What data this category includes
Data covered by this category includes measuring tool ledgers, calibration plans, calibration certificates, periodic verification records, original test records, reference material ledgers, and deviation handling documents. Data sources include internal enterprise metrology management systems, external calibration institution certificates, standard instruments, LIMS systems, and environmental monitoring equipment. Data updates are triggered by calibration cycles, completion of individual tests, or abnormal situations, with no fixed, unified schedule. Document fields include instrument number, calibration validity period, measured value, measurement uncertainty, traceability identifier, and others. Units include specialized metrology units such as length, mass, and time.
Constraints imposed on HTTP interfaces and external systems
The data characteristics of this category impose multiple constraints on HTTP interface configuration. Multiple data sources require interfaces to support multiple authentication methods to adapt to the access specifications of different external systems. Uncertain update frequencies require interfaces to support both on-demand pull and event-triggered invocation modes to avoid invalid requests. Complex specialized metrology fields require interface returned data to be structured, and return fields to be specified via parameters, to ensure data meets the traceability requirements of the metrology system. Large-volume calibration certificate data requires interfaces to configure sufficient timeout periods to avoid transmission interruptions. Additionally, the requirement for high data credibility requires complete invocation logs to be retained for subsequent traceability audits.
How to configure settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
Authorization | Bearer {metrology system API token} | Identity authentication is required for connecting to internal metrology management systems, which meets the traceability and security requirements for metrology data |
variables | {"calibrationCycleRange": "30-365 days", "maxRetryTimes": 3} | Adapts to the calibration cycles of different types of instruments, and sets a reasonable number of retries to avoid repeatedly triggering abnormal requests |
responseData | Return only instrument number, calibration certificate number, measured value, uncertainty, traceability identifier | Filters redundant data, reduces transmission load, and ensures returned fields meet the core requirements of metrology audits |
| Interface timeout period | 600 seconds | Adapts to the transmission requirements of large-volume calibration certificates, and avoids invocation failures caused by timeouts |
| Retry trigger condition | Status code 5xx, network timeout | Triggers retries only when there is a server exception or network fluctuation, to avoid repeatedly submitting legitimate requests |
| FastGPT version | FastGPT v4.17.0 | This version supports structured responseData configuration and persistent storage of authentication parameters |
Three common configuration mistakes
- Invocation fails with the prompt
invalid token, and configuration is lost after restarting the FastGPT service. This occurs because theAuthorizationparameter was not saved to persistent configuration, and only temporary cache was used, leading to configuration failure after restart. - The interface returns incomplete data fields that cannot meet the core requirements of metrology audits. This occurs because the required return fields were not specified via the
responseDataconfiguration, and unstructured redundant data was returned by default, resulting in missing core information such as instrument number and measurement uncertainty. - Interface invocation times out, with the prompt
request timeout. This occurs because the timeout period was set too short, which does not adapt to the transmission requirements of large-volume data such as calibration certificates, leading to interrupted connections before data is fully pulled.
How to verify successful configuration
- Manually trigger an interface invocation, and check if the returned
responseDataincludes core metrology fields such as instrument number, calibration certificate number, and measured value. - Restart the FastGPT service, and verify that the
Authorizationconfiguration is still retained without loss. - Simulate a server exception status code such as 500, and confirm that the system automatically triggers the retry mechanism.
- Compare the interface returned data with the original data from the internal metrology management system, and confirm that the fields and units match correctly.
The values provided are common starting points and should be evaluated against relevant samples.