What this category of data looks like
Data sources for this category include MES systems, online testing equipment, laboratory ledgers, process parameter documents, customer quality standards, and historical defect databases. Data is collected continuously according to production batches and work shifts, with multiple associated documents generated within a single production cycle, including control plans, patrol inspection records, SPC reports, final product inspection reports, nonconforming product review forms, release forms, and monthly quality reports. Data fields include inspection batch numbers, detection parameter thresholds, nonconforming item types, release determination results, and detection equipment numbers. Associated units include process and quality measurement standards such as ppm, millimeters, and seconds.
What constraints these characteristics impose on the deployment and upgrade phase
The data sources for this category are scattered and updated in real time. During the deployment phase, multiple data source connection rules must be configured to ensure synchronization stability for data from different sources such as MES and testing equipment. There are diverse document types with significant structural differences. When upgrading the knowledge base parsing module, parsing logic must be adapted to handle content in different formats such as control plans and final product inspection reports. Data is associated with production batches and release determinations. During deployment, data permission isolation rules must be clearly defined to prevent unauthorized personnel from modifying release-related records. High-frequency batch data import also places demands on the read and write performance of storage components, so sufficient configuration adjustment space must be reserved.
How to Configure Settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
DB_MAX_LINK | 120–180 concurrent connections | This category generates a large number of quality inspection records per production batch, with high demand for concurrent read and write operations. This configuration balances resource usage and access efficiency |
MONGODB_URI | Connection address of a dedicated quality inspection data storage instance | This category requires storage of unstructured documents such as inspection reports and review records. MongoDB's document storage capabilities are suited to the management needs of this type of data |
STORAGE_S3_ENDPOINT | Access address of an internal enterprise object storage service, supporting a maximum single file upload size of 100 MB | This category requires storage of massive amounts of testing equipment export files and historical monthly quality reports. Reliable object storage ensures read, write, and archiving of large files |
REDIS_URL | Local cache instance address, with cache expiration time set to 300 seconds | This category requires frequent queries of release determination rules and historical defect databases. Caching reduces database read pressure and shortens query response times |
FILE_TOKEN_KEY | Randomly generated 32-character string key | Release forms and review records for this category involve internal quality information. This key ensures permission security for file access |
Three Common Misconfigurations
- Issue: Chinese garbled characters appear in the interface after importing CSV-format patrol inspection records or monthly quality reports. Cause: The correct encoding format was not specified in the import configuration, and the default encoding does not match the actual encoding of the file.
- Issue: The platform fails to start normally after upgrading fastgpt-mcp-server, with container logs returning port occupation or missing configuration file errors. Cause: Port mapping parameters from the original configuration file were not retained during the upgrade process, or compatibility processing for the new version and legacy environment dependencies was not completed.
- Issue: The re-ranking model deployment test passes, but every retrieval returns a false re-ranking result, and retrieval results are not sorted by relevance. Cause: The request address of the re-ranking model was not correctly bound in the retrieval configuration, or the model input format does not match the platform requirements.
How to Verify Proper Configuration
This verification process applies to FastGPT v4.17.0.
- Check whether the
MONGODB_URIconfiguration item points to a dedicated quality inspection data storage instance. Connectivity can be verified using a database connection testing tool. - Upload a test final product inspection report and confirm that the parsed data fields match the inspection batch number, nonconforming item, and other fields for this category.
- Initiate a batch patrol inspection record import task and check the read and write logs of the storage component to confirm there are no timeout or connection error messages.
- Trigger a quality inspection record retrieval request to verify that the cached release determination rules can be returned normally.
The values given are common starting points and should be measured against the reader's own samples.