What the data for this category looks like
The data for this category covers the entire production process for air conditioners, refrigerators, washing machines, and small household appliances. Daily documents include configured BOMs, assembly work instructions, refrigerant charging records, electrical safety test reports, performance spot check reports, and repair records. Data is sourced from ERP/MES systems, component batch ledgers, tightening and charging device logs, safety compliance testers, performance lab data, and after-sales fault work orders. Update frequencies apply to individual products, per-shift output, and fixed spot check cycles. Fields include batch numbers, process parameters, test results, repair reasons, and more. Field units adjust based on document type.
Constraints imposed on deployment and upgrade
The mixed-line assembly of multiple models in this category requires deployment configurations to support quick filtering rules by model and batch. This prevents cross-category data interference. Multiple heterogeneous data sources—including device logs, system export files, and after-sales work orders—require adapted configurations for accessing different data formats. The high-frequency update requirement at the individual product level creates clear constraints on storage and real-time retrieval performance. The upgrade process must verify version compatibility with existing database versions. Compliance requirements for consumer safety and function require clarifying the permissions and priority of analysis results during deployment. This ensures sensitive data is not leaked.
How to configure the settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
MONGODB_URI | mongodb://username:password@host:27017/fastgpt?authSource=admin | Adapts to multi-source device logs and after-sales data storage for complete home appliance manufacturing, and is compatible with MongoDB 5.0.18 and later security update versions |
DB_MAX_LINK | 200–300 connections | Addresses high-frequency individual product data writes and batch retrieval needs, and prevents connection pool exhaustion |
REDIS_URL | redis://:password@host:6379/0 | Caches frequently accessed data such as batch numbers and safety compliance test results, and speeds up retrieval responses |
STORAGE_S3_ENDPOINT | Fill in according to the enterprise's self-built object storage address | Stores large-volume documents such as refrigerant charging records and safety compliance test reports, and adapts to the enterprise's existing storage architecture |
ROOT_KEY | Generate according to the enterprise's internal key specification | Controls the system's highest permissions, and prevents unauthorized access to sensitive product BOM and repair data |
FE_DOMAIN | https://fastgpt.yourcompany.com | Configures the frontend access domain name, and ensures that the analysis result page can properly link to internal enterprise document links |
Three common errors
- The login screen displays an old version number after upgrade. Phenomenon: After logging into FastGPT, the page footer or personal center shows an old version number, but the actual deployment package is the new version. Cause: Frontend static resource files were not updated correctly, or frontend cache was not cleared, so old version page files failed to load.
- Database connection fails after version upgrade. Phenomenon: The system reports
connection refusedorauthentication failedafter startup. Cause: Database connection configurations such asMONGODB_URIwere not updated synchronously, or database permission configurations were reset during the upgrade process. - Interface incompatibility occurs after upgrade following secondary development. Phenomenon: A system developed on an older version with secondary modifications reports interface errors after upgrading to a new version. Cause: The compatibility between custom code and the new version API was not reviewed, and direct overwriting deployment led to interface mismatches.
How to verify successful configuration
- Log into the system backend, check the database connection status, and confirm that the connection test results for configuration items such as
MONGODB_URIandREDIS_URLare normal. - Import a real home appliance assembly work instruction document, and verify that fields such as model, batch number, and process parameters can be correctly extracted after parsing.
- Trigger a quality traceability query, enter a known after-sales fault work order number, and confirm that the corresponding BOM, device logs, and repair records can be associated.
- Check the system version information page, and confirm that the currently running version is FastGPT v4.17.0.
The values provided here are common starting points, and should be evaluated against the reader's own samples.