapshots:
     dependencies:
       lowercase-keys: 2.0.0
 
+  restore-cursor@3.1.0:
+    dependencies:
+      onetime: 5.1.2
+      signal-exit: 3.0.7
+
   restore-cursor@4.0.0:
     dependencies:
       onetime: 5.1.2
@@ -3496,10 +3645,16 @@ snapshots:
       semver-compare: 1.0.0
       sprintf-js: 1.1.3
 
+  run-async@3.0.0: {}
+
   run-parallel@1.2.0:
     dependencies:
       queue-microtask: 1.2.3
 
+  rxjs@7.8.1:
+    dependencies:
+      tslib: 2.8.1
+
   safe-array-concat@1.1.2:
     dependencies:
       call-bind: 1.0.7
@@ -3568,8 +3723,6 @@ snapshots:
 
   signal-exit@4.1.0: {}
 
-  sisteransi@1.0.5: {}
-
   slash@3.0.0: {}
 
   smartwrap@2.0.2:
@@ -3649,6 +3802,10 @@ snapshots:
       define-properties: 1.2.1
       es-object-atoms: 1.0.0
 
+  string_decoder@1.3.0:
+    dependencies:
+      safe-buffer: 5.2.1
+
   strip-ansi@6.0.1:
     dependencies:
       ansi-regex: 5.0.1
@@ -3712,6 +3869,8 @@ snapshots:
 
   trim-newlines@3.0.1: {}
 
+  tslib@2.8.1: {}
+
   tty-table@4.2.3:
     dependencies:
       chalk: 4.1.2
@@ -3732,6 +3891,8 @@ snapshots:
 
   type-fest@0.20.2: {}
 
+  type-fest@0.21.3: {}
+
   type-fest@0.6.0: {}
 
   type-fest@0.8.1: {}
@@ -3794,6 +3955,8 @@ snapshots:
     dependencies:
       punycode: 2.3.1
 
+  util-deprecate@1.0.2: {}
+
   validate-npm-package-license@3.0.4:
     dependencies:
       spdx-correct: 3.2.0
@@ -3912,3 +4075,5 @@ snapshots:
       yargs-parser: 21.1.1
 
   yocto-queue@0.1.0: {}
+
+  yoctocolors-cjs@2.1.2: {}

questions/questions.ts

@@ -1,5 +1,5 @@
+import inquirer, { QuestionCollection } from "inquirer";
 import { blue } from "picocolors";
-import prompts from "prompts";
 import { isCI } from ".";
 import { COMMUNITY_OWNER, COMMUNITY_REPO } from "../helpers/constant";
 import { EXAMPLE_FILE, EXAMPLE_GDPR } from "../helpers/datasources";
@@ -10,43 +10,36 @@ import { supportedTools, toolRequiresConfig } from "../helpers/tools";
 import { getDataSourceChoices } from "./datasources";
 import { getVectorDbChoices } from "./stores";
 import { QuestionArgs } from "./types";
-import {
-  askPostInstallAction,
-  onPromptState,
-  questionHandlers,
-  selectLocalContextData,
-} from "./utils";
+import { askPostInstallAction, selectLocalContextData } from "./utils";
 
 export const askProQuestions = async (program: QuestionArgs) => {
   if (!program.template) {
     const styledRepo = blue(
       `https://github.com/${COMMUNITY_OWNER}/${COMMUNITY_REPO}`,
     );
-    const { template } = await prompts(
+    const { template } = await inquirer.prompt([
       {
-        type: "select",
+        type: "list",
         name: "template",
         message: "Which template would you like to use?",
         choices: [
-          { title: "Agentic RAG (e.g. chat with docs)", value: "streaming" },
+          { name: "Agentic RAG (e.g. chat with docs)", value: "streaming" },
           {
-            title: "Multi-agent app (using workflows)",
+            name: "Multi-agent app (using workflows)",
             value: "multiagent",
           },
-          { title: "Fullstack python template with Reflex", value: "reflex" },
+          { name: "Fullstack python template with Reflex", value: "reflex" },
           {
-            title: `Community template from ${styledRepo}`,
+            name: `Community template from ${styledRepo}`,
             value: "community",
           },
           {
-            title: "Example using a LlamaPack",
+            name: "Example using a LlamaPack",
             value: "llamapack",
           },
         ],
-        initial: 0,
       },
-      questionHandlers,
-    );
+    ]);
     program.template = template;
   }
 
