What data for this category looks like
Data for this category comes from PLM, ERP, MES, supplier materials, validation tests, and customer-specific requirements. Updates are triggered by each change, with no fixed schedule. Daily documents include ECN/ECR, change assessment forms, drawing and BOM version records, process validation reports, production switching plans, inventory disposal documents, and customer approval documents. Core fields include change number, version number, effective time, impact scope, and validation status. Common units are version numbers, days, quantities, and similar units.
What constraints do these characteristics impose on the workflow orchestration link
Multi-source data access requires workflow configuration to include cross-system data pull nodes, to ensure real-time synchronization of change information. There are many document types with no fixed update schedule, so branch trigger logic must be configured based on change categories to avoid executing invalid nodes. Core fields such as effective time and validation status require mandatory validation to prevent unvalidated changes from entering production. Identifying the impact scope of changes requires multi-node linkage, so dependency relationships between nodes must be configured to ensure each step of validation is completed before proceeding. Long document content may trigger AI input limits, so length validation nodes must be configured in advance to block abnormal input.
How to set configurations
This configuration is based on FastGPT v4.17.0:
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Maximum Context | 800–1200 characters | Matches the typical length of documents such as ECN/ECR, to avoid triggering input limit errors |
| Variable Reference | Bind by knowledge base document fields | Accurately call change version information from PLM and BOM, to avoid reference errors |
| Single Search Limit | Top 6 entries | Covers document types associated with core changes, reduces loading of invalid information |
| Timeout Threshold | 300–600 seconds | Adapts to the duration of different change processes, prevents long processes from getting stuck |
| Branch Trigger Rule | Judge change type in variables | Differentiates ECR and ECN scenarios, configures corresponding validation logic |
| Popup Submission Configuration | Bind submit button to the node corresponding to nodeId | Enables users to click to trigger the change validation process, aligns with team approval habits |
Three common misconfigurations
- An "input length exceeds limit" error occurs during workflow execution without triggering the block. The cause is that the maximum context threshold is not configured, or the threshold is set beyond the actual support range of the current AI model version.
- Knowledge base search results cannot correctly reference fields bound by variables. The cause is that variable mapping is not configured according to the field names of change documents, leading to a mismatch between the fields called during search and the fields actually stored.
- No popup submission node is configured in the workflow, so users cannot trigger the approval process. The cause is that
nodeIdis not bound to the popup button, so clicking the button does not trigger the corresponding node for execution.
How to confirm the configuration is complete
- Upload an ECN document to trigger the corresponding workflow, check whether an error is reported and the process is terminated when the input length exceeds the limit.
- After configuring variable references, insert a knowledge base search node in the workflow, verify whether the search results correctly call BOM version information from PLM.
- Edit the workflow to add a popup submission node, bind the corresponding
nodeId, test whether clicking the button triggers the specified validation step. - Switch documents of different change types, check whether the workflow executes the corresponding validation steps according to the configured branch logic.
The values provided are common starting points and should be measured against the reader's own samples.