What the data for this category looks like
Core data for rail transit equipment originates from workshop SCADA systems, maintenance work order systems, and human resource management systems. Update frequencies fall into three categories: real-time (equipment operating parameters), daily (work order completion statistics), and monthly (salary calculations). Document structures include unique equipment codes, maintenance timestamps, fault levels, processing durations, and spare parts requisition numbers. Field units include N·m, operating hours, person-times, and others. Employee data contains dedicated fields such as employee ID, job level, scheduling shifts, salary grades, and there is no universal standardized field template.
What constraints these characteristics impose on the "forms and interactions" link
The multi-dimensional data characteristics of rail transit equipment impose multiple constraints on the forms and interactions link. Real-time equipment parameters require dynamically linked fields: selecting a specific equipment code automatically loads corresponding maintenance parameter input items to avoid manual entry errors. Data with different update frequencies require differentiated data source calling methods: real-time operating data calls online interfaces, and monthly salary data uses batch-synchronized offline datasets. Fields come with professional units, so the interaction link must enforce unit verification to block non-compliant input content. Multi-field work order forms must be displayed in blocks according to business scenarios to reduce the cognitive burden of filling out. Permission grading for employee data requires automatic access permission verification during form interactions, only displaying content visible to the corresponding job position.
How to Set the Configuration
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
formInput field validation | Enable unit validation, bind unit rules such as N·m and operating hours | Adapt to the professional data format of rail transit equipment |
userSelect data source grouping | Divide data sources into 3 groups: maintenance, attendance, salary | Correspond to the three core types of business data |
formInput trigger condition | Trigger only after filling in the equipment code | Avoid invalid form submission requests |
| Timeout setting | 600 seconds | Adapt to the batch query time of large equipment ledgers |
| Single submission limit | Top 50 entries | Avoid interface exceptions caused by excessive single submission data volume |
| Input character limit | 800-1200 characters | Adapt to the conventional length of work order descriptions |
| Form block display | Split into 3 blocks according to business scenarios | Reduce the cognitive burden of single-page filling |
Three Common Mistakes
- Phenomenon: The conversation response includes more than 2 background knowledge entries, and the log shows that 10 matching pieces of data were recalled. Cause: The recall limit parameter of
userSelectis not configured, and the default full recall setting is used. - Phenomenon: The system pops up a "field format error" prompt when submitting the form, but the unit requirement is not specified. Cause: Unit validation rules are not configured for the professional fields of
formInput, so inputs that do not comply with rail transit equipment data specifications cannot be blocked. - Phenomenon: The plugin is triggered twice in a single conversation, and the interface displays two call records. Cause: The single conversation trigger limit for
formInputis not set, resulting in repeated matching of trigger conditions.
How to Confirm the Configuration is Complete
- Open the form editing interface, select the equipment torque field, and confirm that the input validation rule corresponding to the N·m unit has been bound.
- Submit a torque value without a unit, and confirm that the system returns a format error prompt.
- Initiate a conversation containing equipment maintenance queries, and check that the number of background knowledge entries in the response meets the preset requirements.
- Trigger a plugin call, and confirm that only one call is completed in a single conversation.
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 2026-09-28.