Implement LLM chat completions and multi-turn conversations using the z-ai-web-dev-sdk.
npx skills add https://github.com/tmtgroupbot/lptracker-deploy --skill llm-tmtgroupbot
Please help me install this Agent Skill. Skill: LLM Source: https://github.com/tmtgroupbot/lptracker-deploy/tree/main/skills/LLM Command: npx skills add https://github.com/tmtgroupbot/lptracker-deploy --skill llm-tmtgroupbot
High-intent search queries and answers about installing and using this skill.
Call ZAI.create() to initialize the SDK, then use zai.chat.completions.create with a messages array containing an assistant system prompt and user message. The response text is available at completion.choices[0].message.content.
Maintain a messages array that starts with a system prompt, append each user message and assistant response, and pass the full array to chat.completions.create on every turn. Trim older messages when the history grows too long to avoid token limits.
No, z-ai-web-dev-sdk must be used in backend code only. Importing it in client-side code exposes credentials and is not supported; route all chat requests through your server.
Use the z-ai CLI for quick one-off questions, simple automation scripts, and prompt testing with commands like z-ai chat --prompt. Use the SDK for multi-turn conversations, web application integration, and production workflows.
Empty responses occur when completion.choices[0].message.content is missing or blank. Add validation that checks the response is non-empty, and implement retry logic with exponential backoff for transient failures.
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