Short answer: Drop the "xAI → Chat Completion" action anywhere in your workflow, map the inputs from upstream nodes, and publish.
Every field can be mapped from an upstream trigger, AI step, table row, or hard-coded literal.
| Field | Type | Required | Description |
|---|---|---|---|
Model model | options | Required | Which model to use |
User Message message | string | Required | User message to send to the model |
System Prompt system_prompt | string | Optional | Optional system instructions that shape the model's behavior |
Temperature temperature | string | Optional | Sampling temperature (0–2). Higher = more random. |
Max Tokens max_tokens | string | Optional | Maximum tokens to generate in the response |
Top P top_p | string | Optional | Nucleus sampling threshold (0–1) |
Response Format response_format | options | Optional | Force JSON output (model must support JSON mode) |
{"model": "{{trigger.model}}","message": "e.g. Summarize this article in 3 bullets","system_prompt": "e.g. You are a helpful assistant.","temperature": "0.7","max_tokens": "1024"}
{"id": "chatcmpl-abc123","model": "grok-4","usage": {"total_tokens": 60,"prompt_tokens": 10,"completion_tokens": 50},"choices": [{"message": {"role": "assistant","content": "Sample response"},"finish_reason": "stop"}]}
Use these fields in downstream nodes for routing, logging, or error handling.
Any of these apps can fire this action as part of a workflow.
Triggered by anything in the catalog. Free tier available. No credit card.