What the data for this category looks like
The data for this category comes from four main sources: engineering quality and safety supervision systems, on-site construction real-name platforms, supervision logs, and test reports. Daily generated documents include supervision plans, supervision inspection records, hidden danger rectification notices, quality problem handling forms, and completion acceptance supervision reports. Each document has fixed fields: supervision plans include supervision dates, supervision scopes, and participating construction units. Supervision inspection records include inspection points, problem descriptions, and rectification time limits. Hidden danger rectification notices include rectification numbers, rectification contents, and responsible units. Data is updated weekly. A single summary covers all documents generated that week. Most field types are text, dates, and enumeration values. There are no complex nested structures.
Constraints on Workflow Orchestration from These Characteristics
The data for this category is multi-source and scattered, with weekly updates. This requires workflows to support connecting to multiple external systems to pull data, avoiding errors from manual entry. The fixed field structure requires workflows to configure unified field mapping rules. These rules convert heterogeneous data from different sources into standard ledger formats. The core requirement of tracking hidden danger rectification closed loops requires workflows to support variables for storing global states such as rectification status and acceptance progress, and passing data across nodes. The serious consequences of quality accidents require workflows to configure exception verification nodes. These nodes trigger alerts for missing fields or overdue data. The weekly summary frequency requires workflows to configure scheduled trigger mechanisms. These mechanisms automatically start execution at fixed intervals.
How to Set Configurations
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
variables | Isolated by user ID | Separates project data for different supervisors, preventing cross-user data confusion |
nodeId | Assign a unique identifier to each external data source node | Accurately matches data sources passed across nodes, ensuring correct data flow |
| Scheduled trigger cycle | Every Monday 09:00 | Matches the regular weekly data update window, aligning with daily supervision work rhythms |
| Global variable storage limit | 1000 MB | Stores weekly ledgers, rectification records, and acceptance data for a single quarter, meeting regular storage needs |
| Field mapping length | 800–1200 characters | Adapts to the regular text length of supervision documents, avoiding truncation of critical information |
| Exception verification threshold | Trigger an alert for the first 5 abnormal data entries | Prioritizes processing the most urgent missing fields or overdue data, reducing error risks |
Three Common Mistakes
- Symptom: After calling the workflow API, historical ledger data is not loaded, and the rectification status stored in
variablesis empty. Cause: Thevariablesparameter is not included in the API request, or the workflow's context loading node for reading historical global variables is not configured. - Symptom: Data pulled from multiple data source nodes overlaps incorrectly, resulting in chaotic final ledger data. Cause: A unique
nodeIdis not configured for each data source node, leading to failure to accurately identify sources during cross-node data transfer. - Symptom: No customized rectification guidance text is generated after the AI replies, only the default prompt is displayed. Cause: No customized guidance text generation step is configured after the workflow's AI reply node, relying on the system's default suggested questions feature.
How to Confirm the Configuration is Correct
- Manually trigger the workflow once. Verify that pulled data sources match the specified engineering quality and safety supervision system and supervision log data.
- Log in with different user IDs. Review global variables stored in
variablesto confirm data is isolated without crossover. - Simulate input of data source entries with missing fields. Verify that the preset exception alert mechanism is triggered.
- Wait for the scheduled trigger cycle to arrive. Confirm that the workflow starts automatically and generates the weekly ledger summary and report.
The values provided here are common starting points. They 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 2026-09-28.