Short answer: Drop the "OpenAI → 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 OpenAI model to use |
Message message | string | Required | The user message to send |
System Prompt system_prompt | string | Optional | Instructions that shape how the model responds |
Temperature temperature | string | Optional | Controls randomness (0 = deterministic, 2 = very creative). Default is 1. |
Max Tokens max_tokens | string | Optional | Maximum number of tokens in the response |
{"model": "{{trigger.model}}","message": "e.g. Summarize this document...","system_prompt": "e.g. You are a helpful assistant.","temperature": "e.g. 0.7","max_tokens": "e.g. 1024"}
{"id": "chatcmpl-abc123","model": "gpt-4o","usage": {"total_tokens": 30,"prompt_tokens": 10,"completion_tokens": 20},"object": "chat.completion","choices": [{"index": 0,"message": {"role": "assistant","content": "Hello! How can I help you?"},"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.