What data for this category looks like
Data for this category primarily comes from databases, data dictionaries, masking tools, and access approval systems. It is updated per batch or individual project. Daily deliverable documents include masking plans, field mapping tables, masking validation reports, and approval records. Core fields include sensitive field lists, masking rule codes, validation pass rates, approval status, and other relevant items. There are no unified fixed units. Values adjust based on project requirements. Core data processing steps center on sensitive field identification, rule configuration, and usability validation. A balance between data compliance and usability must be maintained.
What constraints these characteristics impose on multi-turn dialogue and prompt engineering
Data for this category is updated in project batches. Multi-turn dialogue must support binding to the current project’s exclusive data source and document collection. This prevents cross-project data confusion. Daily deliverable documents include multiple types of structured content. Prompts must adapt to formats of different documents such as field mapping tables and validation reports. They must explicitly specify reading specified types of document fragments. Sensitive field identification and rule configuration take significant time. This requires multi-turn dialogue to gradually guide users to supplement information. It reduces the complexity of single-turn inputs. Data compliance requirements are strict. Dialogue processes must avoid leaking original sensitive data. Automatic masking must be applied to field information passed during dialogue.
How to configure settings
| Configuration Item | Recommended Approach | Rationale |
|---|---|---|
chatId | Bind to the current project’s unique identifier | Ensures multi-turn dialogue context is tied to the current masking project, preventing cross-project data confusion |
messages | Only retain current project document fragments and user questions | Filters irrelevant historical dialogue, focusing on context for the current masking requirement |
variables | Only pass the current project’s field mapping tables and masking rules | Limits variable scope, reducing interference from invalid information |
| Maximum context length | 8000–12000 token | Adapts to the total length of multiple document types including masking plans and field mapping tables, avoids truncating critical configuration information, and aligns with the window limit of FastGPT v4.17.0 |
| Maximum single dialogue turns | 6 turns | Matches the typical workflow steps of sensitive field identification, rule configuration, and validation |
Three common configuration errors
- Dialogue fails to retrieve the current project’s masking field mapping table content. The symptom is the prompt returning "No valid field data found". Log checks show
variablesare not correctly bound to current project data. The root cause is failure to limit thevariablesconfiguration item to the current project’s fields and rules, so context cannot load the corresponding project’s document data. - Multi-turn dialogue continues interacting after exceeding the preset turn limit. The symptom is the system returning redundant historical dialogue fragments, leading to overly long prompts that harm accuracy. The root cause is failure to set a maximum single dialogue turn limit and filter expired non-project-related dialogue.
- Original sensitive data is leaked during dialogue. The symptom is returned content containing a user’s real phone number or ID number. The root cause is failure to enable automatic sensitive information masking configuration, and failure to perform compliance processing on field information passed during dialogue.
How to confirm configuration is complete
- Initiate a test dialogue, input "Generate the current project’s field mapping table". Check returned content to confirm it only includes valid fields for the current project, with no cross-project data.
- Review dialogue history records to confirm only interaction fragments related to the current project are retained, with no irrelevant historical content.
- Trigger a sensitive information masking test, input a question containing a simulated phone number. Check returned content to confirm the phone number is masked.
- Verify variable binding logic, input "View the current project’s masking rules". Check returned content to confirm it matches the preset masking 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.