What This Category's Data Looks Like
The data sources for this category include animal quarantine information, supplier batch records, production traceability data, real-time temperature collection, metal detection results, and laboratory inspection reports. Daily documents include quarantine certificates, slaughter and cutting records, ingredient marinating records, thermal processing operation records, cold chain temperature logs, and microbial inspection reports. Data updates are performed per production batch and each shift. Cold chain temperature data is updated via continuous collection. Data fields include batch number, quarantine number, raw material source, processing temperature, test results, and some fields require matching biosecurity-related identifiers.
Constraints on HTTP APIs and External Systems
Data must be associated with batches and quarantine information. APIs must support query parameters based on batch numbers and quarantine numbers to avoid mixing data across batches. The volume of continuously collected cold chain temperature data is large, so APIs must support paginated pulling or incremental synchronization to prevent single-request timeouts. Field formats vary across different documents: for example, temperature records are numeric, while inspection reports are text-based. APIs must support returning multiple types of data. Errors in the production process have serious consequences, so API calls must ensure data transmission integrity and timeliness to avoid delays that allow abnormal raw materials to enter production. Additionally, because raw materials carry biosecurity risks, sensitive data returned by APIs must be strictly isolated by permissions to prevent unauthorized access.
How to Configure Settings
These configurations apply to FastGPT v4.17.0.
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
Authorization | Bearer {custom secret} | Ensures identity legitimacy for API calls and prevents unauthorized access to sensitive production data |
variables | {"targetBatch": "{{userInput.batch}}", "quarantineCode": "{{userInput.quarantine}}" } | Passes batch numbers and quarantine codes as query parameters to match data association rules |
responseData | Aggregate and sort by batch and time | Organizes multiple types of ledger data by production batch and time dimension to meet the structural requirements of report generation |
| Request timeout | 600 seconds | Reserves sufficient time for data processing and transmission, as a single request must handle multi-batch cold chain temperature and inspection data |
| Synchronization trigger frequency | Every 30 minutes or triggered per production batch | Matches the rhythm of data updates per batch and shift, reducing redundant API calls |
| Data format validation | Enable batch and quarantine number matching validation | Prevents unassociated ledger data from being aggregated and ensures data accuracy |
Three Common Configuration Errors
- The symptom is an API returning a
401 Unauthorizedstatus code, with the interface displaying "Request not authorized". The cause is incorrect configuration of theAuthorizationparameter, including errors in secret key generation or transmission format. - The symptom is ledger data fields returned being empty or not matching expected values. The cause is that query parameters passed in
variablesdo not match the field names required by the external system's API, and batch or quarantine number rules are not followed. - The symptom is the interface loading state continuing indefinitely after configuration, eventually returning a timeout error. The cause is local server network restrictions causing a timeout for secret key verification requests, with insufficient network response time reserved.
How to Verify Successful Configuration
- Call the test API, pass a known production batch number, and verify that returned data includes business documents such as quarantine certificates and temperature records for the corresponding batch.
- Check API call logs to confirm that the
Authorizationparameter is correctly carried, with no authentication failure records. - Review data synchronization results to confirm that only new data within the specified time range is pulled, with no redundant or duplicate entries.
- Trigger the report generation process and verify that the generated report is sorted and categorized by batch and field, matching the structural requirements of business documents.
The values provided are common starting points and should be evaluated against the reader's own samples.