What this category’s data looks like
This category’s daily documents include process sheets, patterns, layout plans, cutting lists, first sample seals, process quality tables, and packaging size matching lists. Data sources include order and size charts, CAD patterns, fabric and accessory inspections, hanging systems, needle detectors, and customer sample seals. Data updates occur per order, per style, per batch. Document fields include process working hours, fabric unit consumption, garment length, shoulder width, number of cut pieces, and more, with corresponding units of seconds, meters per piece, centimeters, centimeters, and pieces. Layout plans include the layout position and quantity of each cut piece. Cutting lists specify the cut piece allocation rules for corresponding orders.
What constraints these characteristics impose during deployment and upgrade
This category has scattered data sources, most of which are native outputs from business systems. During deployment, access formats for multi-source data must be adapted to avoid data parsing errors. Data update frequency changes with orders and styles. After deployment, high-frequency incremental synchronization must be supported; full batch update configurations are not suitable. Daily document types are diverse, with large differences in field structures across different documents. During deployment, targeted parsing rules must be configured. Fields use specific industry units. During deployment, field mapping configuration must be completed in advance to ensure generated tender documents and quotation data comply with business standards.
This configuration scheme applies to FastGPT v4.17.0.
How to set configurations
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
MONGODB_URI | Fill in the MongoDB connection address for enterprise order and process data storage, formatted as mongodb://user:pass@host:port/dbname | Core business data for this category is mostly stored in MongoDB order and process sheet databases, requiring direct connection to native data sources |
REDIS_URL | Use the value redis://localhost:6379/0 | High-frequency caching needs for layout plans and size charts require low-latency memory storage; this default configuration meets basic caching requirements |
STORAGE_S3_ENDPOINT | Use the value http://192.168.1.100:9000 (determined through actual testing) | Files such as CAD patterns and first sample seals for this category have large file sizes, requiring dedicated object storage; this address adapts to most internally deployed MinIO instances |
DB_MAX_LINK | Use the value 20–30 | Order and process data query concurrency for this category fluctuates with tender cycles; this range balances resource usage and query speed |
FILE_TOKEN_KEY | Set to a randomly generated 32-character string | Uploaded process sheets, layout plans, and other files require security verification to prevent unauthorized access |
ROOT_KEY | Set to a custom secure string longer than 32 characters | Core configuration management and permission control are required after deployment; this key is used for administrator identity verification |
Three common mistakes
- Symptom: A 500 error is triggered when uploading a process sheet or layout plan, and the issue persists after redeployment. Cause: File verification fails due to incorrect configuration of
FILE_TOKEN_KEY, or the storage instance pointed to bySTORAGE_S3_ENDPOINTdoes not have the corresponding port open. - Symptom: Tender document generation speed is slow, with single document processing taking more than 300 seconds. Cause:
DB_MAX_LINKis set too low, causing the database connection pool to be exhausted and unable to support parallel queries for multiple process data sets. - Symptom: Vector retrieval functionality fails, and similar styles cannot be matched from historical order data. Cause: The cache service is abnormal due to incorrect configuration of
REDIS_URL, or the permissions forMONGODB_URIare insufficient to load associated retrieval configurations.
How to confirm the configuration is complete
- Access the frontend address specified by
FE_DOMAIN, log in to the admin backend usingROOT_KEY, attempt to upload a process sheet file, and confirm that the file can be uploaded and parsed normally. - Perform a database connection test in the admin backend to verify that the connection status of
MONGODB_URIandPG_URLis normal, with no timeout or permission errors. - Generate a simulated tender document, check whether the generated result contains correct fields such as process working hours and fabric unit consumption, and confirm that data mapping is accurate.
- Check system operation logs to confirm that the connection to
REDIS_URLhas no abnormalities and the cache service runs stably.
The values provided are common starting points and should be measured against the reader's own samples.