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AI Agent

The AI Agent node calls a large language model to generate text or images. It supports any LLM provider, configurable system instructions, tool connections, and multi-modal operations. AI Agent Node

Use Cases

  • Generate summaries, classifications, or structured data from upstream inputs
  • Answer questions based on dynamic context from other nodes
  • Generate images from text prompts
  • Use reasoning models for complex decision-making within an orchestration
  • Build autonomous agents that use other nodes as tools

Node Reference

Parameters


Providers


Operations

Generate a text response

Calls the model with system instructions and a user prompt. Returns the generated text response.

Generate Image

Generates an image from a text description (requires an image-capable model, e.g. DALL-E 3).

Tool Connections (AI Tool Edges)

Connect other nodes to the AI Agent via an AI Tool edge to give the agent the ability to call those nodes during reasoning. The agent autonomously decides when and how to use each tool. AI Agent with Tools Example: Connect an Airtable node and an HTTP Request node as tools. The agent will query Airtable or call the API as needed to answer the user’s request.

Output Data

For Generate Text:
Reference in downstream nodes:
For Generate Image:

  • SubVerse Agents — Run a full multi-turn SubVerse AI agent with channel support
  • Conditions — Branch based on AI output
  • Slack — Send the generated text to a Slack channel