What this category of data looks like
This category of data covers the entire production process for hot rolling, cold rolling, section steel, and steel pipe manufacturing. Daily documents include rolling plans, heating schedules, rolling specifications, plate shape and thickness records, surface quality reports, and quality certificates. Data sources include slab or billet batches, heating furnaces, mill automatic control systems, online thickness and width measuring equipment, surface inspection devices, and MES systems. Data is generated in real time per coil or steel bundle. Fields include batch numbers, temperature parameters, thickness tolerances, surface defect levels, and more. It supports full-link traceability at the coil level.
What constraints these characteristics impose on the HTTP Interfaces and External Systems link
Real-time data generated per coil or steel bundle requires HTTP interfaces to support low-latency requests. This prevents use of lagging data during audit workflows. Diverse heterogeneous data sources — including equipment control systems, inspection devices, and MES systems — require interfaces to support varied parameter formats and field mappings. The coil-level full-link traceability requirement mandates that interfaces carry unique batch identifiers to complete data binding and association. High-frequency production data submissions require limiting concurrent request volume per interface to avoid overloading external systems. Transfer of document-style data such as quality certificates and surface quality reports requires support for large payloads. Reasonable timeout and retry strategies must be configured.
How to set up configurations
These configurations are based on FastGPT v4.17.0.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
Authorization | Bearer {FastGPT API Key} | Complies with HTTP interface authentication standards to ensure the legality of external system calls |
variables | Pass business fields such as batch numbers, steel coil specifications, and inspection results | Binds coil-level data to support precise matching for supplier and process quality audits |
responseData | Return fields such as audit results, defect judgments, and rectification suggestions | Directly outputs structured data that conforms to production audit processes, facilitating integration with external systems |
| Request timeout | 30–60 seconds | Matches the update rhythm of real-time production data to avoid request interruptions caused by network delays |
| Retry attempts | First 2 attempts | Addresses temporary network fluctuations and prevents audit process termination from a single failed request |
| Concurrent request limit | 10 requests per second per node | Adapts to the high-frequency data submission rhythm of production links and avoids overloading external systems |
Three common errors
- Phenomenon: Interface calls return authentication failure or empty model responses, and errors occur when connecting to third-party models. Cause: The
Authorizationparameter is not configured correctly, or necessary business context parameters are not passed invariables. - Phenomenon: The steel coil batch field passed by the external system is empty, audit results have no corresponding data, and audit records from different business entities are mixed. Cause: No unique user or batch identifier is carried in the interface request, and data isolation configuration is not completed.
- Phenomenon: Uploading large documents such as surface quality reports fails, and the interface returns a request body too large error. Cause: No allow threshold for large payload requests is configured, and the interface's request body size limit is not adjusted.
How to confirm the configuration is correct
- Use the interface debugging tool included in FastGPT v4.17.0, pass the
variablesparameters for a known steel coil batch, and check whetherresponseDatareturns the audit result fields corresponding to the batch. - View the interface authentication log to confirm that the format of the
Authorizationparameter matches the key, and there are no authentication failure records. - Simulate high-frequency requests to check the interface's concurrent processing capability and confirm that there are no request limit exceeded errors.
- Pass a large-volume surface quality report document to check whether the interface can receive and process the request normally.
The values provided are common starting points and should be measured against the reader's own samples.