Better AI Agent Tool

Advanced AI Agent with improved memory management and modern AI SDK - usable as Tool
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Overview

This node implements an advanced AI agent tool that can be used by other AI agents to perform tasks by calling various connected tools and managing conversation memory. It integrates with multiple AI language models and supports improved memory management, tool invocation, and step-wise execution control. The node is useful for scenarios where an AI assistant needs to orchestrate multiple tools to accomplish complex user goals, such as automating workflows, answering multi-step queries, or integrating external APIs dynamically.

Use Case Examples

  1. An AI agent that uses connected tools to fetch data, process it, and provide a summarized response.
  2. A multi-step task executor where the agent calls different tools in sequence to complete a complex workflow.
  3. An AI assistant that maintains conversation context and uses memory to improve interactions over time.

Properties

Name Meaning
Tip: This node can be used as a Tool by other AI agents Informational notice that this node can be utilized as a tool by other AI agents.
Description Description of what this AI agent tool does when called by other agents, allowing users to specify the tool's purpose.
Options Collection of configurable options for the AI agent behavior and execution control.

Output

JSON

  • response
    • name - Unique name identifier for the AI agent tool instance.
    • description - Description of the AI agent tool's purpose.
    • schema
      * query - Input query or task string that the AI agent will process.
    • invoke - Asynchronous function that executes the AI agent logic, returning the agent's textual response after processing the query and invoking connected tools.

Dependencies

  • Requires connection to a supported AI language model node (e.g., OpenAI, Anthropic, Google Gemini).
  • Optionally connects to AI memory and AI tool nodes for enhanced functionality.
  • Uses external AI SDKs and telemetry exporters for tracing and logging.

Troubleshooting

  • Error if no language model is connected: Ensure a supported AI language model node is connected to this node.
  • Conversation memory loading failures: The node will start fresh if it cannot load previous conversation history; check memory node configuration.
  • Tool execution errors: If a connected tool fails during execution, the error is logged and propagated; verify tool configurations and connectivity.
  • API key or model configuration issues: Confirm that API keys and model settings are correctly provided for connected language models.

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