What the Data for This Category Looks Like
Typically, technical documentation for garment cutting and sewing links includes process sheets, marker plans, cutting lists, first sample approval records, process quality tables, and more. Data comes from order size charts, CAD design patterns, fabric and trim inspection data, information collected from production hanging systems and needle detectors, and other sources. Documentation updates proceed with each order and batch production, involving fields such as pattern parameters, fabric grain direction requirements, packaging size matching rules, and more in a single update. Cut piece data is irreversible and labor-intensive, requiring strict alignment with size, fabric lot, and cut piece matching requirements. Errors will directly lead to batch deviations or customer rejection.
What Constraints These Characteristics Impose on Deployment and Upgrade
The high-frequency, small-batch update nature of this category requires deployment to support rapid synchronization of new process sheets, marker plans, and other documents, to avoid production deviations caused by update delays. Mixed access to multiple types of heterogeneous documents (CAD patterns, tabular process sheets, scanned paper documents) requires configuration of multi-format storage and vectorization rules. Resource margin for validation nodes must be reserved during deployment. Historical document traceability must be ensured during upgrades, to avoid losing historical validation records due to configuration changes. Additionally, the large number of styles and strong seasonality require that upgrade processes do not interrupt review services in existing production environments. A gray release strategy must be used to gradually switch configurations.
Configuration Settings
This configuration is adapted for FastGPT v4.17.0.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
DB_MAX_LINK | 100–150 connections | Adapts to concurrent connection needs for single-batch multi-document tasks, prevents database connection exhaustion from impacting review efficiency |
MONGODB_URI | Container address pointing to local persistent storage | Stores unstructured documents such as process sheets and marker plans, supports order-based archiving and fast retrieval |
REDIS_URL | Configured as an independent local container instance | Caches frequently queried size charts and process validation rules, reduces cross-review response time to within 2 seconds |
STORAGE_S3_ENDPOINT | Intranet address pointing to the enterprise internal object storage | Adapts to large file storage needs for batch import of CAD patterns and fabric and trim inspection data, ensures stability of large file uploads |
ROOT_KEY | Generate independent keys per production team | Isolates review data across different orders, prevents production errors caused by cross-batch data confusion |
FILE_TOKEN_KEY | Configured as a 32-bit random string | Secures access permissions for uploaded documents such as cutting lists and first sample approval records, prevents unauthorized access |
Three Common Mistakes
- Phenomenon: A "ReferenceError: module is not defined" error is returned when a workflow code execution node runs. Cause:
FILE_TOKEN_KEYis not configured during deployment, leading to local file permission verification failure, and inability to read process data associated with the work order. - Phenomenon: Marker plans imported via file upload cannot be updated along with the source files. Cause: Correct volume mount paths are not configured in docker-compose, leading to loss of uploaded temporary document cache after container restart.
- Phenomenon: Knowledge bases connected via external APIs cannot sync the latest first sample approval data. Cause:
FE_DOMAINis not configured as the intranet address of the knowledge base instance during deployment, leading to cross-instance data synchronization failure.
How to Verify Proper Configuration
- Run the
docker pscommand, confirm that containers corresponding toMONGODB_URIandREDIS_URLare in running state. - Upload a test process sheet, check if the system can generate cross-review results including size matching and fabric grain direction validation.
- Modify the locally mounted test marker plan file, confirm if the system can trigger incremental updates and regenerate validation reports.
- Check database connection monitoring metrics, confirm that concurrent connection count does not exceed the configured threshold of
DB_MAX_LINK.
The values provided are common starting points and should be evaluated against samples appropriate for the specific deployment scenario.