What the data for this category looks like
Daily documents for this category include annotation specifications, sample packages, quality inspection reports, and problem feedback forms. Data mainly comes from customer corpora, annotation platforms, vocabularies, and quality inspection sampling results. Updates follow a cycle of daily or per-batch annotation tasks. Most data fields include text content, annotation tags, quality inspection scores, problem annotations, and similar items. Units are primarily characters, tag categories, and sampling batches. The overall work centers on annotation requirements for semantic boundaries, entity recognition, and intent classification, which differs from image annotation projects that focus on visual features.
What constraints these characteristics impose on the scheduled tasks and automation workflow
Data sources are scattered and update cycles are inconsistent. It is necessary to regularly synchronize corpora and annotation results from multiple channels, which can easily lead to data duplication or omission. There is high demand for batch processing of sample packages and quality inspection reports. The single processing volume is limited by the system, so tasks must be split to avoid timeouts. Annotation specification versions are updated frequently. Regular checks are required to confirm whether the currently used specifications match the latest version, to prevent annotation deviations. Problem feedback forms have high real-time requirements, so they must be automatically routed to the corresponding processing links to avoid delays from manual follow-up. At the same time, semantic verification of text data relies on vocabularies and annotation rules. Regularly updating vocabularies can improve annotation consistency.
How to configure settings
This document is written based on the configuration logic of FastGPT v4.17.0.
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
| Scheduled trigger cycle | 15–60 minutes, or trigger after annotation batches are completed | Adapt to daily or per-batch update rhythms, avoid frequent triggers that occupy system resources |
| Single processing sample volume | 100–500 items | Match the system's single data processing limits, prevent errors from exceeding content length limits |
| Specification and vocabulary check interval | 24 hours | Adapt to the daily update frequency of annotation specifications and vocabularies, ensure the latest rules are used |
| Task timeout threshold | 600 seconds | Reserve sufficient time for batch text processing, avoid task interruptions mid-run |
| Failure retry count | 2–3 times | Address temporary network fluctuations or data reading exceptions, reduce task failure rates |
Three common configuration mistakes
- Phenomenon: A maxLength error is triggered when importing a large number of documents in batches, and the number of single processing result entries is insufficient. Cause: A reasonable single processing task volume is not set, exceeding the system's single data reading content length limit.
- Phenomenon: After knowledge base retrieval is completed, the reranking model continues to occupy video memory and cannot automatically release it. Cause: No automatic unload rule for idle models after task completion is configured, resulting in continuous resource occupation.
- Phenomenon: The automatic dialog question function in the workflow does not respond, and preset actions are not triggered. Cause: Trigger conditions and question actions are not correctly bound, and context data for the corresponding annotation task is not associated.
How to confirm the configuration is correct
- View the scheduled task trigger logs to confirm that the task starts normally according to the preset cycle or batch node.
- Perform a single batch processing test, check that the number of processed samples matches the configured single processing task volume.
- Simulate an update to the annotation specification or vocabulary, verify whether the system triggers the check action according to the configured interval.
- Trigger a failed test task, confirm that the system executes retry operations according to the configured retry count.
The values provided are common starting points and should be measured against the reader's own samples.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-10-19.