What the data for this category looks like
The business process data for non-ferrous metal smelting mainly comes from production scheduling logs, process operation specifications, equipment operation and maintenance manuals, quality inspection reports, and administrative approval process documents. The update rhythm varies significantly: process specifications are revised annually, equipment operation and maintenance logs are updated per shift, and quality inspection reports are updated synchronously with production batches. Document structures include fields such as process steps, equipment numbers, temperature and pressure parameters, approval nodes, and required material lists. Most units are industrial standard units such as degrees Celsius, pascals, tons, and hours.
What constraints do these characteristics impose on the knowledge base retrieval and recall link
Differentiated update rhythms require the knowledge base to support batch incremental synchronization to avoid excessive resource consumption from full updates. Process parameters with precise units require the retrieval system to match field-level information; keyword-only matching cannot meet precise matching requirements. Structural splitting of long documents must retain the contextual association of approval nodes to avoid losing process logic after chunking. The presence of structured fields requires the retrieval system to prioritize associating corresponding fields, as global semantic matching has insufficient coverage.
How to set the configurations
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
similarity | 0.72–0.80 | Meets the precision requirements for matching smelting process parameters, and avoids recalling irrelevant quality inspection data or process documents from other workshops |
limit | Top 8 entries | Covers the main node documents of a single batch smelting process, avoids excessive results exceeding context limits, and improves readability |
searchMode | vector_search | Prioritizes vector matching for structured process parameters and process fields; keyword-only matching cannot meet the precise requirements for structured fields |
usingReRank | Enabled | Re-ranks recalled results by business relevance, prioritizes returning approval process documents to help quickly find handling steps |
datasetSearchUsingExtensionQuery | Enabled | Automatically expands synonyms related to business handling, such as expanding "electrolyzer" to "electrolysis process equipment" to cover more relevant documents |
collectionIds | Bound by smelting workshop classification | Limits the retrieval scope to the knowledge base collections of the corresponding workshop, reduces irrelevant data interference, and improves retrieval precision |
Three common mistakes
- Phenomenon: Retrieval results include steel smelting documents, and the
similarityscore is lower than 0.70. Cause: ThecollectionIdsconfiguration was not set to limit the retrieval collection, resulting in cross-category data being recalled. - Phenomenon: After uploading an electrolysis process specification document, approval nodes are split into two chunks, and the complete process cannot be matched. Cause: The chunk length setting is unreasonable, and the contextual association of the approval process is not retained, resulting in the
searchModebeing unable to match the complete logic. - Phenomenon: After deploying FastGPT v4.17.0 locally, there is no image indexing option when uploading process documents with electrolysis workshop flowcharts. Cause: The image indexing extension package is not installed for the local deployment, and this function must be manually configured before it can be enabled.
How to confirm the configuration is correct
- Initiate a query for "electrolysis workshop anode assembly process", check whether the matching score of the returned results falls within the 0.72–0.80 range.
- Count the number of documents returned by the retrieval, confirm that the number does not exceed 8.
- Enter "electrolyzer maintenance approval", check whether the system automatically expands the query terms to include relevant business words.
- View the re-ranked results, confirm that approval process documents are ranked in the top 3 of the vector matching results.
The values provided here 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.