What This Type of Data Looks Like
The core data of image annotation projects comes from original image samples on the annotation platform, category dictionaries, bounding box results output by annotators, and quality inspection reports and rework lists generated by quality inspectors. Data updates follow a daily or single-batch annotation task cycle. Annotation data from different batches has a relatively fixed structure, usually including fields such as pixel coordinates of target bounding boxes, category labels, annotation time, and sampling inspection marks. Units are mostly pixels, category serial numbers, and similar values. Daily supporting documents include annotation specifications and bounding box example templates, used to unify annotation standards and defect judgment rules.
What Constraints Do These Characteristics Impose on Tool Calling and Plugins?
The data characteristics of image annotation projects impose clear constraints on tool calling and plugin configuration. First, pixel-level fields of image samples and annotation results require strict format verification during tool calling to avoid coordinate parameter deviations. Second, the daily or batch update rhythm requires plugins to adapt to batch trigger logic to avoid overloading single calls. Third, supporting annotation specifications and quality inspection reports require plugins to extract structured fields for automatically generating test cases and defect statistics. Finally, the independent data context of different batches requires tool calling to bind the category dictionary and annotation rules of the corresponding batch to avoid parameter confusion across batches.
How to Configure the Settings
This article adapts to the tool calling and plugin configuration logic of FastGPT v4.17.0. The specific configuration items are as follows:
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
toolChoice | auto | Adapts automatic tool selection logic for multiple types of image annotation tasks, matching the diversity of annotation tasks |
| Plugin trigger timing | After batch annotation is completed | Matches the daily or single-batch data update rhythm, avoiding repeated triggers |
| Single tool call limit | Top 10 entries | Controls the data volume of a single request to avoid interface timeouts |
| Timeout threshold | 600 seconds | Adapts to the tool call time consumption of large-size image annotations, meeting the processing needs of complex tasks |
functionCall parameter verification | Enable bounding box format verification | Matches the pixel coordinate field requirements of image annotation data, reducing the probability of format errors |
| Global variable binding | Bind by batch | Adapts to category dictionaries and annotation rules of different batches, ensuring context consistency |
Three Common Misconfigurations
- Phenomenon: Unexpected numeric prefixes (such as leading 0) appear in tool call return results, and the content does not match the model's original response. Cause: The parameter format of
functionCallis not configured correctly, causing the model to automatically generate redundant number prefixes. - Phenomenon: The display names in the system plugin list and the plugin list page in plugin management are inconsistent. The former is the internal code identifier, and the latter is the custom name. Cause: The display name and the internal unique code identifier are not filled in synchronously in the plugin configuration.
- Phenomenon: After setting specified reply content, the tool still automatically calls plugins to generate additional replies. Cause:
toolChoiceis not set tonone, and the model enables automatic tool call logic by default.
How to Verify Proper Configuration
- Upload a single test image with clear targets, trigger tool calling, and check whether the bounding box coordinate format of the returned result meets the pixel unit requirements.
- Enter the plugin management page, compare the display names in the system plugin list and the plugin list page, and confirm that they are consistent.
- Enable the specified reply mode, set
toolChoicetonone, submit a test request, and verify that only the preset specified content is returned. - Submit a batch of annotation data, check whether the tool call is only triggered after batch annotation is completed, and there are no repeated or missing call records.
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.