What Data for This Category Looks Like
Shipping port yield rate data primarily originates from port production scheduling systems, container loading and unloading operation systems, and public maritime freight rate databases. The system updates data daily at midnight, synchronizing full statistical data for the previous calendar day, and exports the data as structured JSON or CSV documents. Core fields in these documents include port unique identifier, statistical date, loaded and discharged TEU volume, comprehensive revenue per container, average berth waiting time, and regional route benchmark freight rate. Corresponding units are TEU, RMB yuan, hours, yuan per standard container, and USD per 40-foot container respectively.
What Constraints Do These Characteristics Impose on Conversation Logging and Auditing
This category of data updates daily and includes multi-dimensional business fields. Conversation logs must be archived by calendar day to facilitate periodic audit verification. Multiple fields have dedicated units, so the audit process must verify the unit consistency of returned data to avoid unit conversion deviations affecting yield rate calculations. Data from multiple systems must include trace identifiers for the original operation system in logs, enabling quick tracing of the data chain during audits. Single data entries have multiple dimensions, so the number of entries carried in conversation context must be limited to prevent log overload from causing LLM call timeouts or response lag.
How to Set Configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
historyLogMaxCount | 50–100 entries | Shipping port data has multiple dimensions per entry. Excessive historical messages will trigger token limit violations. This range balances context completeness and call stability |
logRetentionDays | 365 days | Meets industry audit compliance retention requirements, enabling cross-period business log review |
workflowNodeTimeout | 600 seconds | Multi-system data pulling may have long-duration scenarios. This duration covers conventional data synchronization processes |
fieldUnitValidation | Enabled | Multiple fields have dedicated units. Requires verification that returned data units match query parameters to avoid calculation deviations |
maxContext | 8000–12000 tokens | Adapts to long context requirements for single-round queries carrying multi-dimensional port data, preventing truncation of critical business information |
auditTraceIdEnabled | Enabled | Associates trace identifiers for multi-system data sources, ensuring quick location of data traces and call sources during audits |
The parameter values provided on this page are common starting points for configuration. Actual values are affected by data format, data volume, and business rules. Specific issues require individual analysis. It is recommended to test on your own samples before finalizing settings.
Three Common Mistakes
- Issue: In version v4.8.14, when the workflow "Code Run" node input includes historical records, verification failure is triggered and execution cannot proceed. Cause: This version defaults to limiting the upper limit of
historyLogMaxCountto 50 entries, and the verification rule for custom configurations was not updated synchronously. - Issue: When calling a proprietary model, empty content is occasionally returned, the process gets stuck for approximately 10 seconds before an error is reported, and no corresponding call log exists on the oneapi side. Cause: The
auditTraceIdEnabledconfiguration was not enabled, making it impossible to associate the model call chain, resulting in lost logs and an unadapted timeout threshold for the proprietary model's response delay. - Issue: During audits, it is found that the yield rate calculation results do not match the original data. Post-investigation, the returned data units do not match the query requirements. Cause: The
fieldUnitValidationconfiguration was not enabled, and the unit matching of returned fields was not verified, leading to mixed calculation of data with different units.
How to Confirm Configurations Are Set Correctly
- Navigate to the system log management page, filter port yield rate query logs from the past day, verify that each log is associated with the trace ID of the original operation system, confirming that the
auditTraceIdEnabledconfiguration is active. - Initiate a query carrying multi-port and multi-dimensional data, check that the execution duration of workflow nodes does not exceed the preset threshold, confirming that the
workflowNodeTimeoutvalue is reasonable. - Adjust
historyLogMaxCountto the preset range, initiate multiple consecutive rounds of conversation, check that the number of historical messages carried in the context meets the configuration requirements, confirming no token limit violation errors. - Manually trigger the field unit verification logic, pass test data with inconsistent units, check whether the system triggers a verification alert, confirming that the
fieldUnitValidationconfiguration is active.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-09-14.