What the data for this category looks like
Data for shipping port intelligent due diligence reports primarily comes from port operation management systems, maritime supervision databases, shipper registration ledgers, and vessel scheduling platforms. There are two categories of data update rhythms: Dynamic information such as vessel berthing and departure, and berth occupancy status is updated in real time. Statistical data such as cargo throughput and container turnover volume is updated daily. The document structure includes structured operation tables and unstructured compliance description texts. Core fields include berth number (unit: count), berthing duration (unit: hours), throughput (unit: ten thousand tons), and vessel draft (unit: meters). The number of structured fields per single report is relatively large, and the length of unstructured text varies widely.
What constraints these characteristics impose on the "HTTP Interfaces and External Systems" link
The high-frequency update requirement for real-time dynamic data requires HTTP interfaces to support low-latency calls and flexible synchronization frequency configuration, to avoid data lag caused by current limiting or timeouts. Differentiated update rhythms across multiple data sources require interfaces to support pulling different types of data at different cycles, while compatibility with return format differences across multiple data sources. The large number of structured fields requires interfaces to support specified field filtering to reduce invalid data transmission volume. Port data involves operation compliance information, so interfaces must carry identity verification parameters to prevent unauthorized access. The mixed structured and unstructured document structure requires interfaces to support segmented pulling and batch parsing adaptation.
How to set the configurations
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
api_request_timeout | 600 seconds | Addresses scenarios where bulk port operation data is pulled, avoiding interface timeouts due to large data volume |
api_rate_limit | 10 requests per minute | Adapts to interface call frequency limits of most port systems, avoiding triggering the other party's current limiting intercepts |
field_filter_enable | Enabled | Only pulls core due diligence fields such as berth number, berthing duration, and throughput, reducing transmission redundancy |
sync_interval | 1 hour / real-time (on demand) | Daily updated cargo volume data uses a 1-hour synchronization cycle, real-time berthing data uses real-time pulling mode |
auth_token_required | Enabled | Complies with compliant access requirements for port operation data, only authorized users can call external interfaces |
max_response_fields | 20 fields | Limits the number of returned fields to avoid excessive interface return data affecting FastGPT's parsing efficiency |
The parameter values provided on this page are common recommended starting points for configuration. Actual values are affected by material form, data volume, and business rules. Specific issues require case-by-case analysis, and it is recommended to test on your own samples before finalizing settings.
Three common mistakes
- A
403 Forbiddenstatus code is returned when calling the interface. The cause is that the correctauth_token_requiredparameter is not configured, or a valid access token is not carried. - The
sourcefield returned by the interface only displaysapi. The cause is that a custom source identifier is not set in the external interface configuration, resulting in incorrect recording of the data source type. - Indicator data cannot be obtained when connecting to Zabbix monitoring. The cause is that correct request header parameters are not configured, and authentication information required by the target interface is not carried.
How to confirm the configuration is complete
- Call the test interface, check whether the returned
sourcefield includes the custom port data source identifier, to confirm that the source configuration takes effect. - Check the field list returned by the interface, confirm that only the pre-configured core due diligence fields are included, with no redundant data.
- Initiate a bulk data pull request, confirm that the interface response duration is less than the set
api_request_timeoutvalue, with no timeout errors. - View the FastGPT interface logs, confirm that the call frequency does not exceed the set
api_rate_limitthreshold, with no current limiting intercept records.
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.