@@ -55,19 +48,17 @@ export const askProQuestions = async (program: QuestionArgs) => {
       COMMUNITY_OWNER,
       COMMUNITY_REPO,
     );
-    const { communityProjectConfig } = await prompts(
+    const { communityProjectConfig } = await inquirer.prompt([
       {
-        type: "select",
+        type: "list",
         name: "communityProjectConfig",
         message: "Select community template",
         choices: projectOptions.map(({ title, value }) => ({
-          title,
+          name: title,
           value: JSON.stringify(value), // serialize value to string in terminal
         })),
-        initial: 0,
       },
-      questionHandlers,
-    );
+    ]);
     const projectConfig = JSON.parse(communityProjectConfig);
     program.communityProjectConfig = projectConfig;
     return; // early return - no further questions needed for community projects
@@ -75,19 +66,17 @@ export const askProQuestions = async (program: QuestionArgs) => {
 
   if (program.template === "llamapack") {
     const availableLlamaPacks = await getAvailableLlamapackOptions();
-    const { llamapack } = await prompts(
+    const { llamapack } = await inquirer.prompt([
       {
-        type: "select",
+        type: "list",
         name: "llamapack",
         message: "Select LlamaPack",
         choices: availableLlamaPacks.map((pack) => ({
-          title: pack.name,
+          name: pack.name,
           value: pack.folderPath,
         })),
-        initial: 0,
       },
-      questionHandlers,
-    );
+    ]);
     program.llamapack = llamapack;
     if (!program.postInstallAction) {
       program.postInstallAction = await askPostInstallAction(program);
@@ -101,42 +90,38 @@ export const askProQuestions = async (program: QuestionArgs) => {
     program.dataSources = [EXAMPLE_FILE];
     program.framework = "fastapi";
     // Ask for which Reflex use case to use
-    const { useCase } = await prompts(
+    const { useCase } = await inquirer.prompt([
       {
-        type: "select",
+        type: "list",
         name: "useCase",
         message: "Which use case would you like to build?",
         choices: [
-          { title: "Structured Extractor", value: "extractor" },
+          { name: "Structured Extractor", value: "extractor" },
           {
-            title: "Contract review (using Workflow)",
+            name: "Contract review (using Workflow)",
             value: "contract_review",
           },
         ],
-        initial: 0,
       },
-      questionHandlers,
-    );
+    ]);
     program.useCase = useCase;
   }
 
   if (!program.framework) {
     const choices = [
-      { title: "NextJS", value: "nextjs" },
-      { title: "Express", value: "express" },
-      { title: "FastAPI (Python)", value: "fastapi" },
+      { name: "NextJS", value: "nextjs" },
+      { name: "Express", value: "express" },
+      { name: "FastAPI (Python)", value: "fastapi" },
     ];
 
-    const { framework } = await prompts(
+    const { framework } = await inquirer.prompt([
       {
-        type: "select",
+        type: "list",
         name: "framework",
         message: "Which framework would you like to use?",
         choices,
-        initial: 0,
       },
-      questionHandlers,
-    );
+    ]);
     program.framework = framework;
   }
 
