What This Category of Data Looks Like
The daily documents for this category include batching lists, smelting records, electrolytic cell condition records, laboratory reports, anode and cathode quality records, and environmental protection ledgers. Data sources include concentrate and auxiliary material analysis reports, DCS systems, cell voltage and current monitoring data, laboratory test results, and energy and environmental monitoring equipment. Data update frequency is adjusted according to production rhythm. This includes immediate updates for each batch of raw materials, each furnace, or each cell, as well as real-time operating condition monitoring data. Documents contain professional fields such as concentrate grade, cell voltage, current value, impurity content, and emission indicators, with units matching the corresponding parameters.
Constraints Imposed on Knowledge Base Retrieval and Recall by These Characteristics
Multi-source heterogeneous data sources require retrieval to cover multiple formats including structured forms, real-time logs, and ledger reports. It also requires adaptation to the structural features of different documents. Frequently updated production data requires the knowledge base to support incremental synchronization, to avoid recalling outdated process records. Professional process fields and terms require precise matching. Dual capabilities of keyword and vector retrieval must be considered to prevent recalling irrelevant general content. The volume of associated data for a single batch or single cell is limited. The number of retrieval results must be controlled to avoid context overload that affects drafting efficiency.
How to Configure the Settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
similarity | 0.72–0.85 | Confidence interval for matching non-ferrous metal smelting professional terms, filters irrelevant general process content |
limit | Top 6 entries | Covers the number of associated records for a single furnace or single cell, avoids context exceeding processing limits |
usingReRank | Enabled | Re-ranks retrieval results by abnormal relevance, prioritizes core process content such as cell conditions and smelting parameters |
datasetSearchUsingExtensionQuery | Enabled | Expands professional query terms based on batching lists and laboratory reports, for example, expanding "molten aluminum impurities" to "excessive iron content in molten aluminum" |
searchMode | mixedRecall | Balances professional term matching and precise recall of structured fields |
collectionIds | Calibrated through actual testing | Binds process document collections corresponding to the smelting workshop, avoids interference from cross-workshop data |
Three Common Configuration Mistakes
- Retrieval results do not include English professional documents stored in the knowledge base. This occurs when cross-language query expansion is not enabled, or English documents are not included in the bound document collection.
- Independent electrolytic cell condition records are merged during chunking, or complete batching list paragraphs are split. This occurs when custom separators do not adapt to the line break format of smelting documents, and chunking rules are not adjusted based on process paragraph logic.
- The number of retrieval return results is far lower than the set limit. This occurs when the
similaritythreshold is set too high, filtering out weakly relevant valid records that fit the abnormal report scenario.
How to Verify Correct Configuration
- In the FastGPT v4.17.0 environment, upload a smelting document containing English professional terms. Initiate a query of the "electrolytic cell voltage abnormality handling" type, and confirm the result includes the uploaded document content.
- Manually split an electrolytic cell condition record, set the corresponding line break separator, and check if the chunking result retains independent single-cell operating condition paragraphs.
- Initiate a query related to abnormal report drafting, and check if the sorted return results prioritize core process content such as cell voltage abnormalities and excessive impurity levels.
- Check if the bound document collection includes target data sources such as batching lists and laboratory reports from the current workshop.
The values provided are common starting points and should be measured against the reader's own samples.