This page applies to FastGPT v4.17.0.
What this category of data looks like
Data sources for this category include manufacturing execution systems (MES), online inspection equipment, laboratory test results, process parameter records, customer quality standards, and historical defect databases. Data is collected continuously on a production batch and shift cycle basis, covering the full workflow from in-process product inspections to finished goods release. Daily output documents include control plans, inspection log sheets, SPC statistical reports, finished product inspection reports, non-conforming product review forms, release approval forms, and monthly quality summary reports. Data fields include batch number, inspection item parameters, test values, judgment results, responsible persons, approval status, and more. There are no unified fixed units; they vary based on the type of inspection item.
Constraints imposed on HTTP interfaces and external systems by these characteristics
This category of data comes from multiple dispersed systems and is updated frequently. HTTP interfaces must support multi-dimensional query parameters such as batch number, shift range, and time interval to accurately pull quality data for corresponding production batches. Differences in fields across multiple document types require interface responses to support dynamic field mapping, to adapt to the structures of different documents such as control plans and inspection reports. Sensitive release approval data requires interfaces to bind permission verification logic, so only authorized users can call them. Test data without unified units requires interfaces to support carrying unit parameters, or clearly mark unit information for corresponding fields in returned results.
How to Set Configurations
| Configuration Item | Recommended Setup | Rationale |
|---|---|---|
Authorization | Bearer [space] API key generated by the application | Complies with HTTP interface standard identity verification specifications, ensuring security for cross-system calls |
variables | Key-value pairs containing batch number, query start time, and inspection type; each key-value pair has a length of no more than 200 characters | Adapts to the requirement of pulling data by production batch and time range for this category, accurately locating target quality ledgers |
responseData | Field set mapped by document type, including batch number, test values, judgment results, and approval status | Adapts to the return format of multiple types of quality documents for this category, compatible with parsing logic of external systems |
| Timeout threshold | 600 seconds | Matches the average time required to pull data from multiple sources for this category, avoiding request interruptions during high-frequency calls |
| Field filtering rules | Only return business fields visible to the current caller with authorization | Reduces invalid data transmission and improves interface response speed |
Three Common Mistakes
- The interface returns a 401 Unauthorized status code, and quality ledger data cannot be pulled. The cause is that the
Authorizationparameter is not configured correctly, and a valid API key generated by the application is not used with the Bearer prefix. - The interface response time far exceeds results from interface testing. Calls through the FastGPT interface complete in a short time, but interface calls exceed the preset threshold without returning a response. The cause is that a reasonable timeout threshold is not set, or the interface request carries query parameters beyond the necessary scope, resulting in excessive data pull volume.
- The
responseDatafield in the interface return is empty, and external systems cannot parse inspection reports or release order content. The cause is that the correct document type or batch number is not specified invariables, so no matching data records are found.
How to Confirm the Configuration Is Complete
- On the API management page of the FastGPT application, copy the generated API key, add the Bearer prefix to the
Authorizationparameter, initiate a test request, and confirm that a 200 OK status code is returned. - Fill in known production batch numbers and time ranges in
variables, initiate a request, and compare the ledger data on the FastGPT interface to confirm that theresponseDatafield in the return contains inspection records for the corresponding batch. - Adjust the timeout threshold of the interface request, simulate a high-frequency call scenario, observe whether the interface response time meets the requirements of the business scenario, and optimize the threshold setting based on actual call conditions.
- Check whether the fields returned by the interface include the business fields required by the current external system, and confirm that the mapping rules of
responseDatamatch the parsing logic of the external system.
The values given are common starting points and should be measured against the reader's own samples.