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.