What the data for this category looks like
Data sources for this category include health supervision information systems, medical institution electronic registration systems, complaint reporting platforms, and law enforcement inspection records. Update frequency is monthly. Commonly processed documents cover supervision inspection forms, medical institution practice licenses, rectification notices, supervision opinions, and penalty case files. Structured documents include fixed fields such as institution name, practice scope, and license validity period. Unstructured documents include free text content such as on-site inspection details and rectification requirements. Fields and units follow unified standards from the health commission system.
What constraints these characteristics impose on the knowledge base retrieval and recall link
Monthly data updates require the retrieval link to adapt to non-real-time data synchronization. Avoid frequent full index rebuilds to reduce system overhead. Mixed recall of multiple document types requires balancing structured field matching and unstructured text understanding. Core fields such as institution qualification numbers and rectification items should be high-priority matching terms. Retrieval result accuracy directly relates to law enforcement compliance. Strictly filter irrelevant documents to prevent errors in law enforcement documents caused by retrieval bias. Single retrieval response time should not exceed 10 seconds. This avoids impacting on-site law enforcement document generation efficiency.
Configuration settings
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Setting | Basis |
|---|---|---|
similarity | 0.75–0.85 | Match core keywords such as qualifications and rectification items in health supervision documents, and filter low-relevance general medical documents |
limit | Top 8 entries | Cover the core context length of a single supervision document, and avoid exceeding model input limits |
searchMode | vector + keyword | Balance structured field matching (such as practice license numbers) and keyword matching for unstructured inspection records |
usingReRank | Enabled | Perform secondary sorting on recall results to optimize matching accuracy for professional terms such as hospital infection disinfection and diagnosis and treatment behaviors |
datasetSearchUsingExtensionQuery | Enabled | Automatically expand business terms such as "rectification notice" and "practice qualification" to match synonymous expressions |
collectionIds | Bind dedicated health supervision dataset | Isolate document data from other categories to avoid recalling irrelevant content |
Three common configuration errors
- First submission of a retrieval request containing "rectification notice" returns no matches. Subsequent repeated submissions return correct documents. The cause is that the first retrieval does not trigger
datasetSearchUsingExtensionQuery, and automatic business term expansion is not performed, leading to matching failure. - Manually uploaded supervision inspection document indexes disappear after several hours. The cause is that persistent storage configuration for the dataset is not enabled. Monthly synchronization tasks overwrite temporarily created indexes.
- Retrieval results include practice license information for non-target institutions. The cause is that
collectionIdsis not configured correctly, and documents from other datasets are recalled.
How to confirm correct configuration
- Retrieve the practice license number of a specified medical institution. Verify that returned results include complete fields of the corresponding document and associated law enforcement records.
- Submit a retrieval request containing "hospital infection disinfection" and "diagnosis and treatment behavior norms". Check that sorted results prioritize professional business content.
- View the bound
collectionIdsparameter for the dataset. Confirm that only dataset IDs for health supervision documents are included. - Submit the same retrieval request twice. Verify that the number and content of returned results are consistent across both attempts, with no omissions or deviations.
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 2026-09-28.