What the data for this category looks like
Construction machinery ledger data primarily comes from three sources: device IoT terminals, on-site operation and maintenance systems, and after-sales maintenance logs. Data update rhythm falls into two categories: real-time equipment operating condition data updates every second, while daily aggregated data such as operating duration and maintenance records updates every early morning. A single ledger document includes fields such as equipment number, model, rated power, cumulative operating duration (unit: hours), daily fuel consumption (unit: liters), last maintenance date, and operation times (unit: times). The length of a single complete document falls within the standard range for conventional business data.
What constraints these characteristics impose on the HTTP Interfaces and External Systems link
Heterogeneous data from multiple sources requires the interface to support pulling ledger data from different systems simultaneously, so the interface must support parsing logic for multiple data formats. The short-interval updates of real-time operating condition data require the interface to support high-frequency calls, and a reasonable timeout configuration must be set to avoid request interruptions. The unique units for construction machinery ledgers (hours, liters, times) require the interface to retain unit information during data transmission and parsing to avoid field parsing errors. The daily data volume for a single device is large, so batch pulling must support pagination parameters to prevent overload from single requests from affecting system stability.
How to set the configuration
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Single Request Limit | Top 20 entries | Adapt to the data volume of multi-device ledgers per batch and avoid request timeouts |
| Timeout Duration | 600 seconds | Adapt to network latency of internal systems for state-owned enterprises and time required for bulk data pulling |
| Authentication Method | Bearer Token | Aligns with common authentication specifications for internal systems of state-owned enterprises |
| Variable Mapping Rule | One-to-one correspondence with ledger fields | Ensure that incoming parameters match fields such as equipment number and operating duration of construction machinery ledgers |
| Response Format | JSON | Consistent with the interface parsing requirements of FastGPT |
| Chunk Length | 800–1200 characters | Adapt to the average length of single ledger documents |
Three common mistakes
- Calling the interface returns 401 Unauthorized, with no valid authentication information carried. The cause is incorrect configuration of the
Authorizationheader, or use of an expired or invalid authentication key. - Calling a shared link fails to associate ledger data for the specified device, and the returned report is empty. The cause is that no custom variables were added to the interface configuration, and the device ID was not passed as a parameter.
- The operation duration unit in the generated report is displayed incorrectly, or the recommended questions do not associate ledger data for the current device. The cause is that no field mapping rules were configured in
variablesorresponseData, leading to failed data parsing or context association.
How to confirm the configuration is correct
- Send a test request and check if the returned JSON structure includes unique fields for construction machinery ledgers such as equipment number, cumulative operating duration, and daily fuel consumption.
- Check that the interface returns a 200 OK status code, and the authentication information carried in the
Authorizationheader is valid. - Verify that the number of results from the batch request matches the configured single request limit, with no data truncation.
- Review the generated report to confirm that units for fields such as operating duration and fuel consumption match the ledger data, with no parsing errors.
The values provided are common starting points and should be measured against the reader'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.