What the Data for This Category Looks Like
Business process data for non-ferrous metal smelting primarily comes from PLC control systems at production sites, manufacturing execution systems (MES), and electronic inspection reports from quality inspection departments. Data update frequencies fall into three categories: real-time collected equipment operating parameters, hourly synchronized material flow data, and daily updated finished product inspection results. Document structure uses individual business process records as units. Each record includes fields such as smelting furnace number, current process, material input quantity, furnace internal temperature, energy consumption data, current progress node, and some records include process abnormality alarm flags.
Constraints Imposed on Tool Calling and Plugin Workflows
The characteristics of smelting business data impose multiple constraints on tool calling and plugin configuration. Real-time collected equipment operating parameters require plugin interface response delays to stay within a reasonable range. Otherwise, business process guidance will experience lag. The structured multi-field data format requires plugin input and output parameter definitions to strictly match field names and units used in smelting scenarios. Otherwise, data parsing errors will occur. Daily updated inspection data requires plugins to support scheduled pulling, to avoid excessive system resource usage from full real-time synchronization. Business process nodes depend on current process status. Plugins must accurately read progress fields to trigger guidance logic. Missing fields or abnormal formats will directly cause guidance interruptions.
Reference only; verify against the target FastGPT release and deployment documentation.
How to Set the Configuration
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Plugin Timeout | 600 seconds | Matches the response requirements of real-time smelting business processes, prevents guidance process lag |
toolChoice | Auto-select | Adapts to scenarios with parallel tool calls, no need to manually specify a single tool |
functionCall | Enabled | Supports structured parameter passing, meets the multi-field format requirements of smelting data |
| Parameter Validation Switch | Enabled | Validates units and formats of input fields, avoids data parsing errors |
| Loop Execution Threshold | First 3 attempts | Adapts to the abnormal retry logic of smelting processes, prevents invalid loops from consuming resources |
| Scheduled Pull Interval | 1 hour | Matches the daily update rhythm of inspection data, balances real-time performance and system resource usage |
Three Common Misconfigurations
- Phenomenon: After adding a custom plugin to a workflow, no content is displayed in the input and output parameter fields. Cause: Plugin parameters are not defined according to the structured field format of smelting scenarios, causing the system to fail to parse the parameter structure.
- Phenomenon: Response delay exceeds expectations after calling the chat interface. Cause: Improper plugin timeout setting or incorrect scheduled pull interval configuration, leading to a large amount of data synchronization occupying interface resources.
- Phenomenon: A loop-executing plugin fails to traverse array elements as expected. Cause: The array input format of the loop body does not meet FastGPT requirements, and the material list data structure of the smelting business is not correctly matched.
How to Confirm Proper Configuration
- Manually trigger a plugin call, check if the returned result fields fully match the preset parameters of the smelting business.
- Simulate input data with abnormal formats, verify that the parameter validation switch can intercept erroneous inputs.
- Run a loop task, confirm that the plugin traverses the input array elements according to preset rules.
- Check interface logs, confirm that the response time of plugin calls meets the configured timeout requirements.
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.