What this category of data looks like
Data for engineering consulting supervision policy and regulatory basis Q&A comes primarily from engineering supervision regulations, bidding supervision measures, industry standard specifications released by the Ministry of Housing and Urban-Rural Development and provincial and municipal housing and urban-rural development authorities, plus supervision duty implementation rules issued by local governments. Data updates are released irregularly alongside industry policy adjustments. National standard documents are revised every 3 to 5 years. Most documents are structured text with document numbers, effective dates, applicable scopes and specific clauses. Fields include supervision scope, compliance requirements, duty time limits and more. Units covered include building area, contract amount and supervision cycle.
What constraints these characteristics impose on knowledge base retrieval and recall
Engineering consulting supervision policy data consists mostly of structured clauses released at different hierarchical levels. Retrieval must balance semantic matching and precise field matching. It must also support filtering recall results by effective date and applicable scope. Data updates follow no fixed cycle, so fast incremental synchronization for knowledge base updates must be supported. Documents contain long clause content. Text chunk cutting length must be controlled reasonably to avoid semantic fragmentation. Supervision policies vary across regions. Retrieval scope must be limited by geographic dimension to ensure results fit specific business scenarios.
How to set the configuration
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
similarity | 0.75–0.85 | Engineering supervision policy clauses are rigorous. This threshold filters low-match results to avoid confusing similar regulations with different document numbers |
limit | Top 6–8 results | Single policy clause content is lengthy. Too many recall results will exceed context window limits |
searchMode | Semantic retrieval | Policy texts are mostly structured clauses. Semantic retrieval matches keywords and contextually related content, and performs better than pure keyword matching |
usingReRank | Enabled | Recall results must be reordered by relevance to ensure core policy clauses are displayed first, meeting the priority needs of supervision business |
datasetSearchUsingExtensionQuery | Enabled | Policies for engineering consulting supervision often use synonymous expressions. Enabling this optimizes query terms to improve recall coverage |
collectionIds | Bind the corresponding supervision policy knowledge base collection | Limit retrieval scope to the exclusive dataset to avoid mixing policy content from other categories, ensuring result accuracy |
Three common misconfigurations
- Phenomenon: AI-generated policy clauses deviate from the original text stored in the knowledge base, and may even reference regulations with incorrect document numbers. Cause: The
similaritythreshold is not configured, or the threshold is set too low, which recalls low-match non-target policy documents. - Phenomenon: Empty results are returned after calling a knowledge base query, and the application and knowledge base belong to different teams. Cause: The
collectionIdsbinding for the target knowledge base collection is not configured, or cross-team access permissions are not granted, so the retrieval scope covers irrelevant datasets. - Phenomenon: Long policy documents are split with semantic breaks, leading to missing core context in retrieval results. Cause: Text chunk cutting configuration is not adjusted based on policy clause length, splitting continuous compliance requirement clauses.
How to confirm the configuration is correct
- Manually import a test supervision policy clause, enter a query containing keywords from that clause, and verify that the recall results include the target document.
- Adjust the
similarityparameter, observe changes in recall result matching accuracy, and confirm the threshold meets business precision requirements. - Switch
searchModeto different modes, compare the coverage of recall results, and confirm the retrieval method adapted to policy texts is selected. - Check the knowledge base synchronization logs to confirm that new policy documents can be normally incrementally synchronized to the retrieval scope.
The values listed here are common starting points. They should be evaluated against samples relevant to the specific deployment scenario.
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.