What the data for this category looks like
Data for this category comes from administrative law enforcement case handling systems, body camera footage, the national enterprise credit information publicity system, and departmental supervision databases. It is updated daily. Daily documents include on-site inspection records, inquiry transcripts, evidence lists, prior administrative penalty notices, hearing notices, penalty decisions, and service receipts. Core fields focus on illegal fact determination, discretionary benchmark application, and penalty decision content. Some documents include identification fields such as law enforcement officer signatures and law enforcement numbers. There is no unified standard unit.
Constraints on knowledge base retrieval and recall
Daily updated bulk data requires retrieval to support incremental synchronization and high-frequency recall, to avoid excessive resource usage from full scanning. Multiple types of law enforcement documents have significant structural differences. Chunking logic must be adapted for different text types to ensure core fields are accurately matched. Heterogeneous data from multiple systems requires unified preprocessing to eliminate format differences that impact recall accuracy. Business needs centered on penalty decisions and evidence chains require retrieval to prioritize matching illegal facts and content related to legal clauses. This ensures retrieval results align with law enforcement scenarios.
Configuration settings
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
similarity | 0.72–0.85 | Matches the relevance between technical terms and illegal facts in law enforcement documents, avoiding recall of irrelevant general administrative documents |
limit | Top 8–12 entries | Covers the number of evidence, notice, and decision documents required for a single penalty case file, ensuring complete context |
searchMode | vector_search | Targets the structured and semi-structured features of law enforcement documents, prioritizing vector retrieval to match core semantics |
usingReRank | Enabled | Rearranges initial recall results by business relevance, prioritizing return of content related to penalty discretion and legal application |
datasetSearchUsingExtensionQuery | Enabled | Automatically expands query terms related to law enforcement, such as expanding "penalty" to "prior administrative penalty notice", "penalty decision document", and similar terms |
collectionIds | Bind corresponding collections by law enforcement type | Limits retrieval scope to the administrative penalty case file collection of the current law enforcement institution, avoiding interference from cross-category data |
Three common mistakes
- Phenomenon: Returned results have format errors and cannot be recognized as standard JSON. Cause: Retrieval result serialization rules are not configured correctly, or extended query parameters cause returned content to exceed format limits.
- Phenomenon: Retrieval results return empty JSON. Cause: Correct
collectionIdsare not bound, orsearchModeis configured incorrectly, preventing matching of target data. - Phenomenon: Data cannot be added to or deleted from the specified collection via API. Cause: Correct collection identification parameters are not included in API requests, or permission configuration does not grant access to the corresponding operations.
How to confirm the configuration is correct
- Submit test queries for law enforcement scenarios, check if returned result formats meet expectations and have no syntax errors.
- View retrieval logs to confirm that
collectionIdsis bound to the correct administrative penalty case file collection, and no cross-category data is mixed in. - Verify that the reranking function works, compare the order of initial recall results and rearranged results to confirm that core business content is displayed first.
- Test the API add and delete interface, confirm that data in the specified collection can be added or deleted normally, and no permission errors occur during operations.
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.