What Data for This Category Looks Like
Data comes primarily from manufacturing execution systems (MES), raw material inventory ledgers, online quality inspection equipment, and finished product outbound systems. Updates trigger for each production batch. A corresponding ledger entry is created once a single batch completes processing. Document structure includes furnace batch numbers, processing step parameters, raw material grades, online inspection values, finished product specifications, and transfer node records. Fields include character-type furnace batch numbers, numeric processing temperatures and durations, and date-type transfer times. Units are unspecified, degrees Celsius, minutes, and days respectively. The length of a single ledger document fluctuates based on processing step complexity, typically falling between 300 and 800 characters.
Constraints for HTTP Interfaces and External Systems
Ledgers are generated per production batch and sourced from multiple dispersed systems. Interfaces must support query parameters based on furnace batch numbers and transfer time ranges. This prevents excessive resource usage from full data pulls. Fields include multiple data types. Interfaces must support transmission and parsing of numeric, character, and date-type parameters. Single documents have moderate length, but data volume varies widely across batches. Interfaces must support paginated responses to prevent overloading single requests. Data comes from multiple internal systems. Interfaces must include multi-source data aggregation logic to ensure complete ledger information. Additionally, internal system access is restricted. Interfaces must adapt to intranet deployment access rules to avoid cross-domain or permission verification failures.
Reference only; verify against the target FastGPT release and deployment documentation.
How to Set Configurations
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
Authorization | Bearer {<dedicated API key>} | Used for interface identity verification, adapts to intranet access permission controls |
variables | {"batch_no": "<target batch number>", "start_date": "<production completion date>"} | Passes filter parameters for ledger queries, matches requirements for pulling data per production batch |
responseData | Return only furnace batch numbers, processing parameters, and quality inspection result fields | Filters redundant data, focuses on core information for ledger summary |
| Request timeout | 30-60 seconds | Metal material processing ledgers require aggregation across multiple systems; this duration covers most scenarios |
| Items returned per request | First 10 items | Single batch ledger data volume is moderate; too many entries increase subsequent processing load |
| Multi-source data aggregation configuration | Calibrated based on actual testing | Internal system interface formats vary, adjustments must be made based on actual integration conditions |
Three Common Misconfigurations
- A 401 Unauthorized error is returned when calling the interface, or a custom connection test fails directly. The
Authorizationparameter is not configured correctly, or theBearerprefix is missing from the key format, causing identity verification to fail. - Interface calls time out, or empty ledger data is returned. The request timeout duration is set too short, which does not match the actual time required for multi-system data aggregation in metal material processing, leading to premature request termination.
- After accessing via an nginx reverse proxy on an intranet, uploading associated data or calling interfaces throws exceptions. Necessary request headers are not forwarded in the nginx configuration, and intranet deployment permission control rules are not adapted, preventing the service from receiving requests normally.
How to Confirm Configurations Are Correct
- Run the preset curl test command. Check that the returned response status code matches the expected value, and that core ledger fields are included.
- Enter correct parameters in the FastGPT interface debugging screen and initiate a test. Confirm that no errors occur and the returned data matches the expected batch range.
- Review system operation logs. Confirm that interface request parameters are parsed correctly, with no format errors or permission interception records.
- Trigger the ledger summary and report generation workflow. Check that the fields included in the generated report match the
responseDataparameter configuration.
All values provided here are common starting points. They should be evaluated against the user’s own samples.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-09-28.