What this category of data looks like
The data sources for iron and steel smelting cover full-process real-time monitoring systems, material ledger databases, process specification documents, and quality inspection reports. Real-time data comes from online sensors of blast furnaces and converters, with updates every second. Unstructured data includes process cards and PDF operation specifications for each process step. Structured data includes fields such as steel grade, furnace temperature, and smelting duration. Their respective units are none, ℃, and minutes. Data is stored classified by processes like ironmaking, steelmaking, and rolling. Each structured document contains all parameter items for the current process.
What constraints these characteristics impose on tool calling and plugins
The second-level update of real-time sensor data requires that tool calling response delays stay within a reasonable range. Otherwise, the latest parameters for the current process cannot be returned. The fixed format of structured fields requires tool call return results to strictly match field names and units. Otherwise, subsequent processes cannot parse the results. Unstructured process documents need plugins to support PDF text extraction and keyword matching. This provides accurate process basis for the model. Parameter thresholds vary widely across different process steps. Tool calling must combine current process rules to filter invalid data. This prevents returning results that do not meet process requirements.
How to configure the settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Tool call trigger threshold | Calibrate based on the current process parameter deviation range | Match the field verification rules of iron and steel smelting data |
| Maximum duration of single tool call | 60 seconds | Adapt to the refresh rhythm of real-time smelting data |
toolChoice | auto | Allow the model to independently select tools matching the smelting process |
functionCall | Enabled | Force structured output to match the field format of smelting data |
| Tool result cache duration | 10 minutes | Balance real-time performance and call frequency |
| Number of tool result items returned per single call | Top 3 | Avoid overload and cover core process parameters |
Three common configuration mistakes
- Phenomenon: The model does not trigger the specified smelting data query when calling tools, and directly generates a generic response. Cause: The
toolChoiceparameter is not configured correctly, and the model is not forced to call tools. - Phenomenon: Tool call return results have a disorganized format and cannot be parsed into process step parameters. Cause: The
functionCallconfiguration is not enabled, and the model does not return tool call results in a structured format. - Phenomenon: MCP service call times out, and real-time furnace temperature data cannot be obtained. Cause: A reasonable maximum single tool call duration is not set, so the request fails to complete the response within the allowed range.
How to confirm correct configuration
- Send a request that includes a query for specific process step parameters. Verify whether the tool call is triggered and returns results with corresponding fields.
- View the tool call log to confirm that the
toolChoiceandfunctionCallparameters have taken effect as configured. - Simulate a parameter query that exceeds the process threshold. Check whether the tool returns prompts that comply with the rules.
- Test the MCP service connection in the FastGPT v4.17.0 environment. Confirm that the request can complete the response within the configured timeout duration.
The values provided here are common starting points. They should be evaluated 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.