What Data for This Category Looks Like
Daily data for image annotation projects includes five core document types: annotation specification documents, bounding box sample images, quality inspection reports, rework lists, and annotation script version records. Data sources include image samples exported from annotation platforms, bounding box coordinate data submitted by annotators, category dictionaries maintained by algorithm teams, annotation script version records, and spot check results generated by quality inspectors. Data updates follow a daily cycle or per batch annotation task cycle. Each single data entry includes fields such as unique image identifier, bounding box pixel coordinates, target category label, quality inspection judgment result, rework description, and script version number. There are no unified fixed units; adjustments are made based on specific annotation scenarios.
Constraints on Citation and Traceability
The multi-type data and high-frequency update characteristics of image annotation projects create multiple constraints for the citation traceability process. In the code and change review assistance scenario, teams must also associate annotation script versions with data batches to ensure cited annotation data matches the current code version during review. First, data includes both text-based specification documents and multimedia image samples. Cross-modal source association must be supported to ensure retrieval results match both annotation rules and visual reference materials. Second, daily or batch-level update rhythms require the traceability process to accurately bind the latest annotation data for the current task. This avoids citing expired old bounding box samples or quality inspection standards. Third, each single data entry includes granular fields such as pixel coordinates and batch identifiers. Field-level association must be retained during traceability to ensure cited annotation results can be traced back to specific annotators and task batches.
How to Configure
The following configurations follow official specifications for FastGPT v4.17.0.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
quoteMaxToken | 1200–1800 token | Covers the total content length of annotation specifications, bounding box instructions, and quality inspection reports, preventing truncation of critical traceability information |
detail | Enabled | Retains the original storage path of annotation images and the specific entry number of quality inspection reports to support precise traceability |
responseData | Return only specified fields | Limits returned core traceability fields such as unique image identifier, annotation batch number, and rework reason |
| Single recall limit | Top 4 entries | Matches the typical sample count for a single batch annotation task, avoiding retrieval of irrelevant historical batch data |
| Maximum context | Calibrated via actual testing | Adapts to knowledge bases of different-sized annotation teams, preventing retrieval exceptions caused by context overflow |
Three Common Misconfigurations
- After completing configuration, clicking test prompts an error, but the citation function works normally during formal operation. The root cause is that the test process does not correctly load the full batch data of the annotation team and associated annotation script versions. Only basic parameter formatting is verified, and full retrieval logic is not activated.
- The knowledge base retrieval result only returns 1 document, and cannot match multi-batch annotation data. The root cause is that the single recall limit is configured too low, or batch-level associated retrieval is not enabled. This results in only the currently active single batch data being recalled.
- After importing a JSON-formatted knowledge base, the available knowledge base list is empty, and the target library must be manually selected. The root cause is that the field filtering rule for
responseDatais not configured. This causes the system to fail to recognize the annotation batch identifier field in the JSON, and cannot automatically bind the target knowledge base.
How to Confirm Proper Configuration
- Upload a single annotation specification document, and check whether the returned results include the original citation path and version information of the document after retrieval.
- Submit a query containing bounding box coordinates, and confirm that the returned results are associated with the corresponding image samples and category dictionary entries.
- Import multi-batch annotation data, and verify whether the retrieval results cover multiple batches of annotation tasks and only match the currently configured task range.
- Trigger the test process, confirm that there are no error prompts, and the returned traceability fields align with the configured restriction rules.
The values provided are common starting points and should be evaluated 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.