What data looks like for this category
This category includes quarantine certificates, slaughter and cutting records, ingredient marinating records, thermal processing records, cold chain temperature logs, and microbial test reports. Data comes from animal quarantine information, supplier batches, production traceability systems, temperature collection devices, metal detection equipment, and laboratory test results. Updates run per production batch and shift. Cold chain temperature data is collected continuously. Document fields include quarantine number, carcass batch number, processing temperature parameters, monitoring period, and microbial test results. Corresponding links between batches and quarantine information must be maintained.
Constraints during deployment and upgrade
Data for this category has strong links between batches and quarantine information, plus high-frequency, continuously collected temperature control data. Deployment and upgrade processes must balance data security, concurrent processing, and field compatibility. Strong batch traceability requirements demand stable database connection configuration to avoid data matching failures. High-volume continuous temperature control data requires high-throughput storage configuration. Document fields vary widely across production stages. Upgrades must support parsing logic for multi-format fields. Exception reports require rapid integration of multi-source test data. Deployment processes must reserve buffer configurations for data synchronization. Control fields for raw/cooked product separation and sterilization temperature must support precise matching, which constrains field validation logic for configuration items.
How to set configurations
The following configurations are adapted for FastGPT v4.17.0.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
DB_MAX_LINK | 100–150 connections | Matches concurrent requirements for high-frequency data writes and queries across multiple batches, ensuring real-time synchronization of production data |
STORAGE_S3_ENDPOINT | Point to local private storage nodes | Meets the security requirements of local storage for quarantine and production records at slaughterhouses, preventing sensitive data from leaking |
REDIS_URL | 600-second cache expiration | Matches the interval of continuous cold chain temperature collection, ensuring validity of temporarily cached data |
FILE_TOKEN_KEY | Align with quarantine document encryption rules | Ensures compliance with access permissions for sensitive documents such as quarantine certificates and microbial test reports |
FE_DOMAIN | Configure to the enterprise internal office domain | Restricts external access without internal network permissions, complying with internal use requirements for production data |
Three common mistakes
- Symptom: Workflow editing interface fails to load after offline private deployment, with client application error messages displayed. Cause: Internal network-accessible
FE_DOMAINand local storage endpoints were not configured, preventing front-end resources from loading properly. - Symptom: Timeouts occur during exception report generation, with empty results returned. Cause:
DB_MAX_LINKis set too low, failing to support simultaneous queries across multiple batches and exhausting database connections. - Symptom: Tool calls fail to correctly associate quarantine batch information. Cause:
FILE_TOKEN_KEYis not aligned with document encryption rules, preventing sensitive documents from being read and parsed normally.
How to confirm configurations are set correctly
- Access the configured
FE_DOMAIN, open the workflow editing interface, and confirm no client error messages are displayed. - Import a single slaughter batch record, verify that data is successfully written to the database with no connection error prompts.
- Trigger an exception report generation task, confirm that multi-source data such as quarantine and temperature test results for the corresponding batch can be associated.
- Check storage node access logs, confirm there are no frequent connection timeouts or failure records.
The values provided are common starting points, and should be evaluated against your own specific samples.