What data looks like for this use case
Shipbuilding work ledger data comes from on-site recording systems for each process, including block fabrication, outfitting work, and sea trial testing. Updates follow process node progress. A single ledger entry includes fields such as process number, component name, inspection result, man-hour consumption, and material usage quantity. Field units are fixed: man-hours use hours, materials use tons or square meters. Inspection result is an enumerated value of qualified or unqualified. Documents are stored classified by process. Single ledger document lengths range from hundreds to thousands of characters.
Constraints imposed on workflow orchestration by these characteristics
The decentralized sources of shipbuilding work ledgers across multiple processes require workflows to be configured with multiple nodes to directionally pull data sources from different processes, to avoid missing data. Fixed fields and units require workflows to pre-bind variables for corresponding fields, to prevent unit errors during data splicing. The high-frequency process update rhythm requires workflow trigger intervals to match process node cycles, to avoid data lag. Long-text inspection report content requires workflow nodes to support long-text processing and summarization.
How to set configurations
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
variables | Bind the three core fields: process number, inspection result, and material consumption | The core data of shipbuilding work ledgers are process identifiers, quality results, and material usage, which require precise mapping |
| Node timeout period | 600 seconds | Pulling and processing single-process ledger data takes a relatively long time; this setting avoids mid-run interruptions |
nodeId | Bind the three core process node IDs: block fabrication, outfitting work, and sea trial | Shipbuilding work ledgers are split by process, requiring directional pulling of data sources from corresponding links |
| Result verification rules | Match field units and preset standards, such as man-hours ≤ 8 hours per day | Work ledger fields have fixed units, requiring verification of data compliance |
| Log retention period | 30 days | Shipbuilding work ledgers require traceability, requiring a sufficiently long retention period for running logs |
| Single data pull limit | 1000 entries | Avoiding timeouts caused by pulling too much data on a single node |
Three common configuration mistakes
- Phenomenon: After importing a configuration exported from an upstream system into the workflow, the fields output by downstream nodes are empty or do not match the ledger fields exported from the upstream system. Cause: The upstream exported field names are not strictly aligned in the
variablesconfiguration, leading to misplaced data transfer. - Phenomenon: The workflow node returns a 500 status code during operation. Cause: The node timeout period is set too short, below the reasonable threshold of 600 seconds, causing data pulling to be interrupted before completion.
- Phenomenon: The workflow cannot be triggered or called in the chat window. Cause: The call permissions for the workflow are not configured, or the correct
nodeIdparameter is not bound in the request, causing the system to fail to identify the execution node.
How to confirm the configuration is complete
This verification must be performed on FastGPT v4.17.0:
- Manually trigger the configured workflow, and verify that the pulled ledger data fields match the preset
variablesconfiguration. - Review the workflow running logs to confirm that all bound
nodeIdnodes have completed execution, with no timeout or error messages. - Submit test ledger data with non-standard units, confirm that the result verification rules trigger corresponding interception prompts.
- Send a test request from the chat window embedded in the business system, confirm that the workflow returns a summary report normally.
The values provided here 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.