LLM

Implement multi-turn LLM chat completions with the z-ai-web-dev-sdk.

2|Updated Mar 31, 2026
One-click install
npx skills add https://github.com/marktantongco/promptc-os --skill llm-marktantongco
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: LLM
Source: https://github.com/marktantongco/promptc-os/tree/main/skills/LLM
Command: npx skills add https://github.com/marktantongco/promptc-os --skill llm-marktantongco

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires z-ai-web-dev-sdk, and includes scripts (resource) components.

What problem does it solve?

LLM enables developers to implement large language model chat completions and conversational AI using the z-ai-web-dev-sdk. Use this skill when building chatbots, AI assistants, or any text-generation features that require multi-turn conversations, system prompts, and context management.

Core Features & Use Cases

  • Multi-turn conversations: maintain conversation history and context across turns with system prompts to deliver coherent, context-aware AI responses.
  • System prompts & persona control: define and enforce assistant roles, behavior, and constraints to ensure consistent interactions across sessions.
  • Backend-ready guidance for production apps: practical patterns, sample code, error handling, and safety considerations for server-side usage of the z-ai-web-dev-sdk.
  • Use Case: Build a customer-support chatbot that remembers user context and answers questions with relevant data and history.

Quick Start

Initialize the SDK on the server and start a multi-turn chat by supplying a system prompt and a user message.

Frequently Asked Questions about LLM

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I implement multi-turn conversations with an LLM chatbot?▼

To implement multi-turn conversations in an LLM chatbot, you maintain conversation history and context across turns using system prompts, ensuring coherent and context-aware AI responses throughout the session.

What's the best way to enforce a specific persona for a conversational AI assistant?▼

The best way to enforce a specific persona for a conversational AI assistant is by defining and enforcing assistant roles, behavior, and constraints through system prompts to ensure consistent interactions across sessions.

Can I use the z-ai-web-dev-sdk for backend chat completions in production?▼

Yes, you can use the z-ai-web-dev-sdk for backend chat completions in production apps, applying practical patterns, sample code, error handling, and safety considerations for server-side usage.

How do I manage context history and system prompts across backend services?▼

To manage context history and system prompts across backend services, apply clear patterns for conversation history management and system prompts provided by the z-ai-web-dev-sdk for server-side text generation.

How to build a customer support chatbot that remembers user context?▼

To build a customer support chatbot that remembers user context, implement multi-turn conversations with the z-ai-web-dev-sdk, maintaining conversation history and system prompts to answer questions with relevant data.