What this category of data looks like
Data for administrative inquiries and replies in non-ferrous metal smelting mainly comes from on-site real-time production monitoring systems, batch quality inspection reports, process procedure manuals, equipment maintenance logs, and industry compliance standards. Data update frequencies cover multiple dimensions: real-time parameters such as furnace temperature and pressure are updated at the minute level, batch quality inspection data is generated alongside production batches, and process procedures and compliance standards are revised quarterly or annually. Most individual documents contain clear fields: smelting batch number, equipment ID, detection parameter values (with units including ℃, MPa, %, etc.), and process step descriptions. Some long documents need to be split while retaining complete process logic.
What constraints these characteristics impose on the knowledge base retrieval and recall link
Minute-level updates of real-time parameters require retrieval to prioritize the latest batch data and avoid returning expired historical parameters. Dispersed data from multiple sources needs cross-dataset recall, with clear binding of dataset scopes corresponding to this category. Fields include exclusive units and batch identifiers, so retrieval must retain unit information to avoid parameter matching errors, and support precise matching of identifiers such as batch numbers and equipment IDs. The process step structure of long documents requires retaining contextual association when splitting, to prevent loss of process logic after splitting. Inquiries often relate to multi-dimensional parameters such as furnace temperature corresponding to holding time, so extended associated retrieval must be supported to cover complete inquiry scenarios.
How to set the configurations
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
similarity | 0.72–0.85 | Non-ferrous metal smelting has high precision requirements for process parameters. A threshold that is too low will introduce irrelevant low-match data, while a threshold that is too high will miss valid content from different batches of the same process. Calibrated based on actual testing. |
limit | Top 8–12 entries | Retrieval for smelting needs to cover multi-dimensional data from the same batch and equipment. Too many entries will exceed the context window, while too few will lose key associated information. |
searchMode | vector + keyword | There is a need for semantic matching of process parameters, as well as precise keyword matching for identifiers such as batch numbers and equipment IDs, covering different retrieval scenarios. |
usingReRank | Enabled | The fields of smelting data have strong relevance. Reranking can filter out results that are semantically similar but do not match parameters, improving recall accuracy. |
datasetSearchUsingExtensionQuery | Enabled | Inquiries related to smelting often require extended associated parameters. Optimizing the query can expand the recall scope and cover cross-parameter associated inquiries. |
collectionIds | Bind the IDs of the three datasets: production monitoring, quality inspection reports, and process procedures | Administrative inquiries for non-ferrous metal smelting cover the entire production, quality inspection, and compliance links. Cross-dataset recall can cover complete inquiry scenarios. |
Three common mistakes
- Symptom: The number of retrieval results is much lower than expected, with only 1-2 entries returned. Cause: The
similaritythreshold is set too high, filtering out a large number of valid documents that meet semantic matching requirements. - Symptom: The retrieval results include a large number of irrelevant general industrial documents and do not match smelting-specific parameters. Cause: The exclusive
collectionIdsare not bound, recalling content from non-category-specific datasets. - Symptom: The retrieval results do not include real-time batch production data. Cause:
datasetSearchUsingExtensionQueryis not enabled, making extended retrieval for real-time fields such as batch numbers impossible.
How to verify the configuration is correct
- Perform keyword retrieval for a smelting batch number, and check whether the returned results include quality inspection data and production logs corresponding to that batch.
- Perform semantic retrieval for process parameters, and check whether the reranked results prioritize matching the smelting link parameters corresponding to the current inquiry.
- View the retrieval log to confirm that all recalled documents come from the three bound exclusive datasets, with no cross-category irrelevant content.
- Test retrieval for complex associated inquiries, and confirm that the relevance of the results meets expectations after the reranking function is enabled.
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.