What this category of data looks like
Data for this category primarily comes from ERP/WMS systems, barcode or RFID collection devices, procurement and production work orders, warehouse location management modules, AGV or conveyor control systems, and weighing equipment. Daily generated documents include receiving slips, putaway slips, material picking and return slips, warehouse transfer slips, inventory count sheets, lot ledgers, first-in first-out (FIFO) and expiration date records. Data update rhythms cover three categories: real-time (such as scanned receiving), daily (such as same-day inventory summary), and monthly inventory. Common data fields include material code, lot number, warehouse location ID, expiration date, inbound/outbound quantity, and inspection status. Units are mostly physical measurement standards such as pieces, kilograms, and cubic meters.
What constraints these characteristics impose on workflow orchestration
Scattered data sources and varying update rhythms require workflows to support parallel pulling from multiple data sources and time alignment. Strict validation requirements for lot and expiration date fields mean workflows must include built-in field validation nodes to block non-compliant ledger data. Cross-process material location tracking requires workflows to link work order and warehouse location management data to ensure process flow traceability of ledgers. Discrepancy handling between book and physical inventory requires workflows to integrate inventory count data and real-time inventory data to generate discrepancy investigation nodes. Ununiform formats of multiple business document types require workflows to adapt parsing logic for different document structures.
How to set up the configuration
The following configurations are based on FastGPT v4.17.0.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
variables | Preset three core variables: material code, lot number, warehouse location ID. Supports up to 15 custom variables | Adapts to multi-field validation and cross-node data transfer requirements for warehousing scenarios |
| Node timeout setting | 600 seconds | Data pulling for this category involves integration with multiple systems. Typical interface response time ranges from 300 to 500 seconds, with reasonable buffer reserved |
nodeId | Bind a unique nodeId to each data source node | Facilitates precise location of faulty nodes during workflow exceptions and avoids data confusion |
| Field validation rules | Set lot number, expiration date, and material code as required fields. Validate expiration date format as YYYY-MM-DD | Prevents invalid ledger data from entering the summary process and ensures report accuracy |
| Data source pulling frequency | Real-time data source pulling interval: 10 seconds. Daily summary task pulling interval: 86400 seconds. Monthly inventory task pulling interval: 2592000 seconds | Matches the update rhythms of different data in this category and reduces invalid requests |
| Exception retry count | 3 times | Covers temporary faults such as common network fluctuations during warehousing data pulling |
Three common mistakes
- Front-end interface becomes unresponsive or crashes when calling workflow APIs to process batch ledger tasks. No sharding handling configured for batch tasks in
variables, leading to excessive single-node load. - Cannot reuse globally configured external API authentication information in workflows. Global authentication variables in
variablesare not preset correctly, requiring manual parameter configuration for each call. - Number of returned results does not match actual ledger entries when linking lot data in workflows. Unique
nodeIdis not bound to distinguish pulling results from different data sources, leading to data duplication or omission.
How to confirm the configuration is correct
- Manually trigger the workflow, check node logs to confirm that preset variables in
variableshave loaded correctly. - Simulate a single data source pull, check if returned fields comply with preset validation rules.
- Run a batch task, verify that the ledger summary data generated by the workflow matches manually counted basic data.
- View the workflow exception monitoring panel to confirm that node timeout and retry configurations have taken effect.
The values provided are common starting points and should be measured against the reader's own samples.