/LLM

name: LLM
description: Implement large language model (LLM) chat completions using the z-ai-web-dev-sdk. Use this skill when the user needs to build conversational AI applications, chatbots, AI assistants, or any text generation features. Supports multi-turn conversations, system prompts, and context management.
license: MIT

LLM (Large Language Model) Skill

This skill guides the implementation of chat completions functionality using the z-ai-web-dev-sdk package, enabling powerful conversational AI and text generation capabilities.

Skills Path

**Skill Location**: `{project_path}/skills/llm`

this skill is located at above path in your project.

**Reference Scripts**: Example test scripts are available in the `{Skill Location}/scripts/` directory for quick testing and reference. See `{Skill Location}/scripts/chat.ts` for a working example.

Overview

The LLM skill allows you to build applications that leverage large language models for natural language understanding and generation, including chatbots, AI assistants, content generation, and more.

**IMPORTANT**: z-ai-web-dev-sdk MUST be used in backend code only. Never use it in client-side code.

Prerequisites

The z-ai-web-dev-sdk package is already installed. Import it as shown in the examples below.

CLI Usage (For Simple Tasks)

For simple, one-off chat completions, you can use the z-ai CLI instead of writing code. This is ideal for quick tests, simple queries, or automation scripts.

Basic Chat

# Simple question
z-ai chat --prompt "What is the capital of France?"

# Save response to file
z-ai chat -p "Explain quantum computing" -o response.json

# Stream the response
z-ai chat -p "Write a short poem" --stream

With System Prompt

# Custom system prompt for specific behavior
z-ai chat \
  --prompt "Review this code: function add(a,b) { return a+b; }" \
  --system "You are an expert code reviewer" \
  -o review.json

With Thinking (Chain of Thought)

# Enable thinking for complex reasoning
z-ai chat \
  --prompt "Solve this math problem: If a train travels 120km in 2 hours, what's its speed?" \
  --thinking \
  -o solution.json

CLI Parameters

• `--prompt, -p <text>`: **Required** - User message content
• `--system, -s <text>`: Optional - System prompt for custom behavior
• `--thinking, -t`: Optional - Enable chain-of-thought reasoning (default: disabled)
• `--output, -o <path>`: Optional - Output file path (JSON format)
• `--stream`: Optional - Stream the response in real-time

When to Use CLI vs SDK

**Use CLI for:**

• Quick one-off questions
• Simple automation scripts
• Testing prompts
• Single-turn conversations

**Use SDK for:**

• Multi-turn conversations with context
• Custom conversation management
• Integration with web applications
• Complex chat workflows
• Production applications

Basic Chat Completions

Simple Question and Answer

import ZAI from 'z-ai-web-dev-sdk';

async function askQuestion(question) {
  const zai = await ZAI.create();

  const completion = await zai.chat.completions.create({
    messages: [
      {
        role: 'assistant',
        content: 'You are a helpful assistant.'
      },
      {
        role: 'user',
        content: question
      }
    ],
    thinking: { type: 'disabled' }
  });

  const response = completion.choices[0]?.message?.content;
  return response;
}

// Usage
const answer = await askQuestion('What is the capital of France?');
console.log('Answer:', answer);

Custom System Prompt

import ZAI from 'z-ai-web-dev-sdk';

async function customAssistant(systemPrompt, userMessage) {
  const zai = await ZAI.create();

  const completion = await zai.chat.completions.create({
    messages: [
      {
        role: 'assistant',
        content: systemPrompt
      },
      {
        role: 'user',
        content: userMessage
      }
    ],
    thinking: { type: 'disabled' }
  });

  return completion.choices[0]?.message?.content;
}

// Usage - Code reviewer
const codeReview = await customAssistant(
  'You are an expert code reviewer. Analyze code for bugs, performance issues, and best practices.',
  'Review this function: function add(a, b) { return a + b; }'
);

// Usage - Creative writer
const story = await customAssistant(
  'You are a creative fiction writer who writes engaging short stories.',
  'Write a short story about a robot learning to paint.'
);

console.log(codeReview);
console.log(story);

Multi-turn Conversations

Conversation History Management

import ZAI from 'z-ai-web-dev-sdk';

class ConversationManager {
  constructor(systemPrompt = 'You are a helpful assistant.') {
    this.messages = [
      {
        role: 'assistant',
        content: systemPrompt
      }
    ];
    this.zai = null;
  }

  async initialize() {
    this.zai = await ZAI.create();
  }

  async sendMessage(userMessage) {
    // Add user message to history
    this.messages.push({
      role: 'user',
      content: userMessage
    });

    // Get completion
    const completion = await this.zai.chat.completions.create({
      messages: this.messages,
      thinking: { type: 'disabled' }
    });

    const assistantResponse = completion.choices[0]?.message?.content;

    // Add assistant response to history
    this.messages.push({
      role: 'assistant',
      content: assistantResponse
    });

    return assistantResponse;
  }

  getHistory() {
    return this.messages;
  }

  clearHistory(systemPrompt = 'You are a helpful assistant.') {
    this.messages = [
      {
        role: 'assistant',
        content: systemPrompt
      }
    ];
  }

  getMessageCount() {
    // Subtract 1 for system message
    return this.messages.length - 1;
  }
}

// Usage
const conversation = new ConversationManager();
await conversation.initialize();

const response1 = await conversation.sendMessage('Hi, my name is John.');
console.log('AI:', response1);

const response2 = aw