What data for this category looks like
Data for this category comes from customer surface treatment specifications, tank solution laboratory tests, rectifier operation data, online water quality monitoring equipment, and hazardous waste management ledgers. Daily documents include tank solution analysis records, process parameter cards, fixture records, film thickness and adhesion reports, hazardous waste ledgers, and wastewater monitoring records. Data updates occur per tank batch, per shift, or per fixed monitoring requirements. Document fields include tank solution temperature, current strength, pH value, film thickness values, wastewater pollutant concentration, fixture batch numbers, and similar items. Common associated units are ℃, A, μm, mg/L.
Constraints Imposed on HTTP Interfaces and External Systems
Data sources for this category include direct device uploads and manually entered documents, with significant format differences. This requires HTTP interfaces to support multiple request and response formats. The high-frequency update rhythm (per tank batch, per shift) requires interfaces to support calls at short intervals, and single-response delay must be controlled within a reasonable range. Document fields have dedicated units such as film thickness μm and current A. Interfaces must clarify field mapping rules to avoid unit conversion errors. Some data involves environmental compliance requirements. Interfaces must ensure complete data transmission without loss of key fields. There is also a need for batch submission of multi-batch data, which requires interfaces to support batch request processing in array form.
How to Configure Settings
The following configuration items are based on the interface logic of FastGPT v4.17.0.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
Authorization | Bearer {custom interface key} | Verifies the identity of external system calls to prevent unauthorized access |
variables | Bind tank solution batch number, film thickness detection values, and wastewater monitoring data fields | Injects business context data into interface request parameters |
responseData | Extract audit results, compliance check flags, and exception prompt fields | Accurately retrieves core business data returned by the interface |
| Timeout period | 10–30 seconds | Adapts to typical delays in device data uploads, avoids frequent timeout triggers |
| Batch request limit | First 50 entries | Matches typical data volumes per shift or single tank batch processing, reduces interface load |
| Field mapping rules | Match interface parameters using business document field names | Ensures accurate transfer of business data, reduces unit or format conversion errors |
Three Common Misconfigurations
- Phenomenon: Audit text returned by the interface has syntax errors due to lack of formatting processing, such as consecutively concatenated statements that cannot be parsed normally. Cause: Long text returned by the interface is not segmented or provided with necessary separators, and is directly passed to subsequent processing nodes.
- Phenomenon: Interface calls return a 401 unauthorized error. Cause: The
Authorizationparameter is configured incorrectly, with the custom interface key not filled correctly or the format not meeting requirements. - Phenomenon: Some entries are not processed when submitting data in batches. Cause: The batch request limit is set too small, not matching the actual submitted data volume, resulting in the interface truncating unprocessed entries.
How to Confirm Configuration Is Complete
- Call the test interface, check if
responseDatacorrectly extracts the expected audit result fields, with no missing or incorrectly mapped fields. - Simulate frequent interface calls, confirm that response delay matches the preset timeout configuration, with no frequent timeout errors.
- Submit batch data, check if the interface processes all submitted entries with no omissions.
- Verify identity configuration: use an invalid key to call the interface, confirm that an unauthorized error is returned, ensuring identity verification is effective.
The values provided are common starting points and should be measured against the reader's own samples.