Data Profile for This Category
Data for this category originates from hot metal and scrap steel ledgers, L2 process control systems, laboratory composition reports, MES production management systems, energy medium monitoring platforms, and equipment status monitoring platforms. Daily generated documents include heat plans, batching lists, converter smelting records, molten steel composition reports, continuous casting process parameter records, and slab quality judgment sheets. Data update frequencies include per heat, real-time, and shift cycles. Fields include heat number, hot metal ratio, composition content, temperature parameters, cast sequence timing, and more. Units include tons, degrees Celsius, percentage, and minutes, among others.
Constraints on Tool Calling and Plugin Workflows
The data characteristics of this category impose multiple constraints on tool calling and plugin workflows. Multi-source heterogeneous data sources and differentiated update frequencies require plugins to support integration with multiple system interfaces. This enables accurate synchronization of real-time, per-heat, and shift-based data. The strong coupling between heats and cast sequences requires tool calling to strictly bind the corresponding heat number. This prevents cross-heat data misuse. The high-temperature continuous production environment with no downtime requires tool calling to have low-latency response capabilities. This avoids production process interruptions caused by waiting timeouts. The large number of closely related professional fields requires plugins to accurately match key fields such as heat number, composition thresholds, and cast sequence timing. This prevents production abnormalities caused by data misalignment.
Configuration Setup
This document is written based on FastGPT v4.17.0. Specific configuration items and their supporting rationale are listed below:
| Configuration Item | Recommended Approach | Rationale |
|---|---|---|
| Plugin trigger timing | Triggered immediately after heat plan generation | Matches the strong coupling between heats and cast sequences, ensuring accurate data association |
| Workflow/API tool selection | Force specify the target plugin | Prevents the model from selecting irrelevant tools, adapting to the fixed workflow requirements of bid quotation preparation |
| Maximum call wait time | 30–60 seconds | Aligns with production rhythm, avoiding delays that disrupt subsequent process arrangements |
| Plugin input field validation | Enable required field validation | Prevents missing key information such as heat number and composition data |
| Workflow/API function-call configuration | Enable strict parameter validation mode | Ensures that parameter formats received by plugins comply with field specifications for production documents |
| Single call return data limit | Top 10 heat records | Avoids data overload that reduces quotation calculation efficiency |
Three Common Misconfigurations
- Symptom: A custom Python plugin fails to operate normally after configuration, with logs indicating the target executable file cannot be found. Cause: The local path of the Python script is not correctly specified in the plugin configuration, and the file storage location does not match the production environment.
- Symptom: Calling a tool interface returns empty results, and converter smelting record data cannot be retrieved. Cause: The corresponding heat number is not bound as a call parameter, causing the plugin to fail to match the correct production data.
- Symptom: The initial call works normally, but subsequent calls with multi-turn context trigger timeout errors. Cause: The number of data items returned per call is not limited, leading to context overload that exceeds the response threshold.
How to Verify Successful Configuration
- Manually trigger plugin calls, enter a known heat number, and verify that returned data includes fields such as hot metal ratio and composition report for the corresponding heat.
- Review plugin logs to confirm that each call correctly connects to the specified production system interface, with no parameter transfer errors.
- Simulate multi-turn context calls, and verify that response delays fall within the allowable range for production processes.
- Trigger input of abnormal parameters, and confirm that the plugin returns clear error prompts in accordance with the configured validation rules.
The values provided here are common starting points, and should be evaluated against local deployment samples.