The Tool step is a deterministic execution node that invokes a predefined Tool and returns a schema-validated output. It enables reuse of packaged Tool logic across workflows, APIs, and other Tool...
Once logging is active and your flow has executed, you can access the run logs directly from the run history for each record. Following are the Run log column details: Timestamp: Start time of ...
Once you’ve built a reusable AI agent, you can incorporate it into multiple flows and APIs, very much like you would any import resource. In the steps below, you will also define the agent’s purpo...
Use the Tool Builder to create tools using a visual, low-code interface. You can define input and output schemas, add lookups or imports, configure mappings and transformations, set error handling...
To see all AI agents in your account, from the navigation menu, click AI agents under AI studio. Note If you haven’t added any agents yet, click Create AI agent to add one. The list displays key...
The table describes the log data captured for flow runs based on the selected log level (Basic or Detailed) and the type of application used in a flow step. Understanding this helps you know what ...
What's new Celigo AI delivers descriptive resource summaries, intuitive code assistance, and intelligent auto-mapping Resource descriptions With the help of Celigo AI, you can instant...
You can save and use mock output data in the Mock output panel of the Edit export section as simulated output data when configuring a flow. Enter your own sample data in the integrator.io canonica...
This article explains how to view and use logs related to AI agents and Guardrails in your environment. When you use AI agents and guardrails, you can track exactly what happened during a request ...
Tool input defines the structure and format of data exchanged between systems. It acts as a blueprint, ensuring consistency by specifying required fields, data types, and validation rules. This re...