What data for this category looks like
Data sources for non-ferrous metal smelting include real-time collection data from production control systems, offline inspection reports from quality inspection departments, and ledger data from production management systems. Update frequencies follow three patterns: minute-level updates for real-time collection data, daily updates for offline inspection data, and synchronized updates when production work orders are completed for ledger data. The document structure of a single data entry includes process nodes, corresponding parameter values, inspection time, and associated work order number. Fields include smelting temperature, electrolysis current, raw material input volume, and finished product output volume, with units of degrees Celsius, amperes, tons, and tons respectively.
What constraints these characteristics impose on the tool calling and plugin workflow
Minute-level real-time data updates require that tool calling trigger intervals do not exceed 5 minutes. If intervals exceed this threshold, returned parameters cannot match current production states, and accurate responses to real-time user consultations cannot be provided. Structured data with multiple fields requires that plugin calls clearly specify parameter fields for the target process, to avoid returning irrelevant data that causes redundant responses. Differences in data formats across sources require plugins to support parsing standardized interfaces from production control systems and offline inspection report templates, adapting to both data structures to cover different consultation needs. Parameter threshold requirements for non-ferrous metal smelting are strict. Parameter values returned by tool calls must strictly correspond to actual production nodes, otherwise they may mislead users' production judgments.
How to set configurations
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
toolChoice | Force specify the smelting data query function | Ensure the model only calls the target tool, avoiding selection of unrelated functions |
functionCall | Enable active calling mode | Allow the model to automatically trigger plugins to obtain real-time data based on user consultations |
| Trigger timing | Within 10 seconds after production work order creation | Match the startup node of the smelting production process, avoiding delayed calls |
| Calling interval | 300 seconds | Adapt to the minute-level update rhythm of real-time data, balancing timeliness and calling frequency |
| Parameter matching rule | Only return process fields associated with the current work order | Match the field structure of structured data, reducing interference from irrelevant information |
| Result verification threshold | Deviation not exceeding the measured calibration range | Adapt to the strict precision requirements of smelting parameters, ensuring data availability |
Three common configuration mistakes
- The first common mistake: The plugin returns an empty result, and logs show that the parameter fields for the target process were not matched. The cause is that no specific data source node was specified during configuration, causing the plugin to pull full data and fail to filter valid information.
- The second common mistake: A parameter format error is returned during calls, with a status code of 400. The cause is that parameters were not passed according to the field structure of smelting data, confusing the parameter naming rules of different processes.
- The third common mistake: The model does not trigger tool calls and directly generates a response. The cause is that the
functionCallconfiguration was not enabled, preventing the model from actively calling plugins to obtain real-time production data.
How to confirm the configuration is complete
- Manually trigger plugin calls, and check whether returned parameters match the process parameters of the current test work order.
- Check calling logs to confirm that trigger timing meets the configured time requirements.
- Verify the parameter matching rule, confirming that returned results only include specified fields for the target process.
- Adjust test parameter values, confirming that the result verification threshold correctly intercepts abnormal data exceeding reasonable ranges.
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.