What the data for this category looks like
Daily documents for this category include process sheets, patterns, marker plans, cutting orders, first sample seals, process quality forms, and packaging size-matching lists. Data comes primarily from orders and size charts, CAD patterns, fabric and accessory inspection, hanging systems, needle detectors, and customer sample seals. Updates occur per order, per style, per batch. Single-batch data includes fields such as version parameters, process requirements, fabric batches, size ratios, and quality inspection records. Teams adjust fields and units based on the actual needs of each individual style.
What constraints these characteristics impose on workflow orchestration
The multi-style, high-update-frequency nature of this category requires workflows to bind dynamic variables to adapt to version parameters and process requirements for different individual styles. The irreversible nature of cut pieces requires teams to run data validation nodes early in the workflow to avoid invalid processing. Dense process steps and reliance on data from multiple systems require workflows to support cross-data-source calls. Teams must also split long workflows into multiple sub-nodes to avoid single-execution timeouts. The strong correlation between packaging size-matching lists and cutting orders requires configuring data transfer rules between workflow nodes. These rules ensure fields such as size ratios and fabric batches match without deviations, reducing the risk of wrong sizes and wrong cartons.
How to set up the configuration
Configuration reference for FastGPT v4.17.0 is as follows:
| Configuration Item | Recommended Approach | Rationale |
|---|---|---|
variables | Bind three core fields: order number, size chart, and fabric batch | Adapt to differentiated parameters for individual styles and meet the demand for rapid switching between multiple categories |
| Sub-workflow call node | Enable wait-for-completion mode, set timeout threshold to 180–300 seconds | Cover the execution duration of complex cutting and quality inspection links and avoid mid-execution disconnections |
nodeId | Configure a unique identifier for each data validation node | Facilitate troubleshooting of cross-node data transfer exceptions |
| Code execution node | Configure to return only structured JSON results, with output not exceeding 2000 characters | Ensure downstream nodes can directly read and process results and avoid incompatible content formats |
| Specified reply node | Turn off the AI reply generation switch and only output structured ledger data | Avoid redundant content interfering with ledger summary |
| Trigger rule | Bind the new order creation event and trigger per batch | Match the update rhythm of this category per order and per batch |
Three common misconfigurations
- After a sub-workflow is called, the main workflow shows execution completed but the sub-workflow does not generate complete ledger data. Cause: The wait-for-completion configuration of the sub-workflow is not enabled, or the timeout threshold is set lower than the actual execution duration of the sub-workflow.
- The code execution node has output, but the specified reply node cannot read the result. Cause: The content returned by the code execution node is not converted to a structured format, or it is not passed to downstream nodes via
variables. - After the workflow is triggered, only some nodes are executed and subsequent nodes do not respond. Cause: No data transfer rules are configured between nodes, and the upstream node output is empty, causing the downstream trigger condition to not be met.
How to confirm the configuration is correct
- Upload the pattern and process sheet of a test order, trigger the workflow, and check whether
variablesare correctly bound to order-related fields. - Manually trigger the sub-workflow and confirm that its execution duration meets the preset threshold and there is no mid-execution disconnection.
- Run a test workflow that includes code execution and specified reply nodes, and check whether the specified reply node outputs the structured results from the code execution.
- View the workflow logs to confirm that all nodes are executed in the preset order and there are no abnormal errors.
The values provided here are common starting points and should be measured against the reader's own samples.