Enable backend chat completions with large language models via z-ai-web-dev-sdk.
npx skills add https://github.com/TIAN0517/iosboss --skill llm-tian0517
Please help me install this Agent Skill. Skill: LLM Source: https://github.com/TIAN0517/iosboss/tree/main/temp_extract/99999999/skills/LLM Command: npx skills add https://github.com/TIAN0517/iosboss --skill llm-tian0517
This skill enables backend-driven chat completions with large language models, allowing developers to build robust conversational AI applications with controlled prompts and context.
Use the provided scripts/chat.ts to run a basic chat example: initialize the SDK, construct a messages array with system and user messages, and call zai.chat.completions.create with thinking disabled to obtain a reply.
High-intent search queries and answers about installing and using this skill.
Backend chat completions are implemented using the z-ai-web-dev-sdk to execute server-side inference. You initialize the SDK, construct a messages array with system and user roles, and call the chat completions endpoint to generate context-aware replies.
Yes, multi-turn conversations are supported by passing message histories and system prompts to the backend. This allows you to maintain context across exchanges and customize the behavior of large language models for conversational AI applications.
Context-aware responses are fully supported by supplying message histories to the large language model. This mechanism enables AI assistants and content-generation tools to generate replies that reference prior user inputs and system instructions accurately.
The best way to start is by running the included example scripts. You initialize the SDK, define a messages array, and call the chat completions endpoint with thinking options disabled to quickly obtain your first AI-generated reply.
Yes, you need the z-ai-web-dev-sdk to run server-side chat completions. This dependency handles backend execution for large language models, ensuring controlled prompts and context management for your AI applications.
A backend-first workflow secures API keys and manages context directly on the server. Relying on the z-ai-web-dev-sdk for server-side execution prevents exposure of sensitive credentials and ensures robust conversational AI behavior.
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