What Data Looks Like for This Category
Data sources for this category include raw and auxiliary material qualification certificates, ERP/MES systems, weighing systems, ovens or frying lines, laboratory equipment, and food traceability ledgers. Daily documents include formulas and feeding lists, production records, baking or steaming curves, metal detection records, cleaning and disinfection records, and factory inspection reports. Data is updated per batch, per shift, or daily. Core fields include allergen material lists, baking/frying window parameters, packaging dates, shelf life, and more. Full information for corresponding production links must be associated via batch numbers.
Constraints Imposed by These Characteristics on Workflow Orchestration
This category has multi-source, scattered data sources. Workflow orchestration must adapt to the formats and pulling logic of different systems to avoid audit interruptions caused by data format incompatibility. The per-batch or per-shift update rhythm requires workflows to support batch triggering, to align with real-time or per-batch production data update cycles. Frequent product line changes and diverse formula requirements mean workflows must support quick adjustment of parameters for nodes such as allergen verification and window control, without rebuilding the entire process. Severe error consequences require workflows to be configured with multi-step verification and exception handling links, to ensure problems are intercepted promptly during processing.
Configuration Guidelines
This configuration is based on FastGPT v4.17.0.
| Configuration Item | Recommended Approach | Rationale |
|---|---|---|
variables | {"batch_id": "", "allergen_list": []} | Matches the core requirement of batch management for baked convenience foods, and carries key parameters such as batch numbers and allergen material lists |
| Node Trigger Condition | Triggered by data source updates associated with nodeId | Adapts to the rhythm of multi-source data updates per batch or per shift, ensuring the audit process starts only after corresponding production data is generated |
| Subprocess Variable Sharing | Inherit outer global variables | Meets the requirement for shared core parameters such as batches and allergens between the outer process and nested subprocesses, avoiding repeated configuration |
| Exception Retry Count | 2 times | Addresses scenarios where production data reading is temporarily delayed, reducing unnecessary process interruptions |
| API Call Timeout | 300 seconds | Adapts to the time required to pull multi-source data such as baking curves and laboratory inspection reports |
| Single Knowledge Base Retrieval Limit | Top 5 entries | Focuses on core raw and auxiliary material qualification certificates and inspection reports, avoiding redundant results that interfere with the audit process |
Three Common Configuration Errors
- Phenomenon: Knowledge base referenced variables cannot be selected in code run nodes, and retrieval result fields are empty. Cause: Parameters for knowledge base-associated retrieval results were not pre-declared in the
variablesconfiguration, causing the node to fail to recognize the corresponding call fields. - Phenomenon: Workflow execution times out, returning a gateway timeout status code. Cause: The API call timeout setting value is too small, failing to accommodate the time required to pull complete multi-source data such as baking curves and laboratory inspection reports.
- Phenomenon: Nested subprocesses cannot access global variables from the outer process. Cause: The subprocess was not configured to inherit outer
variablesparameters, resulting in independent parameter pools for the subprocess and outer process.
How to Verify Proper Configuration
- Trigger a simulated batch audit process, and verify whether the batch number and allergen list parameters configured in
variablesare correctly passed to all nodes. - Call the API to create a test workflow, and confirm that node trigger conditions match the production data update rhythm.
- Launch a nested subprocess, and confirm that outer global variables are correctly inherited and function within the subprocess.
- Simulate a single knowledge base retrieval, and confirm that the number of returned results aligns with the configured retrieval limit.
The values provided are common starting points and should be evaluated against the reader's own samples.