Reference only; verify against the target FastGPT release and deployment documentation.
What the data for this category looks like
Daily documents for this category include patrol records, case filing approval forms, on-site photos, order of correction notices, penalty decisions, closing reports, and similar items. Data primarily comes from urban management law enforcement platforms, urban operation grid platforms, video surveillance systems, and public complaint tickets. The update frequency is daily.
Most data fields include law enforcement scenario descriptions, violation act definitions, rectification requirements, penalty basis, and similar content. Some entries are linked to on-site images and location information. The length of single documents varies widely, ranging from simple records of several hundred characters to formal penalty documents of several thousand characters.
What constraints do these characteristics impose on the knowledge base retrieval and recall link?
Daily updated law enforcement data requires the retrieval system to support incremental synchronization, to avoid excessive server resource usage from full re-scans. Mixed multi-type document structures require retrieval models to support associated recall of text and non-text fields, prioritizing matching between law enforcement scenarios and policy basis.
Association of unstructured data such as on-site photos requires the retrieval link to support cross-modal association, while ensuring precise matching between policy clauses and case scenarios to avoid recalling irrelevant penalty cases. The strong correlation of law enforcement scenarios requires that recall results cover the basis of specific law enforcement links, rather than only returning general generic clauses. Otherwise, the accuracy of case judgment will be affected.
How to configure the settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
similarity | 0.72–0.80 | Matches the accuracy requirement for urban management law enforcement policy clauses, avoiding recalling regulations from irrelevant scenarios |
limit | Top 10 entries | Covers all policy basis required for case handling, while controlling context length |
searchMode | hybrid | Combines text semantic and keyword matching, adapting to the need for both semantic association and precise clause numbers in law enforcement scenarios |
usingReRank | Enabled | Re-ranks initial recall results to prioritize returning policy clauses most relevant to law enforcement scenarios |
datasetSearchUsingExtensionQuery | Enabled | Automatically expands user queries by adding keywords related to law enforcement scenarios, improving recall coverage |
collectionIds | Bind to the dedicated knowledge base collection for urban management law enforcement | Isolates documents from other categories to avoid interference from irrelevant data on recall results |
Three common configuration mistakes
- Phenomenon: Knowledge base documents are retrieved, but the large model only makes general mentions without citing specific clause content. Cause:
datasetSearchUsingExtensionQueryis not enabled, and the query is not linked to keywords of specific clauses, resulting in recalled clauses not being fully included in the context. - Phenomenon: Single search takes more than 60 seconds, and server resource usage is high. Cause: No reasonable
limitparameter is set, too many irrelevant documents are recalled leading to excessive context length, andusingReRankis not enabled, increasing the model's processing load. - Phenomenon: Recall results are inconsistent each time the same query is submitted. Cause: No fixed
collectionIdsbound to the dedicated knowledge base collection, so the recall range includes documents from other business lines, and thesimilaritythreshold is not adjusted, leading to random matching of marginal results.
How to confirm the configuration is correct
- Submit a test query containing a specific law enforcement scenario, and check whether the recall results include complete document fragments of the corresponding policy basis.
- View the retrieval log to confirm that
searchModeis set to hybrid mode andusingReRankis enabled. - Compare recall results from multiple submissions of the same query, confirm that the results are consistent and do not include documents from non-urban management law enforcement categories.
- Test the incremental update scenario, confirm that newly uploaded daily law enforcement documents can be retrieved within 1 hour.
The values provided here are common starting points and should be evaluated 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.