What the data for this category looks like
Production data for this category primarily comes from water source and raw material testing, formula systems, online sugar and acidity monitoring, filling equipment, visual inspection systems, and LIMS systems. Daily stored documents include formula sheets, water treatment records, blending records, sterilization or aseptic filling records, packaging material inspection reports, and finished product inspection reports. Data is updated per batch, per shift, or via continuous collection. Fields include batch number, raw material batch, sugar content value, filling liquid level, sealing pass rate, label batch number, and others. Units include mg/L, %, mm, pieces, and others. All data must correspond one-to-one with equipment parameters in the production process.
What constraints these characteristics impose on deployment and upgrade
Data for this category is collected per batch, per shift, or continuously, with sources spanning multiple production and testing devices. Deployment must support real-time synchronization of multiple data sources and protocol adaptation. Multiple types of fixed-format documents stored daily require targeted parsing rules configured to match the field structures of different documents. High-frequency updated production data creates significant storage and query pressure. Database connection parameters must be optimized to ensure stability. Additionally, production ledgers must be strictly bound to batch numbers and production links. Deployment must ensure that summary logic fully aligns with fields of processes such as feeding, water treatment, and filling to avoid batch misalignment or data omission. This configuration solution is based on FastGPT v4.17.0.
Configuration Settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
DB_MAX_LINK | 20–30 connections | This category has high data collection frequency. A reasonable database connection pool upper limit is needed to adapt to concurrent ledger writes and queries. |
REDIS_URL | 1000 MB memory authenticated instance | High-frequency accessed batch ledger metadata must be cached to shorten response time for production report generation. |
STORAGE_S3_ENDPOINT | Local or cloud object storage access address | Documents such as water treatment records and finished product inspection reports for this category have large volumes. Unified storage paths must be configured to facilitate archiving and retrieval. |
PG_URL | Connection parameters calibrated via actual testing | Structured batch production data must be stored to support multi-table association for ledger summary logic. |
FILE_TOKEN_KEY | 32-bit random string | Access permissions for uploaded production documents must be secured to prevent unauthorized document leaks. |
Three Common Errors
- Phenomenon: An empty response is returned after calling the ledger summary interface. Complete ledger content can only be viewed by entering conversation details. Cause: Permission verification rules for
FILE_TOKEN_KEYare not configured correctly. Uploaded production documents only load after permission verification is triggered on the details page. - Phenomenon: A database connection timeout error occurs when starting the container after upgrading the version. Cause: Compatible configurations for
PG_URLorREDIS_URLare not updated. The database connection logic of the new version does not match the parameters of the old instance. - Phenomenon: A file parsing error is triggered when uploading packaging material inspection records. Cause: The correct storage path for
STORAGE_S3_ENDPOINTis not configured. Uploaded files fail to be written to the storage medium, and the parsing link cannot obtain the target file.
How to Verify Successful Configuration
- Run a database connection test to verify that configurations for
DB_MAX_LINK,PG_URL, andREDIS_URLcan establish normal connections. The connection number upper limit must match actual concurrent request volume. - Upload a standard finished product inspection report to verify that the configuration for
STORAGE_S3_ENDPOINTcan correctly store the file, and the file path can be accessed normally by the parsing link. - Initiate a batch ledger summary request to verify that the response content includes complete fields such as batch numbers, raw material data, and detection indicators, with no missing or misaligned data.
- Check the configuration for
FILE_TOKEN_KEYto confirm that access permissions for uploaded production documents comply with preset rules, and no unauthorized access prompts appear.
The values provided are common starting points and should be measured against relevant samples.