What this category of data looks like
The data for this category comes from PLM, ERP, MES, supplier materials, validation tests, and customer-specific requirements. Updates are triggered irregularly with each change. Daily output documents include ECN/ECR, change assessments, drawings and BOM versions, process validation reports, switching plans, inventory disposal lists, customer approval documents, and similar items. Each individual document contains unique fields such as change number, associated bill of materials, approval node records, and effective time. There is no fixed batch update rhythm.
What constraints these characteristics impose on the "workflow orchestration" link
Data sources cover multiple production systems and external materials. Workflow orchestration must support cross-data source node calls, and pull rules for each system’s data must be pre-configured. Daily document types are diverse, with unique field requirements for each type. The workflow must configure corresponding field verification logic for different document nodes to ensure output content complies with format specifications. Change triggers have no fixed cycle. The workflow must support on-demand startup to adapt to the rapid response needs of temporary changes. Cross-departmental collaboration processes require the workflow to support configurable multi-role approval nodes. These nodes trigger approval actions in sequence according to change stages to avoid process stagnation.
Configuration Settings
These configuration instructions apply to FastGPT v4.17.0.
| Configuration Item | Recommended Approach | Basis for This Approach |
|---|---|---|
variables | Bind change number, BOM version number, and effective time fields | Match the identification and time requirements of core documents such as ECN/ECR |
nodeId | Arrange execution order sequentially according to change stages | Adapt to the process logic from data pulling, approval to document generation |
| Timeout threshold | 1200 seconds | Cover the average time consumption of cross-system data pulling and multi-role approval |
| Field verification rules | Configure required items according to document type | Ensure that output process documents and exception reports comply with business formats |
| Node retry count | 3 times | Cover the failure retry requirements of a single cross-system call |
Three Common Mistakes
- Phenomenon: After configuring multiple tool nodes in the workflow, some nodes do not trigger execution, and the execution order does not match the preset. Cause: The execution order of
nodeIdis not arranged according to the sequential logic of the change process, resulting in chaotic node trigger logic. - Phenomenon: After deploying via docker-compose, the workflow list and knowledge base content display blank, but interface calls can return normal results. Cause: Local cache files are not configured with persistent mounting, and cache data is lost after container restart or update.
- Phenomenon: When configuring variable references in the knowledge base search node, the returned results do not match the expected knowledge base content. Cause: The search keywords or screening conditions required for the search are not correctly bound via
variables, resulting in incorrect variable transmission.
How to Confirm the Configuration is Correct
- Manually trigger a test change process, check the execution logs of each tool node, and confirm that the node execution order matches the preset logic.
- Check whether the fields bound by
variablesmatch the core information of the current test change, and confirm that variable transmission is normal. - Trigger the process after intentionally omitting the required fields of a certain type of document, and confirm that the system intercepts abnormal submissions.
- Check the workflow's timeout records, and confirm that the time consumption of a single process meets the preset threshold range.
The values provided are common starting points and should be measured against the reader's own samples.