What This Category of Data Looks Like
Data for this category comes from monitoring systems, ticketing systems, contract documents, and customer communication logs. Update frequency is monthly or quarterly. Daily deliverable documents include SLA clauses, monthly service reports, availability statistics reports, and customer review minutes. Core fields include service indicators bound to contracts, event occurrence time periods, response processing durations, and customer feedback records. There are no fixed unified units. Units must be matched according to the corresponding indicators.
Constraints for Tool Calling and Plugins Workflows
Data sources are scattered and require cross-system data pulling. Tool calling must configure multi-source data docking permissions to avoid single-call timeouts. Update frequency is fixed, so plugins must support periodic task triggering to avoid repeatedly pulling expired data. Document structures include exclusive indicators bound to contracts. Tool calling must pass the contract number as a filter parameter to ensure data matches the corresponding customer. Core fields have no unified units, so plugins must support dynamic adaptation of field formats to avoid data parsing failures. The volume of cross-system pulled data is large, so reasonable pagination and timeout limits must be set to prevent task interruptions.
How to Set Configurations
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
toolChoice | auto | Adapt to dynamic calling requirements for multi-source data pulling, automatically match available tools |
functionCall | Set based on actual test calibration | Target complex logic for SLA indicator calculation, trigger specified tools as needed |
| Periodic trigger interval | 30 days | Match the update rhythm of monthly service reports, avoid repeatedly pulling expired data |
| Multi-source data timeout threshold | 600 seconds | Adapt to time consumption requirements for pulling monitoring and ticketing data across systems |
| Maximum number of data entries pulled per single request | First 1000 entries | Adapt to data pagination limits of ticketing systems, avoid overload during single calls |
| Field format adaptation rules | Adjust dynamically based on data source | Adapt to field format differences across different data sources, meet core field matching requirements |
Three Common Configuration Mistakes
- Tool calling returns empty results, and the interface displays that no valid data was matched. The cause is that the contract number filter switch was not enabled, pulling irrelevant data across customers.
- Plugin execution times out, returning a 504 status code. The cause is that the multi-source data timeout threshold was set too short to complete cross-system data pulling.
- The large language model does not correctly reference SLA data returned by the plugin, only outputting generic responses. The cause is that the trigger rules for
functionCallwere not configured, so tool calling was not activated.
How to Verify Proper Configuration
This document applies to FastGPT v4.17.0.
- Manually trigger plugin calling, pass a test contract number, and check whether returned data only includes SLA indicators and corresponding records bound to that contract.
- View plugin execution logs to confirm multi-source data pulling time does not exceed the set threshold.
- Verify that the
toolChoiceparameter is set toautoto ensure the tool calling logic is correctly activated. - Simulate a monthly update cycle to check whether the plugin automatically triggers tasks at the set interval.
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 2026-10-19.