What the data for this category looks like
The data for document and material drafting in shipbuilding primarily comes from technical documents accompanying ship design drawings, mandatory standard documents from classification societies, section construction process records, and procurement contract attachments. Data is updated according to project construction milestones, and single update volume fluctuates with section construction progress. Document structures include core ship parameters, process numbers, material specification details, and approval signature columns. Fields cover project numbers, classification society codes, and material batch numbers. Units include industrial standard units such as gross tonnage, millimeters, and square meters.
What constraints these characteristics impose during deployment and upgrade
FastGPT v4.17.0’s deployment process adapts to the multi-source data access needs of the shipbuilding industry. Multi-source heterogeneous data sources require configuring multi-format file access adapters during deployment, supporting parsing of CAD-exported PDFs, classification society Word standard documents, and Excel process record sheets. The update rhythm aligned with project milestones requires configuring incremental sync trigger rules during upgrades, to avoid full syncs consuming excessive system resources. Long document structures require reserving sufficient context processing capacity during deployment. The strong binding between fields and industrial standard units requires accurate mapping of fields and unit identifiers during configuration, to prevent parameter mismatches during vector retrieval.
How to set configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
DB_MAX_LINK | 20–30 connections | The data volume of a single shipbuilding document project is large, so the upper limit of the database connection pool must be controlled to avoid resource exhaustion |
MONGODB_URI | Local private cluster address | Shipbuilding documents contain internal industrial parameters of enterprises, so they must be deployed in a private network to ensure data security |
REDIS_URL | 1000-second cache expiration time | The cache for document sync tasks needs to cover longer project cycles, to avoid frequent data re-pulling that increases system load |
STORAGE_S3_ENDPOINT | Enterprise self-built object storage address | Large ship documents require high-capacity, highly reliable storage services that adapt to the enterprise’s own storage architecture |
FILE_TOKEN_KEY | Random key generated per project | Documents of different ship projects need isolated access permissions to prevent cross-project data leaks |
Three common errors
- Frontend
Uncaught TypeErrorerrors appear after startup, with logs pointing to autofill-related modules. The cause is incorrect configuration of theFE_DOMAINparameter during deployment, leading to incorrect frontend script loading paths. - Uncaught exceptions are triggered by the AI chat component in workflows. The cause is an incorrect
MONGODB_URIconfiguration during private deployment, preventing normal connection to the database for document fragment retrieval. - Document sync tasks time out without completing. The cause is failure to adjust the
DB_MAX_LINKparameter, leading to database request blocking due to exhausted connection pools.
How to confirm the configuration is complete
- Access the configured
FE_DOMAINaddress, and confirm that there are no script loading failure errors on the frontend page. - Run a single document sync test task, and check that logs show normal database connection and storage service calls.
- Upload a shipbuilding process record sheet, and confirm that the system can correctly identify material specification and unit fields in the document.
- Trigger an incremental sync test, and confirm that only document data within the specified time range is updated.
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.