What the data for this category looks like
It typically covers garment OEM/ODM, brand supply chains, and cutting and sewing workshops. Daily generated documents include process sheets, patterns, layout plans, cutting orders, first sample seals, process quality forms, and packaging size matching lists. Data comes from orders and size charts, CAD patterns, fabric and accessory inspection, hanging systems, needle detectors, and customer sample seals. Data is updated per order, per style, and per batch. Document fields include version parameters, size specifications, fabric batches, process quality inspection items, and packaging ratios. Common units are centimeters, pieces, kilograms, and batch numbers.
What constraints these characteristics impose on deployment and upgrade
Documents for this category are mostly non-standard paper or CAD-exported files with dimensions and batch information. They have high update frequencies. Multi-source heterogeneous data access must be supported during deployment. Fields in cutting orders, packaging size matching lists, and similar documents require batch association verification. Rules supporting structured field extraction must be configured. Audit logic related to fabric batches and size deviations must be bound to the order dimension. Deployment environments must reserve storage space for associated data. During upgrades, the archived data format of historical orders must be compatible. This avoids interrupting the inspection processes of existing workshops.
How to set configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
MONGODB_URI | mongodb://username:password@host:port/dbname?authSource=admin | Stores structured business data such as orders and quality inspection records, requires a connection address with permission verification configured |
REDIS_URL | redis://:password@host:port/0 | Caches frequently accessed size charts and process sheet data to reduce database load |
STORAGE_S3_ENDPOINT | Fill in according to the enterprise storage service provider address | Stores large files such as CAD patterns and first sample seals, adapts to the storage needs of multi-category documents |
FILE_TOKEN_KEY | Randomly generate a 32-bit string | Generates file access tokens to prevent unauthorized access to sensitive documents such as cutting orders and packaging size matching lists |
ROOT_KEY | Configure a strong password in accordance with security specifications | Initializes system administrator permissions to ensure access security of the deployment environment |
DB_MAX_LINK | 100–200 connections | Adapts to concurrent inspection record query requests from multiple workshops, avoids connection pool exhaustion |
Three common mistakes
- After deploying the v2 version marker, logs show an OCR error. This occurs when no OCR model adaptation rules supporting garment fabric texture and cut piece detail recognition are configured, or the stored pattern image format is not supported.
- After locally deploying FastGPT v4.17.0, no image understanding model option appears when creating a knowledge base. This happens when the relevant model loading configuration is not enabled in environment variables, or the corresponding dependency packages are not installed.
- Adding the Volcano Engine DeepSeek-R1 model fails after Docker deployment. This occurs when the API key and request address for model access are not correctly configured, or the outbound access permission for the corresponding port is not enabled.
How to confirm the configuration is complete
- Run the environment variable verification script. Confirm that the formats and permissions of configuration items such as
MONGODB_URIandREDIS_URLmeet requirements. - Upload a cutting order sample. Test the structured field extraction function, and verify that fields such as size and fabric batch are correctly identified.
- Initiate a batch inspection record query request. Confirm that the database connection pool does not show exhaustion errors, and the response time meets business requirements.
- Try to access the stored pattern image. Verify that the access token generated by
FILE_TOKEN_KEYauthorizes normally, and no unauthorized access prompt appears.
The values provided are common starting points and should be measured against the reader's own samples.