What the Data for This Category Looks Like
The data for this category originates primarily from urban management law enforcement platforms, urban operation grid platforms, video surveillance systems, and public complaint work orders. The update frequency is daily. Daily documents include inspection records, case filing approval forms, on-site photos, rectification orders, penalty decisions, and case closure reports. Data fields cover event locations, timestamps, violation type descriptions, case numbers, disposal progress, and additional relevant fields. Some documents include multimedia attachments.
Constraints on Vector Models and Indexing Workflows
Bulk daily updated data requires indexes to support incremental synchronization, to prevent excessive resource consumption from full reindexing. Mixed document types, including text and on-site photos, require vector models to support cross-modal feature extraction. Case documents contain both structured fields and unstructured descriptions. Chunking must avoid splitting related information across multiple chunks. Some documents contain long text paragraphs. Chunk boundaries must be set appropriately to preserve the complete semantics of policy basis.
Reference only; verify against the target FastGPT release and deployment documentation.
How to Configure Parameters
| Configuration Item | Recommended Value Range | Rationale |
|---|---|---|
| Chunk Length | 800–1200 characters | Adapts to the average paragraph length of documents such as inspection records and penalty decisions, preventing key policy basis from being truncated |
| Overlap Length | 100–200 characters | Preserves contextual connections across chunks, ensuring coherent matching between case descriptions and policy clauses |
| Similarity Threshold | 0.75–0.85 | Balances retrieval accuracy and recall rate, meeting the strict requirements for policy basis in urban management law enforcement scenarios |
| Single Search Limit | Top 10 results | Controls the number of returned results, preventing law enforcement personnel from being distracted by redundant information |
defaultToken | 2048 | Adapts to the input length limit of most local vector models, and is compatible with short-text scenarios such as inspection records |
maxToken | 4096 | Meets the vector extraction requirements for long texts such as penalty decisions and case closure reports |
Three Common Mistakes
- Incorrect knowledge base capacity estimation. This occurs when the storage proportion of text vectors and multimedia attachments is not differentiated, and calculations are based solely on document count, failing to accurately match actual storage requirements.
- 503 status codes returned by vector model calls. This happens when the concurrent request threshold is not adjusted based on the daily volume of updated law enforcement data, leading to service overload and delayed response.
- Low matching degree between retrieval results and policy basis. This is caused by using a general vector model without domain fine-tuning, which cannot accurately identify specialized terminology and scenario logic for urban management law enforcement.
How to Verify Correct Configuration
- Manually upload an inspection record and a penalty decision, confirm the number of post-chunking text chunks matches expectations, and no critical policy content is truncated.
- Initiate a test query containing a violation type description, check that the similarity values of returned results fall within the 0.75–0.85 range.
- Simulate daily incremental updates of law enforcement data, confirm the index only synchronizes newly added data and does not trigger a full reindexing process.
- Call the vector model interface, confirm the dimension of the returned embedding vector matches the configured model parameters.
The values provided here are common starting points, and should be evaluated against respective deployment 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.