What this category of data looks like
Typical entities are regulatory departments including market supervision, housing and urban-rural development, and ecological environment. Daily documents cover random inspection plans, inspection object lists, inspection item lists, on-site inspection records, rectification notices, and random inspection result announcements. Data sources are the "Double Random, One Public" regulatory platform, enterprise credit information disclosure system, industry regulatory systems, and law enforcement officer directory. Update frequency is typically monthly. Document fields include inspection batch number, unified social credit code, law enforcement officer number, inspection item entries, rectification requirements, and more. The structure varies significantly across document types. For example, random inspection plans focus on planning dimensions, while on-site records focus on details of individual law enforcement actions.
What constraints these characteristics impose on the source citation and traceability link
Dispersed multi-source data requires the traceability link to associate multiple knowledge bases, to ensure coverage of full-process regulatory documents. The monthly update rhythm requires the knowledge base synchronization cycle to match the update frequency, to avoid citing expired random inspection plans or rectification notices. Documents with different structures need to adapt to different retrieval logic, to ensure core fields such as inspection objects and law enforcement information are accurately recalled. The compliance attribute of regulatory law enforcement requires traceability to clearly mark document sources and generation times. Failure to do so will risk regulatory traceability failure. It is also necessary to avoid citing irrelevant data, which may cause repeated disturbances to enterprises or non-compliant extraction issues.
How to set configurations
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Similarity Threshold | 0.75–0.85 | Must accurately match core fields such as inspection object names and law enforcement officer numbers, to avoid mixing irrelevant regulatory data into Q&A content |
| Single Search Limit | Top 8 entries | "Double Random" regulatory data entries are well-structured. Excessive results will exceed context length, affecting traceability accuracy |
| Reranking | Enabled | Regulatory documents have clear structures. Reranking can improve the recall priority of highly relevant fragments, adapting to the precise citation of policy basis required for party building learning Q&A |
quoteMaxToken | 1200–1500 token | Matches the effective content length of a single regulatory document such as on-site inspection records, to ensure cited fragments are complete and not truncated |
responseData | Enable source field display | Meets compliance traceability requirements for regulatory law enforcement. Answers must include identifiers such as document type and source platform |
detail | Enable full traceability | Party building learning Q&A requires clear specification of specific document generation times, inspection batches, and other information for cited content, to improve traceability rigor |
Three Common Incorrect Configurations
- Enabling reranking results in empty citations. This manifests as zero results returned by knowledge base search, with no available fragments in the traceability link. The cause is an overly high reranking threshold, which filters out compliant but low-relevance regulatory data fragments that originally met requirements.
- Failing to set
quoteMaxTokento match document length. This manifests as cited fragments being truncated, making it impossible to fully display inspection items or rectification requirements. The cause is that the parameter value does not match the actual content scale of regulatory documents. - Failing to enable the
responseDataconfiguration. This manifests as answers not including document source identifiers, which cannot meet compliance requirements for regulatory traceability. The cause is that relevant settings for returning source data are not enabled.
How to Confirm Configurations Are Correct
- Access the knowledge base configuration page of FastGPT v4.17.0, and check whether the settings for similarity threshold, single search limit, and reranking switch match the preset values.
- Launch a test question related to party building learning, and check whether the answer includes identifiers such as source platform and document type of the corresponding regulatory document, to confirm that the
responseDataconfiguration is active. - After adjusting the
quoteMaxTokenparameter, verify that cited fragments are fully displayed without forced truncation. - Compare the number of recalled fragments before and after enabling reranking, to confirm that the reranking function operates normally and does not abnormally filter valid data.
The values listed above are common starting points. They should be evaluated against the user’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.