What this category’s data looks like
Data for inspection and process record audits in pulp and paper scenarios comes from wood pulp and waste paper batches, DCS/QCS systems, on-paper machine measurement equipment, laboratory testing, and energy and water treatment systems. Data update frequencies fall into three types: real-time, shift-based, and per-roll. These correspond to real-time paper machine operating parameters, shift production records, and single-roll finished product quality inspection data, respectively. Daily documents include pulp preparation sheets, beating records, paper machine operation logs, online quality curves, laboratory test reports, and sheet break and product change records. Fields include pulp ratio, beating degree, grammage, moisture, thickness, and more. Units include g/㎡, %, mm, and more. This scenario involves high-speed continuous web production, with data linked to cross-longitudinal quality distribution and sheet break risk.
Constraints imposed by these characteristics on tool calling and plugins
Multi-source heterogeneous data sources require tool calling plugins to support API interface integration with different systems, and adapt to the differentiated update frequencies of real-time, shift-based, and per-roll data. Diverse document structures and field characteristics require plugins to parse production records in different formats, and accurately match dedicated fields such as pulp ratio and grammage. The high-speed continuous production feature requires tool calling response speeds to meet real-time monitoring needs, avoiding delays that cause production deviations. Single-roll data association requires tool calling to pull associated records in batches, avoiding fragmented queries that reduce audit efficiency.
Configuration settings
This configuration is based on FastGPT v4.17.0. Specific parameters are as follows:
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Single tool call limit | First 3 entries | Adapt to the need to pull complete inspection data for a single roll of paper |
| Tool call timeout | 30–60 seconds | Match real-time and shift-based production data update cycles |
| Result reranking threshold | 0.75–0.85 | Ensure relevant matching for online quality curves and laboratory reports |
| Question optimization switch | Enabled | Simplify query logic for pulp preparation parameters and paper machine operating status |
| Workflow/API tool selection | auto | Adapt to tool calling scenarios for multiple data sources |
| Workflow/API function-call configuration | strict | Ensure parameter matching meets the dedicated field format for pulp and paper production |
Three common configuration mistakes
- Phenomenon: Tool calling returns abnormal content in
Human <Instruction>format. Cause: Strict mode forfunctionCallis not enabled, causing the large model to generate instructions that do not meet format requirements. - Phenomenon: Calling quality data tools returns an insufficient number of results. Cause: The single tool call limit is set too low, failing to cover complete inspection data for a single roll of paper.
- Phenomenon: A specific MCP service call returns a parsing failure. Cause: Service address and permission parameters are not configured for dedicated data sources in the pulp and paper scenario.
How to confirm correct configuration
- Submit a pulp preparation sheet query request, check that the fields returned by tool calling include core production parameters such as pulp ratio and beating degree.
- Simulate a real-time paper machine operating data pull, confirm that tool calling returns complete results within 30–60 seconds.
- Test parameter passing in
functionCallmode, check that generated calling instructions comply with the dedicated field format for pulp and paper production. - Adjust
toolChoiceto auto, verify that automatic switching between multiple data sources operates normally.
The values listed above are common starting points. Adjust them based on your own specific samples and operational requirements.