What the data for this category looks like
Ledger data for refined petroleum product sales comes from gas station POS transaction systems, oil tank level monitoring systems, inventory management systems, and tax declaration modules. Data is synchronized in real time for individual transactions. A daily summary table is generated after daily closing, and full site inventory updates are completed at the end of each month. Individual transaction documents include fields such as product number, sales volume (liters/tonnes), sales unit price (yuan/liter/tonne), actual received amount (yuan), transaction time, gas station code, and payment method. Batch summary documents aggregate corresponding fields by site and cycle, and field units strictly match general measurement standards for petroleum product transactions.
What constraints these characteristics impose on workflow orchestration
Multi-source real-time and periodic updated data for refined petroleum product sales requires workflows to support both real-time triggering and scheduled batch task modes. The need to connect multiple system data sources requires workflows to have cross-interface data pulling and format conversion capabilities. Fields include clear units of measurement (liters, tonnes, yuan), which requires workflows to have built-in unit verification and unified conversion nodes to avoid unit confusion in ledger summaries. The fixed monthly summary report generation cycle requires workflows to support scheduled triggering rules configured by natural day or natural month, and to adapt to the scale of batch data aggregation for single or multiple sites.
How to set configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
| Single data source pull volume | 800–1000 records | Matches the average daily transaction record scale of a single gas station, avoids pulling overload |
| Global variable configuration | Preset variables to product code, gas station ID, revenue threshold | Reuse fixed business parameters across nodes to reduce repeated entry |
| Node timeout period | 600 seconds | Adapts to the interface response duration for pulling POS and inventory data across systems |
| Knowledge base search reference upper limit | 30–50 entries | Controls token consumption per round of calls, matches the information density of ledger fields |
| Text processing module parameters | Set field splitting granularity to 100–200 characters | Adapts to the length of individual transaction fields in refined petroleum product sales ledgers |
| Workflow triggering rule | Trigger at daily closing time | Matches the daily summary business cycle of refined petroleum product sales |
Three common mistakes
- After importing another person’s JSON workflow, the text processing module option is not available in the local workflow panel. The cause is that the text processing module for FastGPT v4.17.0 must be enabled in the professional version workflow plugin, and this component is not loaded in the basic version workflow panel.
- After setting the knowledge base search reference upper limit to 2000, the generated report prompts that the token limit has been exceeded. The cause is that individual records in refined petroleum product sales ledgers have many fields and high information density, and 2000 references will far exceed the context window of general large models.
- After exporting the workflow JSON file, an error indicating missing node configuration is prompted when importing again. The cause is that complete dependencies were not checked during export, and the
nodeIdparameter and connection configuration between nodes were omitted.
How to confirm the configuration is correct
- Trigger a test workflow, check whether the number of pulled records in the node log matches the preset single pull upper limit.
- Run a test node that includes the text processing module, confirm that the field splitting and unit conversion functions work properly.
- Export the workflow JSON file, import it into the test environment, verify that all nodes and connections are not lost.
- Submit test ledger data, check that the field units and numerical calculation results in the generated report match the original data.
The values provided are common starting points and should be measured against the reader's own samples.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-09-28.