@@ -147,16 +132,15 @@ export const askProQuestions = async (program: QuestionArgs) => {
     // if a backend-only framework is selected, ask whether we should create a frontend
     if (program.frontend === undefined) {
       const styledNextJS = blue("NextJS");
-      const { frontend } = await prompts({
-        onState: onPromptState,
-        type: "toggle",
-        name: "frontend",
-        message: `Would you like to generate a ${styledNextJS} frontend for your FastAPI backend?`,
-        initial: false,
-        active: "Yes",
-        inactive: "No",
-      });
-      program.frontend = Boolean(frontend);
+      const { frontend } = await inquirer.prompt([
+        {
+          type: "confirm",
+          name: "frontend",
+          message: `Would you like to generate a ${styledNextJS} frontend for your FastAPI backend?`,
+          default: false,
+        },
+      ]);
+      program.frontend = frontend;
     }
   } else {
     program.frontend = false;
@@ -169,23 +153,20 @@ export const askProQuestions = async (program: QuestionArgs) => {
   }
 
   if (!program.observability && program.template === "streaming") {
-    const { observability } = await prompts(
+    const { observability } = await inquirer.prompt([
       {
-        type: "select",
+        type: "list",
         name: "observability",
         message: "Would you like to set up observability?",
         choices: [
-          { title: "No", value: "none" },
+          { name: "No", value: "none" },
           ...(program.framework === "fastapi"
-            ? [{ title: "LlamaTrace", value: "llamatrace" }]
+            ? [{ name: "LlamaTrace", value: "llamatrace" }]
             : []),
-          { title: "Traceloop", value: "traceloop" },
+          { name: "Traceloop", value: "traceloop" },
         ],
-        initial: 0,
       },
-      questionHandlers,
-    );
-
+    ]);
     program.observability = observability;
   }
 
@@ -196,34 +177,32 @@ export const askProQuestions = async (program: QuestionArgs) => {
     const choices =
       program.template === "reflex"
         ? [
-            { title: "Structured Extractor", value: "extractor" },
+            { name: "Structured Extractor", value: "extractor" },
             {
-              title: "Contract review (using Workflow)",
+              name: "Contract review (using Workflow)",
               value: "contract_review",
             },
           ]
         : [
             {
-              title: "Financial report (generate a financial report)",
+              name: "Financial report (generate a financial report)",
               value: "financial_report",
             },
             {
-              title: "Form filling (fill missing value in a CSV file)",
+              name: "Form filling (fill missing value in a CSV file)",
               value: "form_filling",
             },
-            { title: "Blog writer (Write a blog post)", value: "blog" },
+            { name: "Blog writer (Write a blog post)", value: "blog" },
           ];
 
-    const { useCase } = await prompts(
+    const { useCase } = await inquirer.prompt([
       {
-        type: "select",
+        type: "list",
         name: "useCase",
         message: "Which use case would you like to use?",
         choices,
-        initial: 0,
       },
-      questionHandlers,
-    );
+    ]);
     program.useCase = useCase;
   }
 
@@ -245,16 +224,14 @@ export const askProQuestions = async (program: QuestionArgs) => {
   }
 
   if (!program.vectorDb) {
-    const { vectorDb } = await prompts(
+    const { vectorDb } = await inquirer.prompt([
       {
-        type: "select",
+        type: "list",
         name: "vectorDb",
         message: "Would you like to use a vector database?",
         choices: getVectorDbChoices(program.framework),
-        initial: 0,
       },
-      questionHandlers,
-    );
+    ]);
     program.vectorDb = vectorDb;
   }
 
@@ -274,18 +251,16 @@ export const askProQuestions = async (program: QuestionArgs) => {
         program.template,
       );
       if (choices.length === 0) break;
-      const { selectedSource } = await prompts(
+      const { selectedSource } = await inquirer.prompt([
         {
-          type: "select",
+          type: "list",
           name: "selectedSource",
           message: firstQuestion
             ? "Which data source would you like to use?"
             : "Would you like to add another data source?",
           choices,
-          initial: firstQuestion ? 1 : 0,
         },
-        questionHandlers,
-      );
+      ]);
 
