What data looks like for this category
Data for this category typically comes from ERP/WMS systems, barcode or RFID collection devices, purchase work orders, storage location management ledgers, AGV transport systems and weighing equipment. Daily generated documents include receiving slips, putaway slips, material picking and return slips, warehouse transfer slips, inventory counts, lot ledgers, and first-in first-out and expiration date control records. Data fields include material codes, lot numbers, storage location numbers, inspection status, expiration dates, inbound and outbound quantities, and more. Update cycles cover real-time (inbound/outbound, barcode scanning operations), daily (ledger updates), and monthly inventory reconciliation.
What constraints these characteristics impose on deployment and upgrades
Data sources for this category are scattered, and update cycles vary widely. This creates multiple constraints for deployment and upgrade workflows. Multiple heterogeneous data sources require pre-configured adapter settings to ensure stable links for barcode/RFID collection, ERP/WMS synchronization, and other processes. Data with different update frequencies needs matching resource configurations. Real-time inbound and outbound data requires adjusting database connection pool parameters. Monthly inventory bulk data needs optimized bulk import logic. Special fields such as lot numbers, expiration dates, and inspection status must have custom field mappings completed during deployment. Upgrades must support version migration of legacy fields to avoid damaging core logic for matching physical and book inventory and lot traceability.
How to set configurations
The following configurations are based on FastGPT v4.17.0, adapted to deployment needs for warehousing, lot tracking, and in-plant logistics scenarios.
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
MONGODB_URI | mongodb://user:pass@host:27017/fastgpt?authSource=admin | This category has large storage volumes for lot ledgers and inventory data. A dedicated database and authentication information must be specified to adapt to concurrent requirements for multi-source data synchronization. |
PG_URL | postgresql://user:pass@host:5432/fastgpt_wms?sslmode=require | Storage location and work order associated data for this category is suitable for storage in a relational database. SSL must be enabled to ensure data security in production environments. |
DB_MAX_LINK | 20–30 | This category has a high volume of concurrent requests for real-time inbound and outbound data. A reasonable connection pool size can prevent database connection exhaustion. |
REDIS_URL | redis://:pass@host:6379/0 | Real-time scanned data and lot verification results must be cached to reduce database query pressure. |
STORAGE_S3_ENDPOINT | Determined through actual testing | Weighing photos and lot traceability documents for this category must be stored in an object storage service. The endpoint must be configured according to the actual deployed storage service provider. |
ROOT_KEY | Randomly generated 32-character string | Production environments must secure access to backend management interfaces to prevent unauthorized operations. |
Three common mistakes
- Symptom: MongoDB connection timeout or authentication failure errors during deployment. Cause: Failure to adjust the
DB_MAX_LINKparameter for multi-source data synchronization in this category, causing concurrent requests to exceed the database connection limit. - Symptom: Abnormal lot traceability functionality after upgrading the production environment. Cause: Failure to pre-map special fields such as lot numbers and expiration dates, causing mismatch between legacy data and new configuration field rules.
- Symptom: Data migration failure when attempting to switch storage versions. Cause: Failure to pre-sort the association between storage location, lot data and storage logic for this category, and incomplete data format conversion.
How to confirm configurations are correct
- Run a database connection test script to verify connectivity for
MONGODB_URIandPG_URL, confirm no authentication or address errors. - Import a sample receiving slip document, check that custom field mappings are correct, and that fields such as lot numbers and expiration dates can be recognized normally.
- Trigger a real-time data synchronization task, verify that scanned inbound and outbound data can be written to the database normally, and that cached results can be queried in the service corresponding to
REDIS_URL. - View the storage configuration in the backend management interface, confirm that the
STORAGE_S3_ENDPOINTendpoint matches the actual storage service, and that attachments such as weighing photos can be uploaded normally.
The values provided are common starting points and should be measured against local deployment samples.