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NodesCore

AI Agent

Run an LLM-backed workflow step with a prompt, chat model, and optional tools.

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AI Agent

Description

AIAgent runs a model against each workflow item. It is the main built-in node for classification, extraction, summarization, routing, and tool-enabled agent flows.

Examples

Basic usage: classify inbound mail into RFQ or other

new AIAgent<{ subject: string; body: string }, { outcome: "rfq" | "other"; reasoning: string }>(
  "Classify RFQ vs other",
  'Respond with strict JSON only. Shape: {"outcome":"rfq"|"other","reasoning":"..."}',
  (item) => JSON.stringify(item.json),
  openAiChatModelPresets.demoGpt4oMini,
);

Example input:

{
  "subject": "RFQ for 1000 widgets",
  "body": "Please send pricing and lead times."
}

Example output:

{
  "outcome": "rfq",
  "reasoning": "The sender is explicitly requesting a quote."
}

Advanced usage: use tools before returning a structured answer

new AIAgent(
  "Answer with product context",
  "Use the available tools when needed, then answer with a final structured result.",
  (item) => JSON.stringify(item.json),
  openAiChatModelPresets.demoGpt4oMini,
  [new SearchDocsToolConfig(), new PricingLookupToolConfig()],
);

Example input:

{
  "question": "Can the Pro plan process Gmail attachments, and what does it cost?"
}

Example output:

{
  "answer": "Yes. The Pro plan supports Gmail attachment processing.",
  "recommendedPlan": "pro",
  "monthlyPrice": 99
}

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