LLM

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

2.7k|627|Updated Sep 11, 2025

Search Tags:#backend #llm #sdk #chat #conversations #prompt-engineering #context-management

Ready to run

npx skills add https://github.com/jjyaoao/HelloAgents --skill llm-jjyaoao

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: LLM
Source: https://github.com/jjyaoao/HelloAgents/tree/main/skills/LLM
Command: npx skills add https://github.com/jjyaoao/HelloAgents --skill llm-jjyaoao

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

This skill enables developers to build robust, multi-turn LLM chat experiences using the z-ai-web-dev-sdk, covering system prompts, context management, and persistent conversation history in backend applications.

Core Features & Use Cases

Multi-turn conversations with role-based messaging and context tracking.
System prompts, session history, and configurable thinking modes for production workloads.
Suitable for chatbots, AI assistants, customer support agents, and content generation workflows that require reliable backend integration.

Quick Start

Create a ZAI instance and initiate a multi-turn chat using a system prompt followed by 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 context management in a backend LLM application?▼

To implement multi-turn conversations with context management, use the z-ai-web-dev-sdk to structure role-based messages and persist conversation history across backend sessions. This ensures reliable chat completions for production workloads.

How do I configure system prompts and session history for chat completions?▼

Configuring system prompts and session history involves passing structured messages with distinct roles to the z-ai-web-dev-sdk. This approach enables context tracking and configurable thinking modes for robust conversational AI workflows.

Does the z-ai-web-dev-sdk support role-based messaging for production chatbots?▼

Yes, the z-ai-web-dev-sdk supports role-based messaging for production chatbots by allowing developers to define system, user, and assistant roles. This structured messaging ensures safe default configurations and reliable error handling.

What is the best way to build a multi-turn AI assistant with persistent chat history?▼

The best way to build a multi-turn AI assistant with persistent chat history is leveraging the z-ai-web-dev-sdk for backend integration. It handles context tracking and session history, ensuring conversations persist reliably across user interactions.

Can I use this backend LLM SDK for customer support agent workflows?▼

Yes, you can use this backend LLM SDK for customer support agent workflows. The skill provides robust prompt engineering, error handling, and context management specifically designed for reliable backend integration in support scenarios.

Why does context management fail in multi-turn LLM chats without session persistence?▼

Context management fails in multi-turn LLM chats without session persistence because the model loses prior interaction state. Using the z-ai-web-dev-sdk to maintain conversation history across backend sessions ensures continuous and coherent dialogue.