What the data for this category looks like
The data sources for elderly care service institution supervision usually include elderly care service information platforms, civil affairs statistics systems, fire inspection records, and institution operation ledgers. The data update frequency is monthly. Commonly used daily documents include filing materials, operation subsidy applications, service quality inspection forms, safety hazard rectification ledgers, and elderly admission files. Document fields usually include institution name, number of beds, filing number, number of service uses, rectification time limit, etc. There are no unified fixed units, and some fields need to match the format requirements of different source systems.
What constraints these characteristics impose on the workflow orchestration link
Differences in multi-source data formats require the workflow to add a field alignment step to unify field names and units returned by different systems. The monthly update rhythm requires the workflow to be configured with a scheduled trigger mechanism to match the reporting cycle of supervision data. The core time-consuming step is verifying filing and bed data, so the workflow needs to set up automatic verification nodes to reduce manual operations. Errors in the supervision process may lead to consequences such as incorrect subsidy distribution and safety accidents, so an abnormal alert link needs to be configured to intercept abnormal processes in a timely manner.
Configuration Settings
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
variables | Preset core field variables such as institution name, number of beds, filing number, etc. | Match the fixed field structure of supervision documents to simplify downstream node calls |
| HTTP request timeout | 30 seconds | Civil affairs system interface responses usually fall within the 10-20 second range, calibrated based on actual testing |
| JSONPath extraction configuration | Extract corresponding fields under data.list in the HTTP response | Match the subsidy application data structure returned by the elderly care service information platform |
| Database connection timeout | 600 seconds | Cross-regional civil affairs database synchronization delays usually fall within 5-10 minutes, with sufficient buffer time reserved |
| Workflow trigger timing | 0:00 on the 1st of each month | Match the regular reporting rhythm of monthly updated supervision data |
| Abnormal alert trigger | Bind the downstream node with nodeId as error | Push process exception information in a timely manner to prevent incorrect processes from continuing execution |
Three Common Mistakes
- Phenomenon: The JSONPath extraction result of the HTTP request node is not passed to the downstream node, and the downstream variable is empty. Cause: The extracted variable name was not declared in
variablesin advance, or the JSONPath expression did not match the target field in the response. - Phenomenon: The database connection node reports an error, and the log shows Failed to connect to jyfkk:1433. Cause: The instance name in the database connection string was configured incorrectly, and it does not match the actual deployed database instance address of the civil affairs system.
- Phenomenon: The classification results of the problem classification node do not meet the requirements of the supervision scenario, and it cannot correctly distinguish between filing change and safety hazard rectification materials. Cause: The background knowledge does not cover the exclusive classification tags for elderly care service supervision, and the common field features of supervision documents are not associated.
How to Confirm the Configuration Is Complete
- Trigger the test workflow, load the preset
variablesvariables, and check whether the field values match the sample data exported from the elderly care service information platform. - Run the database connection test node, confirm that no timeout error occurs when the connection timeout is set to 600 seconds, and that institution bed data can be queried.
- Verify the JSONPath extraction function, check whether the service quality inspection form generated downstream correctly uses the extracted number of beds field.
- Trigger an abnormal test scenario, confirm that the node with
nodeIdas error will trigger the alert process and push exception information in a timely manner.
The values given 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.