What this category of data looks like
Data for this category originates from administrative law enforcement case handling systems, law enforcement recorder footage, national enterprise credit information publicity systems, and departmental supervision databases of market supervision, ecological environment, transportation and other law enforcement agencies. The update frequency is daily. Daily documents include on-site inspection records, interrogation records, evidence lists, prior administrative penalty notification letters, hearing notification letters, penalty decisions, service receipts and more. Different documents follow fixed standardized structures. Some include handwritten annotations or image-based evidence. Fields focus on illegal facts, penalty basis, discretionary benchmarks and service information.
Constraints on document parsing and chunking
Law enforcement case file data has diverse sources, covering text documents and image-based evidence. This means the parsing module must support extraction of both structured forms and unstructured content. Batch documents updated daily require an efficient parsing process to avoid delaying case handling progress. Different document types have distinct structural differences. The chunking logic must adapt to both fixed paragraphs of standardized documents and free question-and-answer content in records. Errors in parsing directly link to law enforcement risks such as penalty revocation and administrative reconsideration litigation losses. Parsing accuracy must therefore ensure key fields are not lost or confused.
Configuration Settings
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Value Range | Rationale |
|---|---|---|
chunkSize | 800–1200 characters | Adapts to the single-paragraph content length of documents such as records and notification letters in law enforcement case files. It preserves contextual relevance while avoiding excessive chunking that causes retrieval redundancy |
chunkSplitter | Semantic chunking + fixed length hybrid | Balances the fixed structure of standardized documents and free-form content of records. It preserves the integrity of key paragraphs such as legal clauses and illegal facts, while reasonably splitting long texts |
customPdfParse | Enabled | Supports extraction of form fields and handwritten annotations from standardized law enforcement documents, adapts to OCR parsing requirements for image-based evidence, and avoids missing key information |
UPLOAD_FILE_MAX_SIZE | 1000 MB | Meets the batch upload requirement for single law enforcement case files containing multiple documents and image files, and adapts to the document scale of daily case handling |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Reserves sufficient time for parsing multi-page PDFs and image-based evidence, avoids parsing failures due to timeouts, and ensures complete processing of complex case files |
chunkSettingMode | Manual mode | Allows manual adjustment of chunking rules for structural differences of case files across different law enforcement categories, adapting to parsing requirements for documents such as on-site inspection records and penalty decisions |
Three Common Configuration Errors
- Phenomenon: When parsing a law enforcement case file, the system loads other previously uploaded case files simultaneously. Cause: The parsing scope is not limited to the currently uploaded attachments. The system uses the parsing logic for all documents in the knowledge base by default.
- Phenomenon: After uploading law enforcement recorder image files, the model cannot recognize text in the images, or Chinese garbled characters appear. Cause: The
customPdfParseconfiguration is not enabled, and OCR parsing rules adapted to Chinese law enforcement documents are not configured. This prevents correct extraction of image content. - Phenomenon: When asking questions about a single uploaded administrative penalty decision, the returned content includes irrelevant information from other case files. Cause: Chunking parameters are not adjusted for standardized law enforcement documents. This causes incorrect association of chunked content from different documents, leading to irrelevant data being included during retrieval.
How to Confirm Proper Configuration
- Upload a single law enforcement case file document. Check the parsing log to confirm only the currently uploaded file is included in the parsing scope, with no historical documents involved.
- Upload a law enforcement case file containing images. Verify that text content in the images is fully extracted in the parsing results, with no garbled characters or missing key information.
- Submit a question about a single uploaded prior administrative penalty notification letter. Confirm the returned content only comes from this document, with no interference from irrelevant cross-document information.
- Adjust the
chunkSizeparameter. Compare chunking results across different documents to confirm chunk length matches the preset range and adapts to each document’s content structure.
The values listed here are common starting points, and should be evaluated against your own specific 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.