What this category's data looks like
Data sources for port and shipping business processing include three categories: internal port operation management systems, official maritime administration bureau reporting platforms, and vessel scheduling systems. Dynamic data such as real-time vessel arrival and berth application status is updated every 5 minutes. Static data such as manifests and business application forms is updated daily. Historical business records are archived quarterly. The document structure of a single business record includes six core fields: vessel name, voyage number, berth number, application type, processing status, and handler ID. The field types are character, character, character, enumeration, enumeration, and character respectively, with no nested complex structures.
What constraints these characteristics impose on the workflow orchestration link
Reference only; verify against the target FastGPT release and deployment documentation.
How to set configurations
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
variables | Extract vessel name, voyage number, and berth number as global variables | All port business processing workflows rely on these three core identifiers, so unified extraction must be completed at the start of the workflow |
| Single search limit | Top 3 entries | Structured entries in port business knowledge bases are mostly standardized processes, and the top 3 entries cover common processing scenarios |
| Timeout threshold | 600 seconds | Response times for external interfaces such as maritime reporting and berth scheduling typically range from 3 to 5 minutes, so sufficient buffer time is reserved |
| System prompt | Only verify the three required fields of vessel name, voyage number, and berth number; do not generate additional business suggestions | Match the process guidance requirements of port business processing, and avoid irrelevant content interfering with user judgment |
nodeId | Bind the unique identifier of the maritime reporting node | Ensure MCP tool calls point to the correct business interface and prevent disordered node calls |
| Context window | 800-1200 characters | Adapt to the conventional length of port business process documents and avoid context overflow |
Three common mistakes
- The context of the AI chat node is empty after workflow execution, shown as 0 matching results returned from the knowledge base. The cause is that port business-specific keywords such as "berth application" and "manifest declaration" are not configured as recall trigger words, leading to recall scope deviating from the business scenario.
- Downstream nodes cannot obtain the return values of MCP tool calls, shown as empty fields when reading the tool output corresponding to
nodeId. The cause is that the mapping relationship between tool outputs and globalvariablesis not configured in the workflow, and data such as returned processing status is not bound to reusable variables. - AI node output contains content beyond the specified range, shown as business suggestions for non-specified fields appearing in the reply. The cause is that the system prompt does not clearly limit only verifying the three required fields of vessel name, voyage number, and berth number, leading the AI to generate irrelevant content.
How to confirm correct configuration
- Trigger a test port business processing request, and check if the logs of each workflow node correctly extract the vessel name and voyage number fields from
variables. - Call the bound MCP tool, and verify that the returned business data is correctly mapped to the global variables of the workflow.
- Run the AI chat node, and check if the output context only contains matching port business knowledge base content, and if the AI reply complies with the preset system prompt requirements.
- Simulate a timeout scenario, and confirm that the workflow triggers the exception handling process after exceeding the set timeout threshold.
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.