What the data for this category looks like
Daily documents for this category include maintenance plans, inspection logs, defect disposal forms, road construction permits, and road damage compensation forms. Data sources include highway maintenance management systems, bridge and tunnel monitoring systems, road administration inspection systems, and traffic flow monitoring data. The update frequency is daily. Common data fields include facility number, inspection time, defect type, disposal progress, and road-related matter type. Units are typically physical units such as kilometers, square meters, and items. Document structures primarily use structured form records and running ledgers.
Constraints on Forms and Interactions From These Characteristics
The scale of structured data updated daily requires forms to support batch import and field mapping. This reduces the probability of errors from manual entry. Physical unit fields need preset standard options to avoid unit confusion in entries. Forms for road construction permits and road damage compensation forms must link to approval process nodes. This ensures traceability in the interaction link. Inspection logs and defect disposal forms require multi-field linkage, so forms need to support conditional display logic. The logic automatically loads corresponding disposal items based on defect type. Most data sources are internal business systems, so forms need to support pulling data via existing system APIs. This reduces duplicate entry work.
Configuration Settings
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Approach | Rationale |
|---|---|---|
formInput field configuration | Add each document field such as maintenance plans and inspection logs one by one. Inspection time and facility number are required fields, with a character length limit of under 200 characters | Ensure the data collected by the form aligns with daily business ledger fields, to meet the material call requirements of party building learning Q&A |
userSelect option configuration | Preset options for defect type and road-related matter type. Each option has a character length limit of under 50 characters | Unify option formats, avoid ambiguous expressions during Q&A, and improve retrieval accuracy |
| Batch import configuration | Support importing CSV format files, with a single import limit of 1000 entries | Adapt to daily updated batch data import requirements, reduce manual entry workload |
| Conditional display configuration | Display the disposal progress and disposal personnel fields when "defect disposal" is selected | Match the field linkage logic of inspection logs and defect disposal forms, simplify the entry process |
| Submission timeout setting | Set the single form submission timeout to 30 seconds | Adapt to the interface response rhythm of internal business systems, avoid submission failures |
Three Common Configuration Mistakes
- Symptom: The interface displays the error "Cannot convert undefined or null to object" after the form is filled and submitted. Cause: No validation rules are configured for required fields. Empty fields during submission prevent generation of valid interaction data.
- Symptom: The party building learning Q&A cannot call the latest maintenance data submitted by the form. Cause: Real-time synchronization between the form and the knowledge base is not enabled. The Q&A uses historical cached data.
- Symptom: Filled content cannot be used as an input parameter for subsequent AI conversations after form submission. Cause: The association between form output and workflow nodes is not bound. Data is not passed to subsequent AI processing links.
How to Verify Successful Configuration
- Manually fill in a test data entry, submit it, and check the workflow log to confirm all required fields have valid content.
- Trigger the form's conditional display logic, select different business types, and confirm that corresponding fields display or hide as configured.
- Import test data that matches the preset format, confirm the import process has no errors and field mapping is correct.
- Trigger the party building learning Q&A function, confirm that business data submitted via the form can be retrieved and included in the Q&A context.
The values provided here are common starting points, and should be evaluated against sample data appropriate for the specific deployment.
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.