What Data for This Category Looks Like
Document data for mineral mining and beneficiation is primarily sourced from geological exploration reports, mining operation plans, mineral processing flow manuals, safety compliance regulations, equipment operation and maintenance records, and mineral processing test reports. The update cadence of this data varies significantly: geological exploration reports and long-term mining plans have update cycles measured in quarters or years, equipment operation and maintenance records and on-site operation logs are updated in real time, and compliance documents are updated monthly or quarterly alongside regulatory policy adjustments. Most document structures are chaptered professional texts, containing dedicated fields such as grade, ore tonnage, mineral processing recovery rate, operation duration, and others. Units are mostly industrial standard units including grams per ton, cubic meters, hours, tons, and similar.
What Constraints These Characteristics Impose on Knowledge Base Retrieval and Recall
Dedicated fields and units require precise matching of professional terms during retrieval, to prevent irrelevant content from being included due to fuzzy matching. Long texts account for a large proportion of the dataset, with individual documents reaching tens of thousands of characters. Unreasonable chunking rules can easily truncate professional semantic units. Varied update cadences require classified handling of knowledge base synchronization: full regular synchronization for static documents, and incremental real-time synchronization for dynamic operation and maintenance documents. Compliance documents have strong timeliness; the latest version of content must be prioritized during recall to avoid referencing expired safety regulations or operation standards.
How to Set Up the Configuration
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Value Range | Rationale |
|---|---|---|
similarity | 0.75–0.85 | Mineral mining and beneficiation professional terms have high precision requirements. A value too low will introduce irrelevant mineral processing flow or equipment operation and maintenance content, while a value too high may miss relevant geological exploration data |
limit | Top 8–12 results | Individual mineral mining and beneficiation documents have lengthy content. Too many results will exceed the context window limit, while too few will fail to cover associated data across multiple processes |
usingReRank | Enabled | Professional texts contain a large number of synonymous terms. Reranking optimizes the semantic relevance of retrieval results and prevents professional content from being ranked low |
datasetSearchUsingExtensionQuery | Enabled | For dynamically incoming document drafting requirements, automatically expand professional term related words to improve recall coverage |
collectionIds | Only bind dedicated mineral mining and beneficiation document collections | Avoid mixing documents from other categories, ensuring recalled content is directly relevant to mining and mineral processing scenarios |
searchMode | Semantic matching combined with keyword matching | Mineral mining and beneficiation texts contain both professional terms and structured data. Combining both modes improves recall precision |
Three Common Configuration Mistakes
- After dynamically passing custom retrieval variables, no matching documents appear in retrieval results. The cause is that
datasetSearchUsingExtensionQueryis not enabled, and no term expansion is performed for the incoming professional drafting requirements, making association with same-category associated documents impossible. - Using default chunking rules directly to process mineral mining and beneficiation documents leads to truncation of professional fields. The symptom is that incomplete grade values or operation process descriptions appear in retrieval results. The cause is that default chunking does not adapt to the paragraph structure of professional texts and fails to retain complete professional semantic units.
- Mixing document collections from other categories when configuring
collectionIdsleads to returned reference documents including content from non-mining scenarios that do not match the current drafting requirements. The cause is that the dedicated mineral mining and beneficiation knowledge base collection is not accurately bound.
How to Verify the Configuration Is Correct
- Manually input a dedicated mineral mining and beneficiation term (such as "mineral processing recovery rate"), then review retrieval results for complete fragments of the corresponding document.
- Dynamically pass custom document drafting requirement keywords and verify returned results include dedicated documents associated with the keywords.
- Review the
collectionIdsconfiguration to confirm it only includes mineral mining and beneficiation documents, with no content from other categories. - After enabling
usingReRank, review retrieval result ranking to confirm it prioritizes relevance to professional fields.
The values provided are common starting points and should be evaluated against local sample datasets.
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.