Reference only; verify against the target FastGPT release and deployment documentation.
What This Category of Data Looks Like
Data for this category primarily comes from health supervision information systems, medical institution electronic registration systems, complaint reporting platforms, and law enforcement inspection records. The data update frequency is monthly. Core documents include supervision inspection forms, medical institution practice licenses, rectification notices, supervision opinions, and penalty case files. Document fields cover institution unified social credit codes, inspection dates, inspection item details, rectification requirements, penalty document numbers, and more. There is no unified fixed unit, and the unit adjusts based on the document type. Some documents include associated on-site captured image information.
What Constraints Do These Data Characteristics Impose on the Knowledge Base Retrieval and Recall Process
These data characteristics impose multiple constraints on the knowledge base retrieval and recall process. Scattered data sources with large format differences require the retrieval link to support unified field recognition and mapping for multi-source heterogeneous documents. The monthly update frequency does not require high-frequency incremental synchronization, but requires configuration of stable full update trigger rules. Core documents are government compliance documents, requiring high keyword accuracy to avoid irrelevant content recall. Some documents are associated with the same medical institution’s qualifications and law enforcement records, so retrieval must support grouping recall by unified social credit code to ensure relevance for ledger summary.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
similarity | 0.72–0.85 | Matches the keyword matching accuracy required for government compliance documents, avoiding recall of irrelevant non-compliance documents |
limit | Top 10 entries | Balances information completeness of ledger summary and context length, adapting to multi-document association requirements |
searchMode | vector | Prioritizes matching semantically related law enforcement records and institution qualification documents, ensuring retrieval relevance |
usingReRank | Enabled, rerank top 5 entries | Improves sorting priority of highly relevant documents, optimizes recall order of rectification notices and penalty case files |
datasetSearchUsingExtensionQuery | Enabled | Automatically expands retrieval keywords, covering common synonyms used in government scenarios such as "practice license" and "rectification requirements" |
collectionIds | Bind the exclusive medical institution supervision dataset ID for this category | Limits retrieval scope to the category-specific knowledge base, avoiding interference from cross-category documents |
Three Common Mistakes
- Symptom: Retrieval results do not prioritize returning supervision inspection form documents with specified file names. Cause: Failed to use file names as retrieval matching fields, or failed to configure metadata-based recall rules.
- Symptom: When calling the chatbot via API, the answer does not reference content from compliance documents in the knowledge base. Cause: Failed to bind the corresponding dataset ID in the request parameters, or failed to enable knowledge base retrieval mode.
- Symptom: Unable to adjust the index weight of retrieval results directly via the retrieval test interface. Cause: Mistook the edit button in the retrieval test interface as the index adjustment entry. The actual entry is located in the content management page of the corresponding knowledge base to adjust metadata weights.
How to Confirm the Configuration Is Complete
- View the knowledge base dataset management page, confirm that
collectionIdsis configured with the exclusive medical institution supervision dataset ID for this category. - Initiate a simulated retrieval, enter a query containing institution qualification or law enforcement keywords, verify the relevance of retrieval results, and adjust the
similaritythreshold to meet the accuracy required for business needs. - Call the API interface, pass the corresponding dataset ID and valid query terms, and confirm that the returned results include supervision opinions or rectification notice content from the knowledge base.
- After enabling
usingReRank, check that highly relevant rectification notice documents appear in higher sorted positions after reranking.
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.