What the data for this category looks like
Data for this category typically comes from elderly care service information platforms, civil affairs statistics systems, fire safety inspection records, and institution operation ledgers. It also includes party building supervision-related policies and learning materials. Daily documents cover filing materials, operation subsidy applications, service quality inspection forms, safety hazard rectification ledgers, and elderly admission files. The data includes both structured fields such as institution filing number and number of beds, and unstructured content such as inspection records, rectification reports, and party building study notes. The data update rhythm is usually monthly. Document structures vary significantly across business processes. Fields include institution identifiers, service data, rectification status, and units such as beds, amount, and duration.
What constraints these characteristics impose on knowledge base retrieval and recall
Data sources for this category are scattered. Cross-system integration requires aligning field formats such as institution filing number and number of beds, which raises requirements for retrieval field matching accuracy. The low-frequency monthly update rhythm means high-frequency synchronization is unnecessary, but retrieval results must cover the latest filing, rectification, and subsidy information. They must also include party building-related policy materials. There are diverse document types, including structured forms and unstructured reports. This requires retrieval to support content recall across different formats. The accuracy of supervision data is directly linked to subsidy distribution and safety control. Low-relevance results must be filtered to avoid incorrect recall that harms the accuracy of party building learning and supervision work.
How to set the configuration
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
similarity | 0.72–0.78 | This category contains a large number of identical-type supervision fields. Low-relevance results must be filtered to prevent incorrect recall of subsidy and rectification information. |
limit | Top 6 entries | The number of single-round retrieval results should not be excessive. This fits the lightweight Q&A scenario of party building learning Q&A, and covers multiple types of business and party building documents. |
searchMode | Hybrid retrieval | Balances structured field matching and unstructured content recall. It supports diverse document types such as filing materials, inspection records, and party building policies. |
usingReRank | Enabled | For multi-source scattered supervision and party building data, re-ranking improves the sorting priority of highly relevant results. This ensures retrieval accuracy. |
datasetSearchUsingExtensionQuery | Enabled | Combines common questions from party building learning to automatically expand retrieval keywords. It covers associated content of party building policies and supervision requirements. |
collectionIds | Bind three types of knowledge base collections: institution filing, supervision inspection, and party building learning | Accurately limit the retrieval scope to avoid irrelevant business data being included in retrieval results. |
Three common mistakes
- Uploading PPT or PDF documents fails to sync to the knowledge base. The symptom is that the document shows unparsed or sync failed after upload. The cause is that the parsing adaptation for the corresponding document format is not enabled, or the data source permissions bound to the knowledge base do not cover unstructured document types.
- Single-file upload takes too long and then a network failure occurs. The symptom is that the upload progress stalls and a network error prompt pops up. The cause is that a reasonable upload timeout threshold is not configured, or the document size exceeds the platform's single upload limit.
- The image understanding model option is missing when deploying an older version locally. The symptom is that there is no selection entry for the image understanding model on the new knowledge base page. The cause is that this version does not pre-install or enable the image understanding extension plugin, and the corresponding package must be installed manually.
How to confirm the configuration is complete
- Upload 1 elderly care institution filing material and 1 party building supervision policy document. Perform a retrieval test, and confirm that the returned results include relevant content from both types of documents.
- Adjust the
similarityconfiguration range. Verify that low-similarity results are filtered, and ensure that the relevance of retrieval results meets business requirements. - Enable metadata output for retrieval results. Check whether the returned content includes fields such as the document's institution identifier and update time, and confirm that data association is accurate.
- Test the upload and retrieval of multi-format documents such as DOCX, PDF, and spreadsheet files. Confirm that all configured document types can be recalled normally.
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.