Short answer: Drop the "Novita AI → Novita 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": "meta-llama/llama-3.3-70b-instruct","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.