What this category of data looks like
This category of data primarily comes from engineering quality and safety supervision systems, construction site real-name management platforms, supervision logs, and test reports. The update frequency is weekly. Commonly processed documents include supervision plans, supervision inspection records, hidden danger rectification notices, quality problem handling forms, and completion acceptance supervision reports. Most document fields include project numbers, responsible entities, rectification deadlines, and acceptance milestones. Field structures vary across different document types, with no unified fixed cross-document field format. Corresponding fields must be matched based on individual document types.
What constraints do these characteristics impose on workflow orchestration
Weekly updated data volume requires workflows to support scheduled batch data pulling. This prevents node timeouts caused by processing excessive data in a single run. Non-unified field structures across multiple document types require workflows to use configured field mapping rules. This adapts to field differences between different documents. Scattered data sources across multiple systems require workflows to integrate nodes from different data sources. This unifies data input formats. Requirements for tracking closed-loop hidden danger rectification require workflows to include branch judgment nodes for state transitions. This links matching logic between rectification notices and review records. Requirements for verifying completion acceptance supervision reports require workflows to include multi-node result verification steps. This ensures data aligns with policy requirements.
Configuration Settings
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
variables | Define field variables by project | Adapt to storage and invocation of full-process data for a single project |
| Single data pull limit | Top 200 entries | Match weekly updated data volume, avoid node timeouts |
| Field mapping rules | Match corresponding fields by document type | Adapt to non-unified field structures across multiple document types |
nodeId | Bind core nodes for each stage | Ensure correct flow logic between workflow nodes |
| Timeout threshold | 600 seconds | Match time limits for single-batch data processing |
| Scheduled trigger interval | 7 days | Match the weekly update frequency of data |
| Timeout retry count | 3 times | Address occasional exceptions during single data pulling or parsing |
Three common configuration errors
- Symptom: Workflow debugging and verification fails. The interface prompts to check whether nodes have correctly filled values and whether connections are normal. Even the simplest two-node workflow cannot run. Cause: Initial values for
variablesare not configured correctly, or node connections do not follow the correct output-to-input flow direction. - Symptom: Content extraction nodes cannot call custom model interfaces. No return results after configuration. Cause: Interface parameters are not configured in the format required by the platform, and model call permissions for the corresponding node are not enabled.
- Symptom: Field parsing errors or node errors occur when the workflow processes documents containing special characters such as double quotes. Cause: No special character escaping step is configured, which causes text format to break the node's input verification rules.
How to verify correct configuration
- Run a single manual trigger of the workflow, check whether input and output fields of each node match the expected format.
- View the scheduled trigger logs of the workflow, confirm that the volume of pulled data and update frequency match the set requirements.
- Simulate the state transition of hidden danger rectification, verify whether the branch judgment node correctly triggers the corresponding processing logic.
- Import test documents containing special characters, confirm that no format errors occur during the parsing stage.
The values provided here are common starting points, and should be evaluated against samples specific to the actual use case.
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.