What the data for this category looks like
Reference only; verify against the target FastGPT release and deployment documentation.
What constraints do these characteristics impose on the "tool calling and plugins" workflow
The multi-source heterogeneous real-time and non-real-time data characteristics of the basic chemical industry create multiple constraints for tool calling and plugin configuration. The second-level update requirement for real-time operating parameters requires that the response delay of tool calls be controlled within a reasonable range to avoid obtaining outdated data. Differences in API formats across different systems require plugins to adapt to different request structures and return parsing rules. Multi-field documents such as equipment ledgers and safety inspection records require accurate matching of field definitions during tool calls to avoid parameter misalignment. Scheduling and attendance data related to employee services need to connect to the permission interface of the HR system via plugins to ensure that only content accessible to the corresponding role is returned. toolChoice must be configured as needed to call tools for corresponding systems; fixed calls to a single tool cannot adapt to multi-source data scenarios.
How to set the configurations
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
toolChoice | auto | Adapts to the multi-system data calling scenario of the basic chemical industry, automatically matching corresponding tool interfaces |
functionCall | enabled | Enables tool calling capabilities, supporting connection to system APIs such as ERP and DCS |
| Tool call timeout setting | 30 seconds | The real-time data update frequency in the basic chemical industry is high; an overly long timeout will lead to obtaining outdated data |
| Single tool call return limit | Top 10 entries | Single equipment ledger and material data volume in the basic chemical industry is large, avoiding excessive returned data that causes timeout |
| Tool call result cache duration | 5 minutes | Balances data timeliness and call frequency, avoiding repeated requests that occupy system resources |
| Tool call retry count | 2 times | Addresses temporary network fluctuations or API temporary failures, reducing call failure rates |
Three common mistakes
- Phenomenon: A "missing parameter" error is returned during tool calling, with status code 400. Cause: The field definition of basic chemical industry data is not correctly matched. For example, the "rated pressure" field of equipment is mistakenly written as "pressure", and the unit information is not carried, causing the API to fail to parse.
- Phenomenon: Only the first tool returns results during multi-tool sequential execution, and subsequent tools have no response. Cause:
toolChoiceis not correctly configured asauto; fixed calls to a single tool prevent subsequent system APIs from being triggered, corresponding to the sequential execution exception issue mentioned in the source material. - Phenomenon: An "invalid key" error is displayed when calling the FastGPT chat application via Java. Cause: The appId is mistakenly used as the API key, and the correct calling key is not obtained in the corresponding interface, corresponding to the key acquisition question mentioned in the source material.
How to confirm the configuration is complete
- Initiate a test call, check whether the returned data contains the complete fields of the target basic chemical industry equipment, and verify that the field names and units are consistent with the local ledger.
- Simulate a multi-tool calling scenario to confirm that all configured tools can be triggered as expected and return data from the corresponding system.
- Switch test accounts with different roles to verify that the returned employee service and equipment data only include content accessible to that role.
- Simulate a network fluctuation scenario to confirm that tool calls will retry according to the configured retry count, and trigger the corresponding error prompt after timeout.
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.