Agent skill

ai-model-nodejs

Use this skill when developing Node.js backend services or CloudBase cloud functions (Express/Koa/NestJS, serverless, backend APIs) that need AI capabilities. Features text generation (generateText), streaming (streamText), AND image generation (generateImage) via @cloudbase/node-sdk ≥3.16.0. Built-in models include Hunyuan (hunyuan-2.0-instruct-20251111 recommended), DeepSeek (deepseek-v3.2 recommended), and hunyuan-image for images. This is the ONLY SDK that supports image generation. NOT for browser/Web apps (use ai-model-web) or WeChat Mini Program (use ai-model-wechat).

Stars 42
Forks 3

Install this agent skill to your Project

npx add-skill https://github.com/TencentCloudBase/skills/tree/main/skills/ai-model-nodejs

SKILL.md

When to use this skill

Use this skill for calling AI models in Node.js backend or CloudBase cloud functions using @cloudbase/node-sdk.

Use it when you need to:

  • Integrate AI text generation in backend services
  • Generate images with Hunyuan Image model
  • Call AI models from CloudBase cloud functions
  • Server-side AI processing

Do NOT use for:

  • Browser/Web apps → use ai-model-web skill
  • WeChat Mini Program → use ai-model-wechat skill
  • HTTP API integration → use http-api skill

Available Providers and Models

CloudBase provides these built-in providers and models:

Provider Models Recommended
hunyuan-exp hunyuan-turbos-latest, hunyuan-t1-latest, hunyuan-2.0-thinking-20251109, hunyuan-2.0-instruct-20251111 hunyuan-2.0-instruct-20251111
deepseek deepseek-r1-0528, deepseek-v3-0324, deepseek-v3.2 deepseek-v3.2

Installation

bash
npm install @cloudbase/node-sdk

⚠️ AI feature requires version 3.16.0 or above. Check with npm list @cloudbase/node-sdk.


Initialization

In Cloud Functions

js
const tcb = require('@cloudbase/node-sdk');
const app = tcb.init({ env: '<YOUR_ENV_ID>' });

exports.main = async (event, context) => {
  const ai = app.ai();
  // Use AI features
};

Cloud Function Configuration for AI Models

⚠️ Important: When creating cloud functions that use AI models (especially generateImage() and large language model generation), set a longer timeout as these operations can be slow.

Using MCP Tool manageFunctions(action="createFunction"):

Legacy compatibility: if an older prompt still says createFunction, keep the same payload shape but execute it through manageFunctions(action="createFunction").

Set the timeout parameter in the func object:

  • Parameter: func.timeout (number)
  • Unit: seconds
  • Range: 1 - 900
  • Default: 20 seconds (usually too short for AI operations)

Recommended timeout values:

  • Text generation (generateText): 60-120 seconds
  • Streaming (streamText): 60-120 seconds
  • Image generation (generateImage): 300-900 seconds (recommended: 900s)
  • Combined operations: 900 seconds (maximum allowed)

In Regular Node.js Server

js
const tcb = require('@cloudbase/node-sdk');
const app = tcb.init({
  env: '<YOUR_ENV_ID>',
  secretId: '<YOUR_SECRET_ID>',
  secretKey: '<YOUR_SECRET_KEY>'
});

const ai = app.ai();

generateText() - Non-streaming

js
const model = ai.createModel("hunyuan-exp");

const result = await model.generateText({
  model: "hunyuan-2.0-instruct-20251111",  // Recommended model
  messages: [{ role: "user", content: "你好,请你介绍一下李白" }],
});

console.log(result.text);           // Generated text string
console.log(result.usage);          // { prompt_tokens, completion_tokens, total_tokens }
console.log(result.messages);       // Full message history
console.log(result.rawResponses);   // Raw model responses

Error Handling Pattern

js
const model = ai.createModel("deepseek");

try {
  const result = await model.generateText({
    model: "deepseek-v3.2",
    messages: [{ role: "user", content: "Summarize today's deployment logs" }],
  });

  console.log(result.text);
} catch (error) {
  console.error("AI request failed", error);
}

streamText() - Streaming

js
const model = ai.createModel("hunyuan-exp");

const res = await model.streamText({
  model: "hunyuan-2.0-instruct-20251111",  // Recommended model
  messages: [{ role: "user", content: "你好,请你介绍一下李白" }],
});

// Option 1: Iterate text stream (recommended)
for await (let text of res.textStream) {
  console.log(text);  // Incremental text chunks
}

// Option 2: Iterate data stream for full response data
for await (let data of res.dataStream) {
  console.log(data);  // Full response chunk with metadata
}

// Option 3: Get final results
const messages = await res.messages;  // Full message history
const usage = await res.usage;        // Token usage

generateImage() - Image Generation

⚠️ Image generation is only available in Node SDK, not in JS SDK (Web) or WeChat Mini Program.

