LLM

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

Updated Jan 7, 2026

Search Tags:#backend #llm #multi-turn #conversational-ai #system-prompt #chat-completions #z-ai-web-dev-sdk

Ready to run

npx skills add https://github.com/ashishkushwaha-mpu/ChocoWrap --skill llm-ashishkushwaha-mpu

💬 Prompt for ChatGPT / Claude Chat▼

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

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

The LLM skill provides a structured guide for implementing chat completions using the z-ai-web-dev-sdk, enabling developers to build robust conversational AI features such as chatbots, AI assistants, and content generators.

Core Features & Use Cases

Backend-first guidance: Emphasizes using the z-ai-web-dev-sdk on the server side with practical code examples and CLI usage.
Multi-turn conversations: Supports context management and system prompts to maintain coherent, long-running dialogues.
Use Cases: Chatbots, virtual assistants, customer support automation, content generation, and internal tooling.

Quick Start

Initialize the SDK in a backend service, create a system prompt and user messages, and call chat.completions.create to generate a response. Maintain conversation history across turns to preserve context.

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 chat completions using z-ai-web-dev-sdk?▼

To implement multi-turn chat completions, initialize the z-ai-web-dev-sdk in your backend, define a system prompt, maintain conversation history across user messages, and call chat.completions.create to preserve context.

Can I use this Skill to build a backend AI assistant with system prompts?▼

Yes, you can build backend AI assistants by applying structured guidance for z-ai-web-dev-sdk, utilizing system prompts and context management to support coherent, long-running dialogues and virtual assistant workflows.

What is the best way to manage context for conversational AI in a backend application?▼

The best way to manage context for conversational AI is maintaining conversation history across turns alongside system prompts, ensuring the LLM preserves coherent state during long-running dialogues via backend code.

Does the z-ai-web-dev-sdk support content generation and customer support automation?▼

Yes, the z-ai-web-dev-sdk supports content generation and customer support automation by providing practical code examples and CLI usage for implementing chat completions and text-generation workflows on the server side.

Do I need a backend environment to run chatbot workflows with z-ai-web-dev-sdk?▼

Yes, you need a backend environment because the Skill emphasizes server-side z-ai-web-dev-sdk usage, providing backend-first guidance with practical code examples and CLI commands for chat completions.