What data in this category looks like
This category of data primarily comes from enterprise databases, data dictionaries, data masking tools, and access approval systems. Updates follow the cycle of each project batch or individual task. Daily produced documents include masking plans, field mapping tables, masking verification reports, and approval records. Data fields cover sensitive field identifiers, masking rule parameters, verification results, and approval statuses. There are no fixed uniform units; values adjust based on project configuration.
How These Characteristics Impact Citation Sources and Traceability
Data sources are scattered and updated per project. Traceability must link to approval and verification records for the corresponding project to avoid cross-project citation failure. Diverse document types require retrieval logic adapted to different formats, to ensure core files such as field mapping tables and masking reports can be accurately located. Update frequency is not fixed, so support for triggering index updates per project batch is required to prevent referencing outdated masking rules. Sensitive field identifiers and rule parameters must be accurately bound to traceability information to avoid confusion between masking configurations from different projects.
Configuration Settings
These settings are based on FastGPT v4.17.0.
| Configuration Item | Recommended Value Range | Rationale |
|---|---|---|
quoteMaxToken | 6000–10000 token | Matches the average total length of single-batch masking documents to avoid truncating core traceability information |
detail | Enabled | Displays specific content of masking verification reports and approval statuses |
responseData | Structured return | Adapts to the parsing requirements of code review tools for masking rules and approval records |
| Number of citation results | Top 3–5 entries | Core citation content for masking projects is concentrated; excessive entries will disrupt review logic |
| Timeout threshold | 300 seconds | Adapts to retrieval latency for batch masking data |
| Index update trigger | Per project batch | Matches the data update rhythm of this category per project |
Three Common Misconfigurations
- Retrieval results only return irrelevant access approval records and fail to match the required masking field mapping tables. This occurs when the number of citation results is set too low, so core documents are not included in the retrieval scope.
- Masking rule content returned by retrieval is truncated, with key masking parameters missing. This occurs when
quoteMaxTokenis set too small and does not cover the total length of single-batch masking documents. - Uploaded masking verification reports show training errors, and duplicate old version entries still appear during retrieval after re-uploading. This occurs when old abnormal index entries are not cleaned up, and the system does not automatically perform full deduplication.
How to Verify Proper Configuration
- Review the traceability information of retrieval results to confirm whether source identifiers for core documents such as masking plans and field mapping tables are included.
- Test interface calls to check whether the returned
responseDataformat meets preset structured requirements. - Submit a test code review request to confirm whether the returned content displays the masking verification details corresponding to the
detailparameter. - Adjust the value of
quoteMaxTokento verify that retrieval content is not truncated for key masking rule information.
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.