What This Category of Data Looks Like
Data for this category comes from urban management law enforcement platforms, urban operation grid platforms, video surveillance systems, and public complaint tickets. Data is updated daily. Common documents include inspection records, case filing approval forms, on-site photos, rectification orders, penalty decisions, and case closure reports. Each document contains fields such as inspection time, point coordinates, violation reasons, rectification requirements, and execution status. On-site photos are unstructured multimedia data bound to the text documents of their corresponding cases.
Constraints for Vector Models and Indexing
Multi-source data updated daily includes structured text and unstructured photos. Indexing processes must adapt to processing rules for different document types. Long texts such as inspection records and penalty decisions require chunking methods tailored to law enforcement logic. This prevents splitting that breaks case association links. On-site photos must first undergo text annotation before being added to the index. Without this step, valid vectors cannot be generated. Law enforcement case data and party building learning content must be stored in separate databases. This prevents unrelated law enforcement details from being included during retrieval. Indexing must support batch incremental updates. This avoids excessive resource usage from full index rebuilding. Meta fields such as responsible entities and rectification status in law enforcement data must be retained. This ensures accurate association with law enforcement specification requirements in party building learning during Q&A.
How to Set Configurations
| Configuration Item | Recommended Value Range | Rationale |
|---|---|---|
| Chunk Length | 800–1200 characters | Adapts to the logical integrity of long law enforcement documents, prevents splitting that breaks case associations |
| Chunk Overlap Length | 100–150 characters | Retains contextual links between adjacent chunks, ensures retrieval does not lose law enforcement process details |
maxToken | 4096 | Adapts to the input upper limit of mainstream embedding models, prevents text truncation that loses key penalty basis and rectification requirements |
defaultToken | 2048 | Sets the input token upper limit for the default embedding model, adapts to short texts such as inspection records and complaint tickets |
| Similarity Threshold | 0.72–0.80 | Accurately matches party building learning content and law enforcement case details, filters low-relevance retrieval results |
| Single Search Limit | Top 10 results | Relevant information for urban management law enforcement cases is concentrated in a small number of documents, prevents excessive results from increasing context processing pressure |
Three Common Misconfigurations
- Issue: A single law enforcement document (such as a case closure report) remains in the indexing state for a long time with no progress updates. Cause: The chunk length and
maxTokenparameters were not adjusted for long text documents, causing the embedding model processing to time out and blocking indexing tasks. - Issue: Q&A workflows do not prioritize retrieval from the party building knowledge base as configured, but instead call content from the law enforcement knowledge base. Cause: The knowledge base priority switch was not enabled in the retrieval configuration, or the party building knowledge base was not set to the highest priority.
- Issue: A 60-second timeout error occurs when switching knowledge base indexes, or a small knowledge base continuously displays the training in progress status. Cause: Incremental index updates were not configured. Full rebuilding of daily updated law enforcement data or small knowledge bases exceeds task timeout limits or uses excessive resources.
How to Confirm Configurations Are Correct
- Upload a typical penalty decision document. Check the update speed of the indexing progress bar to confirm that the chunk length and
maxTokenparameters match the document length. - Initiate a Q&A query related to law enforcement specifications in party building. Verify that retrieval results first hit the knowledge base set to the highest preset priority to confirm the priority configuration is active.
- Manually trigger an incremental indexing task. Check whether the task duration meets expectations to confirm the incremental update configuration is correct.
- Check the meta information of indexed documents. Confirm that fields such as responsible entities and rectification status have been correctly extracted and associated to confirm the meta information retention configuration is active.
The values provided are common starting points. They should be evaluated against sample data for the intended deployment.
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.