What the data for this category looks like
This category of data primarily comes from data asset inventories, database metadata, business system descriptions, and regulatory documents. The update frequency is triggered quarterly or when the system changes. Daily produced documents include data catalogs, classification and grading rules, important data identification tables, and review minutes. Most document structures follow field classification and hierarchical grading, with fields such as asset name, sensitivity level, belonging system, and compliance requirements. There is no unified single-data length standard.
What constraints do these characteristics impose on the reranking and hybrid retrieval link
Decentralized data sources lead to large differences in the relevance of initial search results. Metadata formats from different sources are inconsistent, so reranking is needed to correct the search ranking logic. The update frequency is low but a single change has a wide impact scope, so it is necessary to ensure that search results cover the latest classification and grading rules. Documents contain hierarchical grading information. During hybrid retrieval, priority must be given to matching fields with high sensitivity levels to avoid low-priority results interfering with core requirements. At the same time, search results for compliance documents must strictly match the original regulatory text, and the reranking link must retain the association with the compliance basis from the original search.
How to set the configurations
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
usingReRank | Enabled | This category of documents contains hierarchical grading information. Reranking is required to correct the relevance ranking of initial searches and prioritize matching content with high sensitivity levels |
similarity | 0.65–0.75 | Balance precise matching of compliance documents and associated recall of business system metadata, adapting to differences in metadata formats from decentralized sources |
limit | Top 10 entries | Cover the search needs of multiple document types such as data catalogs and classification rules, avoiding excessive low-correlation results interfering with the review process |
searchMode | hybrid | Combine vector retrieval and keyword retrieval, adapting to the characteristics of mixed data sources of metadata and regulatory text |
Three common mistakes
- Issue: After deploying the bge-rerank-base image and connecting it, a 401 unauthorized error is returned, while configurations on other platforms work normally. Cause: The FastGPT configuration does not correctly fill in the API key for the private reranking model, or the current deployment node IP is not added to the access whitelist.
- Issue: When reranking is not enabled, the relevance field of search results has no clear reference value and cannot be used to filter low-quality results. Cause: The reranking link is not enabled. Initial retrieval is only based on vector similarity, and sorting is not corrected based on semantic relevance. The relevance value only reflects vector space distance and cannot directly reflect business matching degree.
- Issue: In FastGPT v4.9, when configuring a private reranking model, there is no corresponding setting entry in the interface, causing deployment failure. Cause: The reranking model configuration logic in v4.9 differs from later versions, and parameter items for directly connecting to private images are not exposed.
How to confirm the configuration is complete
- Confirm that the currently used FastGPT version is v4.17.0 or higher, which supports complete reranking and hybrid retrieval configuration items.
- Enter the FastGPT reranking model test page, input sample text of classification and grading rules, and verify whether the returned results are sorted to prioritize matching content with high sensitivity levels.
- Check the retrieval log to confirm that the
usingReRankparameter is enabled and thesimilaritythreshold is configured according to business requirements. - Test the hybrid retrieval mode to verify that both metadata and regulatory text documents are recalled.
- Simulate a pre-sales Q&A scenario, input questions related to data asset sorting, and confirm that the returned results include target documents such as data catalogs and review minutes.
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 2026-10-19.