What Data for This Category Looks Like
Data related to internal office and employee services for construction machinery comes primarily from equipment operation data collection terminals, internal enterprise production and maintenance systems, and employee attendance and work order platforms. Update frequencies vary: real-time collection of equipment operation parameters, daily synchronization of maintenance work orders, and monthly aggregation of employee service records. Each data entry includes equipment unique identifier, operation duration, fuel consumption value, fault code, associated work order number, employee ID, and service type. Field units include hours, liters, entries, and times. Most documents are stored in structured JSON or CSV format to support batch reading and parsing.
Constraints Imposed on Tool Calling and Plugin Configuration
The multi-source, heterogeneous data characteristics of construction machinery create multiple constraints for tool calling and plugin setup. Real-time equipment operation data updates frequently, so tool calling interface response times must match collection intervals to prevent data return from lagging behind business scenarios. Field naming differs across source systems, so plugins need unified field mapping rules before calls to adapt to varying return structures from equipment terminals and maintenance systems. Unique identifier fields such as equipment numbers and fault codes require strict binding. Accurate associated parameters must be passed during tool calls, otherwise matching operation and maintenance or service records will fail. The association logic between employee service and equipment maintenance data requires plugins to carry both employee ID and equipment identification when called, to ensure returned results align with specific business scenarios.
Configuration Settings
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Tool calling mode | Select functionCall mode | Adapt to the structured calling requirements of construction machinery data, and clearly specify the target plugin and parameter format for calls |
| Plugin trigger condition | Triggered by employee-initiated service requests, with a delay of no more than 10 seconds | Match real-time response requirements for internal office work, and avoid excessive employee waiting time |
| Field mapping rules | Map according to: equipment number → equipment unique identifier, work order number → associated work order number | Adapt to field differences across multiple systems, and ensure accurate data association |
| Tool calling timeout | 30–60 seconds | Cover conventional response times for equipment data pulling and operation and maintenance work order queries |
| Associated parameter verification | Verify that both employee ID and equipment number exist | Avoid invalid calls, and ensure service results are bound to specific scenarios |
| Return result parsing method | Extract fault handling suggestions and operation and maintenance progress using structured fields | Adapt to standardized parsing requirements for construction machinery data |
Three Common Configuration Errors
- A 401 status code returns during tool calls, but the same API key works in Postman. This occurs when the FastGPT system key is not correctly bound in the plugin configuration, or the key does not have permission to call the target plugin.
- Tool calls return empty result fields, and no matching equipment maintenance records can be found. This happens when no field mapping rules are configured, or the format of passed associated parameters such as equipment numbers is incorrect.
- An unAuthChat error appears after plugin triggering, even though an API key has been entered. This is because the plugin's identity verification logic does not match FastGPT's calling format, and preset verification parameters are not properly included.
How to Verify a Complete Configuration
- Initiate a simulated employee service request, and confirm that tool call parameters include associated fields such as equipment number and employee ID.
- Check tool call logs to confirm returned result fields match preset mapping rules.
- Call the test plugin to verify response time meets preset timeout configuration requirements.
- Review plugin permission settings to confirm FastGPT's calling identity has passed verification.
Note that the values listed here are common starting points, and should be evaluated against the reader's own specific 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.