js
const imageModel = ai.createImageModel("hunyuan-image");

const res = await imageModel.generateImage({
  model: "hunyuan-image",
  prompt: "一只可爱的猫咪在草地上玩耍",
  size: "1024x1024",
  version: "v1.9",
});

console.log(res.data[0].url);           // Image URL (valid 24 hours)
console.log(res.data[0].revised_prompt);// Revised prompt if revise=true

Image Generation Parameters

ts
interface HunyuanGenerateImageInput {
  model: "hunyuan-image";      // Required
  prompt: string;                       // Required: image description
  version?: "v1.8.1" | "v1.9";         // Default: "v1.8.1"
  size?: string;                        // Default: "1024x1024"
  negative_prompt?: string;             // v1.9 only
  style?: string;                       // v1.9 only
  revise?: boolean;                     // Default: true
  n?: number;                           // Default: 1
  footnote?: string;                    // Watermark, max 16 chars
  seed?: number;                        // Range: [1, 4294967295]
}

interface HunyuanGenerateImageOutput {
  id: string;
  created: number;
  data: Array<{
    url: string;                        // Image URL (24h valid)
    revised_prompt?: string;
  }>;
}

Type Definitions

ts
interface BaseChatModelInput {
  model: string;                        // Required: model name
  messages: Array<ChatModelMessage>;    // Required: message array
  temperature?: number;                 // Optional: sampling temperature
  topP?: number;                        // Optional: nucleus sampling
}

type ChatModelMessage =
  | { role: "user"; content: string }
  | { role: "system"; content: string }
  | { role: "assistant"; content: string };

interface GenerateTextResult {
  text: string;                         // Generated text
  messages: Array<ChatModelMessage>;    // Full message history
  usage: Usage;                         // Token usage
  rawResponses: Array<unknown>;         // Raw model responses
  error?: unknown;                      // Error if any
}

interface StreamTextResult {
  textStream: AsyncIterable<string>;    // Incremental text stream
  dataStream: AsyncIterable<DataChunk>; // Full data stream
  messages: Promise<ChatModelMessage[]>;// Final message history
  usage: Promise<Usage>;                // Final token usage
  error?: unknown;                      // Error if any
}

interface Usage {
  prompt_tokens: number;
  completion_tokens: number;
  total_tokens: number;
}

Expand your agent's capabilities with these related and highly-rated skills.

TencentCloudBase/skills

miniprogram-development

WeChat Mini Program development skill for building, debugging, previewing, testing, publishing, and optimizing mini program projects. This skill should be used when users ask to create, develop, modify, debug, preview, test, deploy, publish, launch, review, or optimize WeChat Mini Programs, mini program pages, components, routing, project structure, project configuration, project.config.json, appid setup, device preview, real-device validation, WeChat Developer Tools workflows, miniprogram-ci preview/upload flows, or mini program release processes. It should also be used when users explicitly mention CloudBase, wx.cloud, Tencent CloudBase, 腾讯云开发, or 云开发 in a mini program project.

42 3
Explore
TencentCloudBase/skills

spec-workflow

Use when medium-to-large changes need explicit requirements, technical design, and task planning before implementation, especially for multi-module work, unclear acceptance criteria, or architecture-heavy requests.

42 3
Explore
TencentCloudBase/skills

cloud-storage-web

Complete guide for CloudBase cloud storage using Web SDK (@cloudbase/js-sdk) - upload, download, temporary URLs, file management, and best practices.

42 3
Explore
TencentCloudBase/skills

ui-design

Use when users need visual direction, interface hierarchy, layout decisions, design specifications, or prototypes before implementing a Web or mini program UI.

42 3
Explore
TencentCloudBase/skills

cloudbase-platform

CloudBase platform overview and routing guide. This skill should be used when users need high-level capability selection, platform concepts, console navigation, or cross-platform best practices before choosing a more specific implementation skill.

42 3
Explore
TencentCloudBase/skills

ai-model-wechat

Use this skill when developing WeChat Mini Programs (小程序, 企业微信小程序, wx.cloud-based apps) that need AI capabilities. Features text generation (generateText) and streaming (streamText) with callback support (onText, onEvent, onFinish) via wx.cloud.extend.AI. Built-in models include Hunyuan (hunyuan-2.0-instruct-20251111 recommended) and DeepSeek (deepseek-v3.2 recommended). API differs from JS/Node SDK - streamText requires data wrapper, generateText returns raw response. NOT for browser/Web apps (use ai-model-web), Node.js backend (use ai-model-nodejs), or image generation (not supported).

42 3
Explore

Didn't find tool you were looking for?

Be as detailed as possible for better results