What the data for this category looks like
Daily data in the mold design and manufacturing field includes structured and unstructured documents such as mold design task sheets, DFM reports, part drawings, processing technology cards, trial mold reports, mold modification notices, and mold history records. Data sources include customer product models, mold flow or forming simulation results, CAD/CAM design files, machining and measurement data, and records related to trial mold parts. Data updates follow project progress. New associated documents are generated after each trial mold or mold modification. Data from different projects is independent, with no unified cross-project data format.
What constraints these characteristics impose on workflow orchestration
Diverse document types require workflows to support parsing and associating multi-format data, to avoid information loss from format incompatibility. The update rhythm tied to projects and single trial mold or modification events requires workflow triggers to bind specific project events. This ensures traceability processes start automatically after data updates. Independent project data requires workflow variables to bind exclusive identifiers for the current project, preventing cross-project data confusion. Complex document structures and strict error consequences require workflows to include clear failure handling mechanisms and timely alerts for abnormal links.
How to set the configurations
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
variables | Bind the current project's mold ID and trial mold batch ID | Mold data is updated by project and trial mold batch; identifiers are needed to associate exclusive documents |
nodeId | Assign fixed 24-bit hexadecimal characters as the unique identifier | FastGPT requires compliant node identifier formats to ensure accurate cross-node calls |
| Trigger Timing | Bind events for trial mold report upload completion and mold modification notice release | Data updates concentrate in trial mold or mold modification stages, matching business rhythms |
| Context Window Length | 8000–12000 token | Mold documents include drawing descriptions, simulation parameters and other large volumes of content; sufficient context is needed to support analysis |
| Failure Retry Count | 2 times, 30-second interval | Network fluctuations may occur occasionally during machining data upload; retries can reduce exception probability |
| Knowledge Base Association Scope | Current project-exclusive knowledge base | Mold data is isolated by project to avoid cross-project data interfering with analysis results |
Three common misconfigurations
- Using
variablesin workflows with no selectable values, where global variables cannot be called normally. This occurs when global variable permissions are not enabled in project configuration, or variables are not bound to the context identifier of the current mold project. - An axioserror error appears when calling the workflow. This occurs when the
nodeIdformat does not meet requirements, node call permissions are not configured, or network connections have fluctuations. - The number of results returned after workflow execution does not match expectations, or the corresponding trial mold report cannot be associated. This occurs when
variablesare not bound to the correct project identifier, leading to incorrect data retrieval scope.
How to confirm the configuration is complete
- Enter the workflow editing page of FastGPT v4.17.0, and check that the
variablesconfiguration item is bound to the current project's mold ID and trial mold batch fields. - Copy the workflow ID generated on the workflow management page, and verify that it uses the 24-bit hexadecimal character format.
- Upload a simulated trial mold report to trigger the workflow, and check that the node execution log contains no axioserror errors.
- Check whether the binding relationship between the trigger rule and trial mold report upload, mold modification notice release matches the business process.
The values provided here are common starting points, and should be evaluated against the reader's own samples.