Reference only; verify against the target FastGPT release and deployment documentation.
What the Data for This Category Looks Like
The data used for document and material drafting in port and shipping scenarios comes primarily from three core data sources: port production dispatching systems, customs clearance systems, and freight forwarding manifest management systems. Data updates are triggered per job node or voyage cycle. The size of a single document ranges from several KB to tens of MB. Document structures include fields such as basic ship information, cargo type details, operation volume data, operation time periods, and declaration order numbers. Common units include tons, hours, and voyage numbers. Some compliance-focused documents also include professional identifiers such as customs supervision codes and IMO ship numbers.
What These Characteristics Impose on Tool Calling and Plugins
Dispersed data sources cause differences in field formats across systems. Configure unified mapping rules during tool calling to prevent parameter misalignment. Differences between professional and general fields require preset port-specific field matching templates to ensure accurate retrieval of compliant data during calls. Adjust tool calling frequency and timeout settings to align with job process timelines, avoiding delayed declarations, to match the frequent update rhythm of voyages. Combine the toolChoice configuration to dynamically adapt long-text and short-text calling logic, preventing context overflow, to handle wide variations in document size. Preset corresponding adaptation rules during plugin calls to ensure compatibility for cross-port operations, to address differences in interface formats across some ports.
How to Set Configurations
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
toolChoice | Set to automatically match professional document scenarios | Port and shipping documents involve multiple types of tool calls; automatic matching adapts to the needs of different job documents |
| Tool calling timeout | 120–180 seconds | Port document declaration must comply with job process timelines; this range avoids job interruption due to timeout |
| Data field mapping template | Preset port-specific fields such as ship name, loading and unloading tonnage, and operation time periods | Differences exist between port document fields and general fields; unified mapping reduces parameter misalignment |
| Batch call limit | First 3 pending voyages | Excessive data volume in a single batch call will trigger interface rate limiting rules of port job systems |
| Call log storage capacity | 1000 MB | Port job logs must retain at least one quarter of job data; this setting reserves reasonable storage space |
functionCall | Enable mandatory verification mode | Port documents involve compliance requirements; mandatory verification prevents invalid parameters from being passed |
Three Common Misconfigurations
- Symptom: Customs supervision code field missing from document content returned after tool calling. Cause: No port-specific field mapping rules configured, leading to failure to retrieve professional identifier fields from the corresponding data source during calls.
- Symptom: No tool calling logs generated, with the interface displaying no call records. Cause: Tool calling log storage configuration not enabled, or storage capacity set too low, resulting in automatic log cleanup.
- Symptom: 429 status code returned when batch calling voyage documents. Cause: Batch call limit set too high, exceeding the interface rate limiting threshold of the port job system.
How to Verify Correct Configuration
- Initiate a single-voyage document drafting call, check if the returned result includes preset port-specific fields such as ship name and loading and unloading tonnage.
- View the tool calling log panel, confirm that a complete record of this call is generated, including call parameters and returned results.
- Simulate a batch call for 3 voyage documents, check if the interface returns normal results without triggering rate limiting errors.
- Verify that AI responses are linked to source identifiers of the called data, such as voyage numbers or declaration order numbers, to enable content traceability.
The values provided are common starting points, and should be evaluated against samples from actual deployments.
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.