What This Category of Data Looks Like
This data is maintained daily by data governance teams, security consultants, and legal compliance teams. Core documents include data catalogs, classification and grading rules, critical data identification tables, and review minutes. Data sources include data asset inventory results, database metadata, business system documentation, and public regulatory documents. Update frequency follows a quarterly cycle or occurs when a business system changes. Data fields include asset identifiers, sensitivity levels, affiliated systems, compliance requirements, and other items. There are no uniform fixed units; adjustments are made based on specific business scenarios.
Constraints Imposed on Forms and Interactions by These Characteristics
Multi-source data sources must connect to external business systems to enable cross-source data association and import, eliminating manual duplicate entry. Forms only collect input information. The quarterly or change-triggered update frequency requires external business systems to implement version recording functions, supporting historical configuration review. The diversity of data fields requires external business systems to implement grouped display by document type, reducing operational complexity. Severe potential error consequences require configuring required field validation for FastGPT form input nodes. Real-time prompt functionality must be implemented separately by external business systems, reducing risks of missed data management or permission errors. Differences from personal information protection compliance categories require excluding personal information-related exclusive fields when configuring FastGPT form input nodes, focusing on non-personal information data assets. This page’s configuration is based on the interaction logic of FastGPT v4.17.0.
Configuration Settings
| Configuration Item | Recommended Approach | Rationale |
|---|---|---|
Form input node formInput | Test example: Select 3 fields from data security classification and grading as required inputs; actual fields are determined per task | This node collects user input; missing required fields require checking interaction status to prevent subsequent nodes from receiving incomplete input |
User selection node userSelect | Test example: Set 2 business options, verify corresponding branches one by one | This node handles user selection; queries and filtering of data security classification and grading related records must be implemented by subsequent interfaces or external systems |
| Post-submission field passing | Test example: Prepare 10 data security classification and grading input samples, covering fully completed entries, missing required fields, and canceled operations | Compare input and node output to confirm whether subsequent nodes receive corresponding fields; result thresholds are determined per actual task |
| External implementation item: Review group selection configuration | Must be implemented separately by external systems; userSelect single-select group | Matches collaboration requirements for review minutes |
| External implementation item: Field validation rules | Must be implemented separately by external systems; test example: Force required fields for data asset ID and sensitivity level | Prevent missed management of critical data, aligning with potential error consequences |
| External implementation item: Version recording configuration | Must be implemented separately by external systems; must be implemented by external business systems | Adapts to quarterly updates or update frequency triggered by business system changes |
Three Common Misconfigurations
- Symptom: Form dialog boxes always display in nested workflows, but behave normally in single workflows. Verification steps: Check workflow interaction context configuration, confirm whether scenarios for independent workflows and nested applications are distinguished, and adjust related configurations.
- Symptom: Field empty error prompts appear after form submission. Verification steps: Check the required field configuration of FastGPT form input nodes, confirm whether it matches the required field requirements of data catalogs and critical data identification tables, and verify the error prompt logic of external business systems.
- Symptom: Form submission times out, returning a request failure status code. Verification steps: Check form submission timeout configuration, confirm whether it adapts to complex calculation delays in classification and grading rule reviews, and adjust related parameters.
How to Confirm Successful Configuration
- Connect to external business systems to test cross-source data association and import functions, confirm that data source characteristics can be matched.
- Trigger the form in a nested workflow, confirm that the dialog box display status meets expectations, and adjust external interaction trigger rules.
- Submit a form with all required fields, confirm that no field empty errors occur, and verify that validation rule configurations are correct.
- Test submission delay scenarios, confirm that timeout settings adapt to business requirements, and adjust external configuration parameters to match actual operating conditions.
- Use
userSelectto configure review groups, confirm that the collaboration process can normally trigger review minute generation.
The values provided here 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.