What the Data for This Category Looks Like
The data for text annotation projects mainly comes from client-provided business corpora, annotation results exported from annotation platforms, custom business vocabularies, and quality inspection sampling reports. Data update frequency is either daily synchronization or updates after each batch of annotation tasks is completed. Daily produced documents include annotation specification manuals, annotation sample packages, quality inspection reports, and problem feedback forms. Common data fields include annotated text content, entity/intent tag values, annotator identifiers, quality inspection results, and conversation interaction timestamps. The character length of a single annotation sample covers scenarios ranging from short texts to long documents.
What Constraints These Characteristics Impose on the "Conversation Logs and Auditing" Link
Multi-source data sources require conversation logs to be associated with different identifiers from annotation tasks, annotation samples, and quality inspection links to avoid cross-task confusion. The high-frequency update feature requires log collection to support real-time synchronization of the latest annotation and quality inspection interaction content to ensure the timeliness of audit data. Diverse document types require the log module to classify and store data by annotation task dimension, enabling retrieval by annotation batch or quality inspection batch. The diversity of fields requires audit logs to cover the full link content such as annotation instructions, sample feedback, and arbitration communications to meet the traceability requirements of compliance reviews.
How to Configure the Settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
chatId | Bound to annotation task ID | Associates all conversation logs under a single task to avoid confusion of log data across tasks |
responseChatItemId | Bound to the unique identifier of the annotation sample | Accurately locates audit conversations for a single annotation sample, making it easy to trace the processing process of a specific sample |
detail | Enable full log collection | Covers complete conversation content including annotation specification explanations, sample arbitration, and quality inspection feedback to meet compliance audit requirements |
| Single context recall limit | Top 10 conversation records | The context for text annotation is mostly instructions and sample feedback; 10 records are sufficient to cover the complete communication link, calibrated based on actual testing |
| Single batch log export size | 1000 MB per batch | Adapts to the batch data export needs of annotation teams, avoiding transmission failures caused by overly large single files |
| Session timeout threshold | 600 seconds | Adapts to the long-duration communication scenarios of annotation teams, avoiding interruptions to log collection mid-session |
Three Common Configuration Mistakes
- Phenomenon: Only a single conversation in the current session is retrieved after configuration, and complete annotation communication history cannot be obtained. Cause: The
chatIdparameter is not bound, or the bound task ID does not match the actual annotation task. - Phenomenon: After adjusting the context recall count, audit logs still do not display historical annotation instructions. Cause: The
detailfull collection configuration is not enabled, only core result fields are retained, and complete interaction content is not recorded. - Phenomenon: Conversation records from the quality inspection link are missing in exported logs, making compliance review impossible. Cause: The unique identifier of the annotation sample is not bound, and quality inspection conversations are not tied to the corresponding
responseChatItemId, resulting in scattered data that cannot be associated.
How to Verify the Configuration Is Correct
- Perform a complete communication test for a single annotation task, and check whether all interaction content is displayed in the log module of FastGPT v4.17.0.
- Export the log file for the specified task, and verify whether core fields such as annotation task ID, sample unique identifier, and conversation timestamp are included.
- Adjust the context recall parameter, and verify whether the number of conversation entries displayed in the logs matches the configured recall limit.
- Retrieve conversation records from the quality inspection link, and confirm that they are successfully associated with the
responseChatItemIdof the corresponding annotation sample.
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.