       if (selectedSource === "no" || selectedSource === "none") {
         // user doesn't want another data source or any data source
@@ -310,12 +285,12 @@ export const askProQuestions = async (program: QuestionArgs) => {
           break;
         }
         case "web": {
-          const { baseUrl } = await prompts(
+          const { baseUrl } = await inquirer.prompt([
             {
-              type: "text",
+              type: "input",
               name: "baseUrl",
               message: "Please provide base URL of the website: ",
-              initial: "https://www.llamaindex.ai",
+              default: "https://www.llamaindex.ai",
               validate: (value: string) => {
                 if (!value.includes("://")) {
                   value = `https://${value}`;
@@ -330,8 +305,7 @@ export const askProQuestions = async (program: QuestionArgs) => {
                 return true;
               },
             },
-            questionHandlers,
-          );
+          ]);
 
           program.dataSources.push({
             type: "web",
@@ -344,13 +318,13 @@ export const askProQuestions = async (program: QuestionArgs) => {
           break;
         }
         case "db": {
-          const dbPrompts: prompts.PromptObject<string>[] = [
+          const dbPrompts: QuestionCollection[] = [
             {
-              type: "text",
+              type: "input",
               name: "uri",
               message:
                 "Please enter the connection string (URI) for the database.",
-              initial: "mysql+pymysql://user:pass@localhost:3306/mydb",
+              default: "mysql+pymysql://user:pass@localhost:3306/mydb",
               validate: (value: string) => {
                 if (!value) {
                   return "Please provide a valid connection string";
@@ -365,17 +339,17 @@ export const askProQuestions = async (program: QuestionArgs) => {
                 return true;
               },
             },
-            // Only ask for a query, user can provide more complex queries in the config file later
             {
-              type: (prev) => (prev ? "text" : null),
+              type: "input",
               name: "queries",
               message: "Please enter the SQL query to fetch data:",
-              initial: "SELECT * FROM mytable",
+              default: "SELECT * FROM mytable",
+              when: (answers: any) => !!answers.uri,
             },
           ];
           program.dataSources.push({
             type: "db",
-            config: await prompts(dbPrompts, questionHandlers),
+            config: await inquirer.prompt(dbPrompts),
           });
           break;
         }
@@ -394,18 +368,15 @@ export const askProQuestions = async (program: QuestionArgs) => {
     if (program.useLlamaParse === undefined && program.template !== "reflex") {
       // if already set useLlamaParse, don't ask again
       if (program.dataSources.some((ds) => ds.type === "file")) {
-        const { useLlamaParse } = await prompts(
+        const { useLlamaParse } = await inquirer.prompt([
           {
-            type: "toggle",
+            type: "confirm",
             name: "useLlamaParse",
             message:
               "Would you like to use LlamaParse (improved parser for RAG - requires API key)?",
-            initial: false,
-            active: "Yes",
-            inactive: "No",
+            default: false,
           },
-          questionHandlers,
-        );
+        ]);
         program.useLlamaParse = useLlamaParse;
       }
     }
@@ -416,15 +387,14 @@ export const askProQuestions = async (program: QuestionArgs) => {
     if (!program.llamaCloudKey && !isCI) {
       // if already set, don't ask again
       // Ask for LlamaCloud API key
-      const { llamaCloudKey } = await prompts(
+      const { llamaCloudKey } = await inquirer.prompt([
         {
-          type: "text",
+          type: "input",
           name: "llamaCloudKey",
           message:
             "Please provide your LlamaCloud API key (leave blank to skip):",
         },
-        questionHandlers,
-      );
+      ]);
       program.llamaCloudKey = llamaCloudKey || process.env.LLAMA_CLOUD_API_KEY;
     }
   }
@@ -437,16 +407,18 @@ export const askProQuestions = async (program: QuestionArgs) => {
       t.supportedFrameworks?.includes(program.framework),
     );
     const toolChoices = options.map((tool) => ({
-      title: `${tool.display}${toolRequiresConfig(tool) ? " (needs configuration)" : ""}`,
+      name: `${tool.display}${toolRequiresConfig(tool) ? " (needs configuration)" : ""}`,
       value: tool.name,
     }));
-    const { toolsName } = await prompts({
-      type: "multiselect",
-      name: "toolsName",
-      message:
-        "Would you like to build an agent using tools? If so, select the tools here, otherwise just press enter",
-      choices: toolChoices,
-    });
+    const { toolsName } = await inquirer.prompt([
+      {
+        type: "checkbox",
+        name: "toolsName",
+        message:
+          "Would you like to build an agent using tools? If so, select the tools here, otherwise just press enter",
+        choices: toolChoices,
+      },
+    ]);
     const tools = toolsName?.map((tool: string) =>
       supportedTools.find((t) => t.name === tool),
     );

