What this category of data looks like
This category of data originates from administrative law enforcement case handling systems, law enforcement recorder footage, the National Enterprise Credit Information Publicity System, and departmental supervision databases. Updates are applied daily. Commonly processed documents include on-site inspection records, interrogation records, evidence lists, prior administrative penalty notification letters, hearing notification letters, penalty decisions, and delivery receipts. Each document includes fields such as law enforcement subject identification, description of illegal facts, evidence association information, reference of legal provisions, and penalty decision content. Some documents include unstructured law enforcement footage-related metadata.
Constraints on vector models and indexing
Indexes must support incremental synchronization mechanisms for batch daily business data. This avoids performance losses from full reindexing. Tailor splitting rules for transcript-style text and structured official documents to handle mixed document types. This prevents incorrect splitting of specialized law enforcement terminology and referenced legal provisions. Bind index metadata one-to-one with original documents to meet traceability requirements for law enforcement case files. Retrieval results directly link to original materials from the corresponding law enforcement stage. Use vector models adapted to professional corpora in the public law enforcement domain to ensure semantic accuracy for specialized legal and law enforcement terminology.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
| Chunk Length | 800–1200 characters | Single paragraphs in law enforcement documents typically run hundreds of characters. This range preserves complete semantics of law enforcement procedures or legal provisions. |
| Overlap Length | 100–200 characters | Prevents specialized terminology across chunks from being split apart, ensuring continuity of associated semantics. |
| Similarity Threshold | 0.75–0.85 | Filters low-relevance general legal statements, enabling precise matching of policy clauses corresponding to case files. |
| Maximum Search Results per Query | Top 8 entries | Administrative penalty basis materials typically concentrate in a small number of clauses and evidence. Excessive results can interfere with legal review judgments. |
maxToken | 8000 | Adapts to the context window requirements of FastGPT v4.17.0, accommodating core retrieval results and original policy text for a single case file. |
defaultToken | 2000 | Reasonable display length for a single retrieval result, meeting the quick viewing needs of law enforcement personnel. |
Three Common Configuration Errors
- Enabling the Doubao-embedding-large indexing model, entering a custom request address and API key, then clicking test results in an error. The cause is failure to configure a proxy route for the corresponding model in AIProxy, or the request address format does not comply with FastGPT access specifications.
- The number of retrieval results after index creation does not match expectations, with only a small amount of relevant content returned. The cause is an excessively large chunk length, leading to key law enforcement transcript content not being effectively split and indexed.
- Retrieval results include a large number of irrelevant general legal clauses, failing to accurately match law enforcement clauses corresponding to case files. The cause is a similarity threshold set too low, failing to filter results with low semantic matching.
How to Verify Correct Configuration
- Navigate to the index management page in FastGPT, view the chunk parameters of the created administrative penalty case index, and confirm they match the values in the configuration table.
- Upload a single typical law enforcement transcript document, perform incremental index synchronization, and check that the synchronization log contains no chunk failure or format error messages.
- Input a simulated law enforcement scenario question, retrieve corresponding policy basis, and verify that the semantic matching degree of returned results meets the preset threshold requirements.
- Test the access configuration for the custom vector model, click the test button, and confirm a successful response is returned with no connection or key error prompts.
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.