What the data for this category looks like
Mining and mineral processing data primarily comes from mine MES systems, mineral processing workshop PLC collection terminals, safety inspection systems, and administrative business approval workflows. Structured data includes fields such as equipment ID, raw ore processing volume, operating duration, with units of tons and hours. Unstructured data includes inspection logs, approval documents, and similar content, mostly in PDF or structured form formats. Real-time production data updates every second. Daily production ledgers are summarized and updated each early morning. Monthly business reports are archived and updated before the 5th of each month.
What constraints do these characteristics impose on model access and configuration
The multi-source data characteristics of mining and mineral processing impose multiple constraints on model access and configuration. The high-frequency updates of real-time production data require that the model's context recall range be limited to the last 24 hours, to avoid loading expired data and affecting the accuracy of process guidance. Differences in structured data fields and units require that field mapping rules for recalled data be clearly specified during configuration, to prevent confusion between processing volume and operating duration parameters of different equipment. The diverse formats of unstructured inspection logs and approval documents require that chunking configurations adapt to the length ranges of different documents, to avoid loss of process node information due to long text truncation. The multi-link nature of business handling processes requires that the model's context window cover complete process node descriptions.
How to set the configuration
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
maxContext | 8000–12000 token | Covers complete mining and mineral processing business process node descriptions and real-time production data from the last 24 hours |
maxTokens | 4000 token | Adapts to the reply length of a single business process guidance, avoiding exceeding model output limits |
quoteMaxToken | 2000 token | Limits the total length of recalled reference data, preventing redundant data from occupying too much context space |
temperature | 0.2–0.4 | Reduces reply randomness, ensuring steps for business process guidance are accurate and consistent |
AIPROXY_API_ENDPOINT | Fill in the intranet proxy address according to the deployment environment | Adapts to access restrictions of the mining intranet, ensuring data transmission security |
AIPROXY_API_TOKEN | Generate an exclusive token according to intranet permissions | Restricts only authorized business systems to call model interfaces, preventing unauthorized access |
Three common configuration errors
- When bulk uploading mineral processing inspection logs, only the first dozen entries can complete process matching normally, while subsequent entries return empty results. This occurs because the
maxContextparameter is not adjusted to fit the total length of the batch documents, causing subsequent documents to exceed the context limit and be truncated. - When calling the model interface, a 403 status code is returned, and business process guidance content cannot be generated. This occurs because the
AIPROXY_API_TOKENis not configured correctly, or the token permissions do not cover the access scope of the mining intranet. - The process guidance steps generated by the model do not match the actual mineral processing flow, with parameter unit mismatches. This occurs because field mapping rules are not clearly configured, leading to incorrect association of processing volume and operating duration parameters from different equipment.
How to confirm the configuration is correct
- Call the model interface, pass a single mineral processing business approval document, and check whether the returned process guidance steps include all required nodes for approval.
- Upload a single unstructured inspection log, and confirm that the recalled reference data includes key equipment operating information from the log.
- View the interface call log, and confirm that there are call records for
AIPROXY_API_TOKENand no permission error messages. - Adjust the
temperatureparameter, call the interface for the same business scenario multiple times, and check whether the returned process steps have no obvious deviations.
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.