questions/simple.ts

@@ -1,4 +1,4 @@
-import prompts from "prompts";
+import inquirer from "inquirer";
 import {
   AI_REPORTS,
   EXAMPLE_10K_SEC_FILES,
@@ -9,7 +9,7 @@ import { askModelConfig } from "../helpers/providers";
 import { getTools } from "../helpers/tools";
 import { ModelConfig, TemplateFramework } from "../helpers/types";
 import { PureQuestionArgs, QuestionResults } from "./types";
-import { askPostInstallAction, questionHandlers } from "./utils";
+import { askPostInstallAction } from "./utils";
 
 type AppType =
   | "rag"
@@ -31,65 +31,38 @@ type SimpleAnswers = {
 export const askSimpleQuestions = async (
   args: PureQuestionArgs,
 ): Promise<QuestionResults> => {
-  const { appType } = await prompts(
+  const { appType } = await inquirer.prompt([
     {
-      type: "select",
+      type: "list",
       name: "appType",
       message: "What app do you want to build?",
-      hint: "🤖: Agent, 🔀: Workflow",
+      pageSize: Infinity,
       choices: [
+        new inquirer.Separator("Agents"),
+        { name: " Agentic RAG", value: "rag" },
+        { name: " Data Scientist", value: "data_scientist" },
+        { name: " Code Artifact Agent", value: "code_artifact" },
+        { name: " Information Extractor", value: "extractor" },
+        new inquirer.Separator("Agentic Document Workflows"),
         {
-          title: "🤖 Agentic RAG",
-          value: "rag",
-          description:
-            "Chatbot that answers questions based on provided documents.",
-        },
-        {
-          title: "🤖 Data Scientist",
-          value: "data_scientist",
-          description:
-            "Agent that analyzes data and generates visualizations by using a code interpreter.",
-        },
-        {
-          title: "🤖 Code Artifact Agent",
-          value: "code_artifact",
-          description:
-            "Agent that writes code, runs it in a sandbox, and shows the output in the chat UI.",
-        },
-        {
-          title: "🤖 Information Extractor",
-          value: "extractor",
-          description:
-            "Extracts information from documents and returns it as a structured JSON object.",
-        },
-        {
-          title: "🔀 Financial Report Generator",
+          name: " Financial Report Generator",
           value: "financial_report_agent",
-          description:
-            "Generates a financial report by analyzing the provided 10-K SEC data. Uses a code interpreter to create charts or to conduct further analysis.",
         },
         {
-          title: "🔀 Financial 10k SEC Form Filler",
+          name: " Financial 10k SEC Form Filler",
           value: "form_filling",
-          description:
-            "Extracts information from 10k SEC data and uses it to fill out a CSV form.",
         },
         {
-          title: "🔀 Contract Reviewer",
+          name: " Contract Review",
           value: "contract_review",
-          description:
-            "Extracts and reviews contracts to ensure compliance with GDPR regulations",
         },
         {
-          title: "🔀 Deep Researcher",
+          name: " Deep Researcher",
           value: "deep_research",
-          description:
-            "Researches and analyzes provided documents from multiple perspectives, generating a comprehensive report with citations to support key findings and insights.",
         },
       ],
     },
-    questionHandlers,
-  );
+  ]);
 
