What data looks like for this category
Data for this category includes documents such as process routes, operation cards, tool lists, CNC programs, first-piece inspection records, patrol inspection forms, and measuring tool calibration records. Data sources include product drawings and 3D models, CAPP/CAM systems, machine tool collection data, tool management systems, MES systems, and inspection tool detection data. Data updates trigger per work order, per workpiece, per sampling batch, or tool change. Fields include operation number, tool model and service life, cutting parameters, dimensional deviation values, inspection results, and more. Common units are millimeters, seconds, revolutions per minute, and similar.
What constraints do these characteristics impose on HTTP interfaces and external systems
Multi-source heterogeneous data sources require HTTP interfaces to support receiving structured and unstructured data from different external systems, and avoid relying solely on the system's built-in historical context stitching. High-frequency update characteristics require interface configuration to adapt to real-time or near-real-time request frequencies, and avoid data lag. Diverse document types and fields require interface parameters to clearly specify data types and corresponding field mappings, and prevent field parsing errors. Additionally, the large volume of multi-link data associated with a single work order requires the interface to support batch data submission parameter configuration, to adapt to the load limit of single transmission.
How to configure
| Configuration Item | Recommended Practice | Rationale |
|---|---|---|
Authorization | Bearer {custom API key} | Complies with FastGPT interface authentication standards, ensures secure external system calls |
variables | Populate operation, tool, and inspection record fields with work order-related data | Adapts to multi-source data transmission needs, replaces the system's historical context stitching |
responseData | Return only summarized ledger fields and download links for generated reports | Streamlines returned content, adapts to external system data receiving logic |
| Request timeout | 60–120 seconds | Adapts to transmission time of large files such as CNC programs and process routes |
| Batch submission limit | First 10 work order data entries | Matches the frequency of single-batch data updates, avoids interface overload |
| Single file transfer limit | 1000 MB | Adapts to common storage sizes of CNC programs |
Three common mistakes
- Phenomenon: Ledger data returned by the interface lacks the current work order's tool wear records. Cause: The real-time data from the tool management system was not passed via the
variablesparameter during the call, relying on the system's default historical record stitching instead, so the latest tool status cannot be obtained. - Phenomenon: The interface returns a 408 status code. Cause: The request timeout was not set appropriately, and the transmission time of large files such as CNC programs exceeded the default threshold.
- Phenomenon: The generated report does not include process dimensional deviation data. Cause: The detection result fields of the inspection tools were not mapped in the passed parameters, so the data was not included in the summary.
How to confirm correct configuration
- In the interface debugging panel of FastGPT v4.17.0, call the test interface and pass simulated work order data, check if the returned
responseDataincludes the specified ledger fields. - View the interface authentication log, confirm that the format of the
Authorizationparameter meets requirements, with no authentication failure errors. - Submit batch work order data, check that the interface does not return overload errors, confirm that the batch submission limit is set reasonably.
- Compare the passed
variablesparameter with the generated report content, confirm that business data has been correctly bound, and no system historical records are relied on.
The values provided are common starting points and should be evaluated against the reader's own samples.