JiMax Object Tool LLM
AI-generatedSummary
Generate a structured object from a prompt with a selected AI provider, optionally calling configured n8n workflows as tools and using file-backed conversation memory.
Inputs
- Provider and Model ID (required) — Choose OpenAI, Google Gemini, Anthropic, or an OpenAI-compatible provider, then specify the model ID. The matching provider credentials are required.
- Prompt (required) — The user message sent to the model for this input item.
- Zod Schema (required) — Zod expression defining the structure of the model's returned object; the variable
zis available. - Tools — Optional tools that let the model call specified n8n workflows. Each tool has a required name, description, and workflow ID, plus a Zod input schema. When Include Parent Item Data is enabled, the current input item's JSON is passed as
_parentDataalongside the tool arguments. - Max Steps — Maximum number of tool-calling iterations; defaults to 5.
- System Prompt — Optional system message included before the other messages.
- Initial Messages (JSON) — Optional JSON array of starting messages. Each message must have a role of
user,assistant,system, ortooland string content. - Use Memory — When enabled, loads and saves conversation history using the Session ID. History is stored in
jimax_memory.jsonin the n8n process working directory. - Session ID (required) — Conversation key used when memory is enabled.
- Memory Window — When memory is enabled, number of previous interactions to load; defaults to 5.
- Save in Background — When memory is enabled, saves history without waiting when true; defaults to true.
Output shape
One output item per input item, each containing the model-generated object as its JSON data.
The returned object follows the configured Zod schema. Tool calls return the first output item's JSON from the selected workflow; if it returns no output, the tool reports a success message. With continue-on-fail enabled, an item that errors returns
{ "error": "..." }. Memory stores the latest 100 user/assistant messages per session.
Examples
Example 1: Use a model to classify a support request and call a workflow to look up customer details
Set a prompt and output schema, add a workflow tool with its input schema, and optionally enable memory with a session ID.