What data for this category looks like
This category covers the entire production workflow for carbonated drink, juice, tea, functional beverage, and packaged drinking water factories. Daily documentation includes recipe sheets, water treatment records, blending records, sterilization or aseptic filling records, packaging material inspections, and finished product inspections. Data sources include water source and raw material testing systems, recipe systems, online sugar and acidity monitoring equipment, filling equipment, visual inspection equipment, and LIMS systems. Data updates occur per batch, per shift, or at continuous intervals. Fields include batch number, Brix value, filling liquid level, colony detection value, packaging material batch number, and more. Units include °Brix, mm, CFU/mL, and more.
What constraints this category's characteristics impose on HTTP interfaces and external systems
The multi-source, heterogeneous data characteristics of this category require HTTP interfaces to support integration with multiple external systems, and compatibility with different systems’ field formats and units. High-frequency real-time continuous collection data (such as filling liquid level data) and low-frequency batch shift report data (such as water treatment records) exist side by side. Interfaces must support both real-time push and batch pull capabilities. Data fields include professional physical and chemical indicators and production identifiers. Interfaces must support custom field mapping to avoid returning redundant fields not needed for production ledgers. Compliance requirements for production data also require interfaces to run legality checks on fields such as input material quantities and detection values. This prevents abnormal data from entering the ledger summary process.
How to configure settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
Authorization | Bearer {custom API key} | Complies with identity verification specifications for external system interfaces, ensuring secure data transmission |
variables | {"batchScope": "recent 7 days of production batches", "dataSources": ["recipe system", "LIMS", "filling equipment", "visual inspection equipment"]} | Limits the scope and sources of ledger data pulled by the interface, accurately matching summary requirements |
responseData | Only retain batch number, Brix, filling liquid level, colony detection value | Filters redundant fields, reduces invalid data transmission, and improves summary efficiency |
| Interface timeout period | 300 seconds | Adapts to the time required for pulling multi-source data, preventing request interruptions due to large data volumes |
| Field legality check | Enabled | Verifies the valid ranges of input material quantities and physical and chemical indicators, preventing abnormal data from entering the ledger workflow |
Three common configuration mistakes
- The interface returns a large number of redundant reference fields, leading to low ledger summary efficiency. This occurs because the
responseDataconfiguration is not used to limit returned fields, and full raw data from external systems is pulled directly. - The interface returns a 401 Unauthorized status code, making it impossible to pull production data. This occurs because the
Authorizationparameter is not configured correctly, or an expired API key is used. - Batch data pulled by the interface lacks the filling liquid level field, leading to incomplete ledger reports. This occurs because the
variablesconfiguration does not specify the filling equipment data source, or the filling liquid level field is not associated during field mapping.
How to confirm configuration is correctly applied
- Call the HTTP interface configured with FastGPT v4.17.0, and check that the returned result fields only include the preset core production ledger fields, with no redundant reference content.
- Send a request using an expired API key, and confirm that the interface returns a 401 Unauthorized status code. This verifies that the identity verification configuration is active.
- Manually pass parameters that do not include the specified data sources, and check that the interface only returns ledger data from the corresponding data sources. This verifies that the scope limitation configuration is active.
- Send a batch pull request, and confirm that the interface completes the response within 300 seconds. This verifies that the timeout configuration is appropriate.
The values provided here are common starting points, and should be evaluated against the user’s own samples.