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Logs are system records that contain information about input and output messages that AI Agents receive and send. The primary purpose of the logs is to debug workflows by observing if and where errors are occurring.
You can track logs in real time or load the log history to review outputs that occurred in the past.
To improve browser performance, the log list uses virtualization. This means your browser loads only the log entries visible on your screen at any given time. As a result, you can’t copy more lines than what’s currently visible.

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Log entries

The following table provides an overview of the log entries.
FieldDescription
timestampThe date and time of the log entry. The format is YYYY-MM-DD HH:MM:SS.
log typeOne of the following log entry types:
  • info — a log entry that contains general information about the normal operation of a Flow.
  • error — a log entry that a log entry that might contain information for diagnosing an issue in the Flow.
  • debug — a log entry that contains debug information.
messageDescribes the event of the log entry.
metadataAdditional data associated with the log entry, for example, organisationID, flowID, text, and other.

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Working with Logs

  • GUI
  • API
In Test > Logs, you can view and filter Project logs as well as search them by user ID and Flow name.SettingsTo configure the log entries displayed in the log list, use the following settings:
Setting NameFunction
Live LoggingActivates real-time log updates. This setting is activated by default.
Show TimestampIncludes the timestamp of the log entries. This setting is activated by default.
Show Additional MetadataIncludes metadata related to input and output messages. This setting is activated by default.
InfoIncludes log entries of the info type. This setting is activated by default.
ErrorIncludes log entries of the error type. This setting is activated by default.
DebugIncludes log entries of the debug type. This setting is deactivated by default.
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