What this category’s data looks like
Data for this category comes from special equipment safety supervision systems, inspection and testing institution systems, user unit ledgers, and operator certificate databases. It is updated once per month. Daily documents include use registration certificates, periodic inspection reports, maintenance records, hidden danger rectification notices, accident reports, and operator certificates. Core fields include unique device number, inspection validity period, maintenance cycle nodes, operator certificate number and validity period, hidden danger rectification status, and others. The data structure is built around full lifecycle management of equipment, with no redundant extra fields.
Constraints these characteristics impose on tool calling and plugins
Decentralized data sources require tool calling to integrate with multiple heterogeneous systems. Plugin parameters adapted to different data sources must be configured. The monthly update frequency means the plugin’s data synchronization cycle must match the business rhythm. This avoids frequent pulling of redundant data or missing update deadlines. Multiple document types correspond to different field rules. Tool calling must design precise parsing logic for core fields such as device number, inspection validity period, and operator qualifications. The most time-consuming verification step requires tools to automatically pull associated data for matching. This reduces manual verification workload, while also handling abnormal cross-system data inconsistency scenarios. Errors can lead to equipment shutdown, administrative penalties, or special equipment accidents. The accuracy of tool calling directly affects supervision effectiveness. The scope and data sources of tool calling must be strictly limited.
How to set configurations
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
toolChoice parameter | Limited to designated supervision tools | Matches the fixed business tool requirements for special equipment supervision |
functionCall parameter | Enabled and bound to a custom data pull function | Enables precise pulling of cross-system supervision data |
| Tool calling trigger rule | Triggered only at business process nodes | Avoids unnecessary resource consumption from meaningless calls |
| Single call timeout period | 60 seconds | Adapts to the reasonable response duration for cross-system data pulling |
| Historical context retention count | First 15 conversations | Focuses on the context of the current handling process |
| Data cache period | 7 days | Matches the monthly data update frequency |
| Retrieved document limit | First 4 documents | Focuses on core supervision documents |
Three common mistakes
- Phenomenon: Tool calling is triggered frequently outside of business hours, leading to excessive API call usage. Cause: No rule for triggering tool calls only at business process nodes is configured, and unrestricted automatic calls are enabled.
- Phenomenon: The plugin triggers once after the first conversation, and repeated calls occur in subsequent conversations within the same process. Cause: No limit is set for the plugin to trigger only once per conversation, and the number of calls is not locked.
- Phenomenon: Non-supervision document content is accidentally included in business process guidance. Cause: The knowledge base retrieval scope for tool calling is not limited, and full knowledge base data loads by default.
How to confirm configurations are correct
- Trigger a simulated special equipment business process node, and verify that tool calling only triggers at this node.
- Start two consecutive conversations in the same process, and confirm the plugin triggers only once during the first conversation.
- View tool calling logs, and confirm all retrieved documents are core special equipment supervision documents.
- Initiate a simulated timed-out call, and confirm the system returns expected error feedback.
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.