Logs: Logs

Log Overview

Logs is used to view execution records of tasks related to the current dataset. The top of the page displays statistics such as Total files, Processing, and Downloading. The lower area is divided into document logs and dataset-level logs by log type. Document logs focus on the processing process of a single document. Dataset-level logs focus on tasks within the entire dataset scope. When troubleshooting, first determine whether the problem occurs in a single document or the entire dataset, then go to the corresponding logs to view details.

Document Logs

Document logs are used to view and trace task execution related to a single document, such as document parsing, task cancellation, and task success or failure. When a document has not completed parsing for a long time, parsing fails, or the number of generated chunks is abnormal, use document logs to view task status and execution details.

Document logs mainly include:

• ID: The unique identifier of the log record or task.
• Filename: The name of the document executing the current task.
• Source: The document source.
• Ingestion pipeline: The parsing method or pipeline used when processing the document.
• Start date: The task start time.
• Task: The task type, such as Parse.
• Status: The current task execution status.
• Operations: Operation entry. You can view log details for the current task, including execution process and error information.

If parsing fails for only one document, a document stays processing for a long time, or the number of chunks is abnormal, it is recommended to check that document's logs first.

Dataset-Level Logs

Dataset-level logs are used to view task execution records whose processing object is the entire dataset. Unlike document logs for single-document parsing tasks, dataset-level logs mainly record dataset-level processing tasks, such as Knowledge Compilation.

Dataset-level logs mainly include:

• ID: The unique identifier of the task record.
• Start date: The task start time.
• Processing type: The processing type, used to indicate the current dataset-level task, such as Wiki.
• Status: The current task execution status.
• Operations: Operation entry. You can view log details and execution information for the current task.

When a dataset-level processing task fails, does not complete for a long time, or needs execution confirmation, view the corresponding task record and log details here.

Tip: For tasks executed on a single document, such as document parsing, view document logs. For tasks executed on the entire dataset, such as Knowledge Compilation, view dataset-level logs.

Log Troubleshooting Suggestions

When task execution is abnormal or does not complete for a long time, first select the corresponding logs based on task type, then troubleshoot based on task status and log details.

• Document processing tasks: View document logs. Document logs record processing tasks for specific documents. Use information such as Filename, Source, Ingestion pipeline, Task, and Status to confirm which document and processing flow has the exception. For documents processed with Data Pipeline, you can also use the entry in Operations to view the corresponding pipeline execution result.
• Dataset-level processing tasks: View dataset-level logs. Dataset-level tasks such as Knowledge Compilation are recorded here. Use Processing type and Status to find the corresponding task, and view log details through Operations.
• Task execution failed: When Status is Failed, open the corresponding task log details and view the specific error information.
• Task does not complete for a long time: When a task stays in Pending, Running, or Schedule for a long time, first confirm the current task status and start time, then view log details to determine whether the task is still running normally.

Note: Document logs and dataset-level logs record different types of processing tasks. They are not parent-child logs or summary logs. When troubleshooting, select the corresponding log based on the actual task.