What data in this category looks like
This category of data primarily comes from local public data open platforms, integrated big data platforms, departmental business databases, and electronic credential repositories. Daily generated documents include public data resource catalogs, data opening lists, data item descriptions, desensitization rules, interface documents, and update frequency descriptions. Each individual document mainly uses structured fields, including data resource name, unique identifier, data format, desensitization requirements, opening conditions, update cycle, interface address, and other content. The update frequency is once per month.
What constraints do these characteristics impose on workflow orchestration
Dispersed data sources, mostly cross-departmental systems, require workflows to support flexible configuration of multi-source data pull nodes. The monthly update rhythm requires workflows to have configurable scheduled trigger mechanisms to avoid repeated manual startup. Structured documents include multiple types of mandatory verification fields, requiring field integrity verification nodes to be embedded in the process. Desensitization rules and opening conditions are mandatory compliance requirements, so verification logic must be implemented as standalone workflow nodes. The existence of interface documents requires workflows to support standardized API call configuration to ensure compliance with calls to data opening interfaces.
How to set configurations
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Scheduled trigger cycle | 1st day of each month, 00:00-02:00 | Matches the monthly data update rhythm, avoids business peak hours |
| Multi-source data source binding | Bind two types of sources: local public data open platforms and departmental business databases | Covers the core data sources for this category |
| Field verification rules | Verify three mandatory fields: data name, unique identifier, desensitization requirements | Aligns with the core field requirements for structured documents |
variables variable configuration | Configure desensitization rule code and opening condition type as global variables | Reuses compliance verification logic, reduces repeated configuration |
nodeId node identifier | Assign unique identifiers to data pull, verification, and export nodes | Facilitates process debugging and log localization |
| Single API call limit | Top 10 data items | Controls the volume of data processed in a single run to avoid timeouts |
Three common mistakes
- Phenomenon: Workflows cannot be embedded into existing robots, and can only be created as standalone workflows. Cause: Workflow mounting permission was not enabled in robot configuration, and the node entry corresponding to
nodeIdwas not correctly associated. - Phenomenon: After importing someone else's JSON workflow, the text processing module cannot be found in the local interface. Cause: The local FastGPT version does not have the corresponding plugin package installed, or the imported module dependencies were not configured synchronously.
- Phenomenon: Workflow execution returns results that exceed the preset token limit. Cause: The
variablescontext truncation parameter was not configured, or the number of data items searched in a single run exceeds the system token bearing threshold.
How to confirm that the configuration is correct
- Trigger a test workflow, check if the logs of each node display the pull results of the corresponding data source, and confirm that the data source binding is correct.
- After the verification node is triggered, view the returned field verification results, and confirm that the verification logic for mandatory fields is working properly.
- Export the workflow JSON file, check that the configurations for
variablesandnodeIdmatch the local settings, and confirm that the export process is working normally. - Simulate a monthly update trigger scenario, confirm that the scheduled task trigger time matches the expected value, with no delays or missed triggers.
The values provided 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.