What the Data for This Category Looks Like
The business data for urban sanitation and urban management law enforcement cases comes from four sources: urban management law enforcement platforms, urban operation grid platforms, video surveillance, and public complaint work orders. Daily generated documents include patrol records, case filing approval forms, on-site photos, rectification order notices, penalty decisions, and case closure reports. Common fields include case identification, violation type, responsible subject, and rectification progress. The data updates daily. It covers business information across the full process of on-site patrol, public reports, and law enforcement disposal.
What Constraints Do These Characteristics Impose on the "Knowledge Base Retrieval and Recall" Link?
Data sources for this category are diverse, with significant format differences. They include text work orders, patrol records, and non-text on-site photos. Retrieval systems must support multi-type data recall. Data updates daily. Knowledge base incremental synchronization timeliness must be maintained to avoid using expired law enforcement document content. Case handling relies on accurate law enforcement procedures and evidence documents. Retrieval and recall must prioritize content from key links such as filing, rectification, and penalty. Failure to do so may lead to insufficient case evidence or law enforcement disputes. Frontline grid workers and law enforcement personnel often use colloquial on-site questions. Optimized matching is required to align with standardized law enforcement document content.
Configuration Settings
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
similarity | 0.75–0.82 | Law enforcement case documents have high professionalism. A higher matching threshold filters irrelevant content while covering common wording differences for violation types |
limit | Top 6 entries | Case handling requires associating multiple documents such as patrol records and penalty documents. Too many entries increase token consumption, while too few may miss critical evidence |
searchMode | Hybrid retrieval | Adapts to multi-type data recall needs for text work orders, records, and non-text on-site photos |
usingReRank | Enabled | Key information in law enforcement documents such as rectification requirements and responsible subjects may not appear at the start of passages. Reranking improves the ranking priority of core content |
datasetSearchUsingExtensionQuery | Enabled | Frontline grid workers’ on-site questions are often colloquial. Optimization allows matching standardized law enforcement document content |
collectionIds | Bind to dedicated law enforcement dataset | Isolate documents from other categories to avoid irrelevant content interfering with law enforcement case retrieval results |
Three Common Misconfigurations
- Phenomenon: A large amount of irrelevant chat content is returned even when retrieval results are empty. Cause: The reverse filtering for
datasetSearchUsingExtensionQueryis not enabled, or a dedicated dataset is not configured, leading to recall of general knowledge base content. - Phenomenon: The number of recalled documents per single retrieval is too high, causing token consumption to exceed the preset 8000 token threshold. Cause: The
limitparameter is not set appropriately, and the upper limit is not adjusted based on the single-document length of law enforcement documents. - Phenomenon: Retrieved documents are poorly sorted, with key rectification requirements not appearing at the top. Cause: The
usingReRankreranking function is not enabled, and only basic similarity ranking is used, which cannot highlight core law enforcement information.
How to Confirm Proper Configuration
- Import a single typical urban management law enforcement case file, enter a corresponding question such as "What is the filing process for an unauthorized street vending case", and check whether the recalled results include the core content of this document.
- Enter a chat-style question such as "What is the weather today", and check whether no law enforcement-related documents are recalled, or if no matching results are returned directly.
- Check the number of documents returned by retrieval, confirm that it matches the value set by the
limitparameter, with no abnormal overages or shortages. - Check the sorting of retrieval results, confirm that key information such as rectification requirements and responsible subjects appears at the top, and verify that
usingReRankis active.
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.