Reference only; verify against the target FastGPT release and deployment documentation.
What this category of data looks like
Mining and mineral processing data primarily comes from mine production ledgers, geological exploration archives, real-time collected data from mineral processing flows, safety inspection records, and equipment operation and maintenance logs. Data update rhythms fall into two categories: production and inspection data is synchronized daily or in real time, while geological and design archives are updated quarterly. The document structure uses the unique mine identifier as the core associated field, including mining area coordinates, mineral processing equipment model, processing capacity, energy consumption parameters, inspection batch number, and more. Field units uniformly adopt international standard measurement units such as meters, tons per hour, hours, etc.
What constraints these characteristics impose on the tool calling and plugins workflow
Because the data includes real-time collected equipment operating parameters and daily updated production ledgers, tool calling needs to support pulling the latest data on demand to avoid returning outdated information. Field differences across multiple data sources require unified field mapping rules during tool calling, for example, unifying runtime duration fields from different inspection systems into standard names. The quarterly update characteristic of geological archives requires plugins to periodically synchronize archive snapshots to avoid calling stale exploration data. At the same time, multi-field associated queries must support combined condition filtering, for example, filtering data by both mining area and equipment model.
How to set configurations
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Tool call timeout | 30–60 seconds | Mining and mineral processing data is mostly stored in distributed systems, so sufficient response time must be reserved for pulling batch data |
| Number of data entries recalled per request | Top 10 entries | Single-batch data volume for mining and mineral processing is large, and too many entries will exceed the context window |
toolChoice | auto | The matching tool must be automatically selected based on user queries, without forcing a single function to be specified |
| Field mapping rules | Map in the standard order of mine number, equipment model, and processing capacity | Mining and mineral processing data mostly uses the mine identifier as the core associated field, and unified mapping can improve query accuracy |
| Plugin data synchronization cycle | Once daily | Production data is updated daily, so the synchronization cycle must match the data update rhythm |
Three common misconfigurations
- Symptom: Search plugin calls return empty results. Cause: No dedicated keyword filtering rules for the mining and mineral processing domain are configured, so returned general results are irrelevant to the mining scenario and cannot match user queries.
- Symptom: Missing fields in results after tool call is triggered. Cause: Correct field mapping rules are not configured, so the plugin cannot map external data to system standard fields.
- Symptom: Setting
toolChoiceto a fixed function fails to trigger the expected tool. Cause: The actual needs of the user query are not matched, and the forced specified tool cannot cover the user's query intent.
How to confirm the configuration is complete
- Enter a query that includes core identifiers of the mining scenario, and check whether the tool call process is triggered on the interface
- View the plugin operation logs to confirm that the returned data fields match the preset mapping rules
- Adjust the
toolChoiceparameter to verify whether the large model can automatically select the corresponding tool based on the query - Simulate a data pull delay scenario to confirm that the tool call timeout logic takes effect
The values provided here are common starting points, and 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.