Reference only; verify against the target FastGPT release and deployment documentation.
What the Data for This Category Looks Like
It typically includes daily work data from urban management law enforcement bureaus, street comprehensive law enforcement teams, sanitation centers, and grid workers. Daily documents include inspection records, case filing approval forms, on-site photos, rectification orders, penalty decisions, closing reports, and more. These contain both structured form fields and unstructured text and image attachments. Data mainly comes from urban management law enforcement platforms, urban operation grid platforms, video surveillance, and public complaint tickets. Update frequency is daily. Most document fields contain case-specific law enforcement content such as case number, violation location, responsible party, and rectification requirements.
What Constraints Do These Characteristics Impose on the Document Parsing and Chunking Step?
Multi-source data and diverse document structures in this category create multiple constraints for the parsing and chunking process. Multi-source data includes structured forms, unstructured text, and image attachments. This requires parsing tools to support both format recognition and metadata extraction. High-frequency daily updates require efficient parsing processes to avoid delays that disrupt case workflow. Specialized law enforcement fields such as violation location and rectification requirements must retain contextual associations during chunking, to prevent critical law enforcement information from being split apart. Case files with multiple attachments require sufficient processing capacity for the parsing workflow, to avoid parsing failures caused by overly large files.
How to Set the Configuration
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
chunkSize | 800–1200 characters | Adapts to the natural paragraph length of urban management case documents, retains critical context such as violation facts and rectification requirements |
chunkSplitter | Split by paragraph + line breaks | Matches the segmentation logic of inspection records and penalty decisions, avoids splitting complete law enforcement clauses or responsibility determination content |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Addresses case files containing on-site photo attachments, avoids timeout during large file parsing |
customPdfParse | Enabled | Supports parsing standard law enforcement PDF documents such as rectification orders and penalty decisions, retains original layout and field structure |
UPLOAD_FILE_MAX_SIZE | 100 MB | Adapts to the upload limit for single case files, meets the needs of integrated parsing for multiple attachments |
Three Common Mistakes
- Parsing results are empty or key fields are missing after uploading case documents. The
customPdfParseconfiguration is not enabled, so the PDF format of standard law enforcement documents cannot be correctly recognized, leading to parsing failure. - Core law enforcement fields such as case number and violation location are lost after chunking. The
chunkSplitteris set to split by fixed character count, which does not retain contextual associations, splitting complete law enforcement information into multiple unrelated chunks. - Parsing timeout errors occur when uploading case files with multiple attachments. The
PARSE_FILE_TIMEOUT_SECONDSvalue is set too low, not adapting to the parsing time required for case documents with multiple on-site photos.
How to Confirm the Configuration Is Properly Set
- Upload a standard rectification order PDF, check that the parsing result fully retains core sections such as the document header, violation facts, and rectification requirements.
- Review the chunking results, confirm that each chunk contains at least one complete law enforcement-related field, and no cross-critical information splitting has occurred.
- Upload a case file containing 3 on-site photo attachments, confirm that no parsing timeout error is triggered, and attachment metadata is correctly recognized.
- Adjust
chunkSizeto different ranges, test the chunking effect of inspection records, confirm that no key sentences are forcibly split.
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.