What the Data for This Category Looks Like
Daily documents for this category include formulas and feeding lists, production records, baking or steaming curves, metal detection records, cleaning and disinfection records, and factory inspection reports. Data sources include raw and auxiliary material qualification certificates, ERP/MES systems, weighing systems, ovens or frying lines, laboratory equipment, and food traceability ledgers. Data updates run per production batch, shift, or daily. Document fields include allergen material lists, feeding weights, baking temperatures and durations, test results, and some documents must be linked to batch traceability information.
Constraints Imposed on Deployment and Upgrade
The high-frequency line changes and multi-batch data update characteristics of this category require support for quickly switching knowledge bases for different production lines during deployment, to avoid confusion of process data across batches. The mixed storage need for multiple document types requires configuring a storage solution that supports both structured and unstructured data. Handling sensitive fields such as allergens and foreign matter control requires configuring data permission isolation rules during deployment to prevent sensitive information leaks. The high-frequency update rhythm of daily and shift-based updates requires configuring an automatic synchronization mechanism to ensure the latest production records and test data are accessed by the system in a timely manner.
How to Configure Settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
DB_MAX_LINK | 100–200 records | Adapts to batch reading demands for multi-batch production documents, avoids overload from single requests |
REDIS_URL | Local Redis instance, port 6379 | Caches frequently accessed process parameters and batch information to improve retrieval speed |
STORAGE_S3_ENDPOINT | Configured per the enterprise’s existing object storage endpoint | Supports storage for multiple types of production documents, compatible with large files such as baking curves |
| Maximum file upload limit | 1000 MB | Supports storing complete baking or steaming curve log files |
ROOT_KEY | Configured per the enterprise’s permission system | Enables permission isolation for sensitive fields, ensuring allergen data is only accessible to authorized personnel |
Three Common Misconfigurations
- Phenomenon: After deploying the marker component, logs show OCR error, and printed or handwritten test data in production records cannot be parsed. Cause: OCR model parameters adapted to food packaging printing fonts are not configured, or object storage permissions are insufficient to read test image files.
- Phenomenon: The locally deployed FastGPT v4.8.12 version cannot properly parse complex formulas in process documents. Cause: The built-in formula parsing plugin of this version has compatibility flaws. Upgrade to FastGPT v4.17.0 or a later version.
- Phenomenon: An error triggers when using a third-party model API key for testing, and exception reports cannot be generated. Cause: The valid key for model calls is not configured correctly, or the timeout threshold for model requests does not meet business requirements.
How to Verify Successful Configuration
- Import a batch of formula and metal detection records, confirm the system can fully extract field information from the documents.
- Trigger an exception report generation process, confirm the generated report includes core data such as baking temperature and feeding amount for the corresponding batch.
- Check system logs, confirm there are no error messages about exceeded database connection limits or failed storage access.
- Test the permission isolation rules, confirm sensitive fields can only be accessed by authorized roles.
The values provided here are common starting points and should be measured against the reader's own samples.