   let language: TemplateFramework = "fastapi";
   let llamaCloudKey = args.llamaCloudKey;
@@ -100,46 +73,41 @@ export const askSimpleQuestions = async (
     appType !== "contract_review" &&
     appType !== "deep_research"
   ) {
-    const { language: newLanguage } = await prompts(
+    const { language: newLanguage } = await inquirer.prompt([
       {
-        type: "select",
+        type: "list",
         name: "language",
         message: "What language do you want to use?",
         choices: [
-          { title: "Python (FastAPI)", value: "fastapi" },
-          { title: "Typescript (NextJS)", value: "nextjs" },
+          { name: "Python (FastAPI)", value: "fastapi" },
+          { name: "Typescript (NextJS)", value: "nextjs" },
         ],
       },
-      questionHandlers,
-    );
+    ]);
     language = newLanguage;
   }
 
-  const { useLlamaCloud: newUseLlamaCloud } = await prompts(
+  const { useLlamaCloud: newUseLlamaCloud } = await inquirer.prompt([
     {
-      type: "toggle",
+      type: "confirm",
       name: "useLlamaCloud",
       message: "Do you want to use LlamaCloud services?",
-      initial: false,
-      active: "Yes",
-      inactive: "No",
-      hint: "see https://www.llamaindex.ai/enterprise for more info",
+      suffix: " (see https://www.llamaindex.ai/enterprise for more info)",
+      default: false,
     },
-    questionHandlers,
-  );
+  ]);
   useLlamaCloud = newUseLlamaCloud;
 
   if (useLlamaCloud && !llamaCloudKey) {
     // Ask for LlamaCloud API key, if not set
-    const { llamaCloudKey: newLlamaCloudKey } = await prompts(
+    const { llamaCloudKey: newLlamaCloudKey } = await inquirer.prompt([
       {
-        type: "text",
+        type: "input",
         name: "llamaCloudKey",
         message:
           "Please provide your LlamaCloud API key (leave blank to skip):",
       },
-      questionHandlers,
-    );
+    ]);
     llamaCloudKey = newLlamaCloudKey || process.env.LLAMA_CLOUD_API_KEY;
   }
 

questions/utils.ts

@@ -1,8 +1,8 @@
 import { execSync } from "child_process";
 import fs from "fs";
+import inquirer from "inquirer";
 import path from "path";
 import { red } from "picocolors";
-import prompts from "prompts";
 import { TemplateDataSourceType, TemplatePostInstallAction } from "../helpers";
 import { toolsRequireConfig } from "../helpers/tools";
 import { QuestionResults } from "./types";
@@ -115,7 +115,7 @@ export const onPromptState = (state: any) => {
 };
 
 export const toChoice = (value: string) => {
-  return { title: value, value };
+  return { name: value, value };
 };
 
 export const questionHandlers = {
@@ -131,15 +131,15 @@ export async function askPostInstallAction(
 ): Promise<TemplatePostInstallAction> {
   const actionChoices = [
     {
-      title: "Just generate code (~1 sec)",
+      name: "Just generate code (~1 sec)",
       value: "none",
     },
     {
-      title: "Start in VSCode (~1 sec)",
+      name: "Start in VSCode (~1 sec)",
       value: "VSCode",
     },
     {
-      title: "Generate code and install dependencies (~2 min)",
+      name: "Generate code and install dependencies (~2 min)",
       value: "dependencies",
     },
   ];
@@ -158,21 +158,18 @@ export async function askPostInstallAction(
     !toolsRequireConfig(args.tools)
   ) {
     actionChoices.push({
-      title: "Generate code, install dependencies, and run the app (~2 min)",
+      name: "Generate code, install dependencies, and run the app (~2 min)",
       value: "runApp",
     });
   }
 
-  const { action } = await prompts(
+  const { action } = await inquirer.prompt([
     {
-      type: "select",
+      type: "list",
       name: "action",
       message: "How would you like to proceed?",
       choices: actionChoices,
-      initial: 1,
     },
-    questionHandlers,
-  );
-
+  ]);
   return action;
 }