This documentation is built using the document parsing and chunking functionality of FastGPT v4.17.0.
What the data for this category looks like
Data for this category typically originates from urban management law enforcement platforms, urban operation grid platforms, video surveillance systems, and public complaint work orders. The update frequency is daily.
Commonly processed documents include inspection records, case filing approval forms, on-site photos, rectification orders, penalty decisions, and case closure reports. Most data fields include case numbers, violation locations, responsible parties, rectification requirements, execution status, and similar metrics. Units of measurement include case counts, square meters, person-times, and other standard units. The full dataset is generated around end-to-end records of on-site urban law enforcement and sanitation disposal operations.
What constraints these characteristics impose on document parsing and chunking
The multi-source heterogeneous document structure of this category requires the document parsing link to support extraction of multiple formats, including text and image metadata. This prevents omission of location information and rectification requirements from on-site photos.
The daily updated batch data volume requires the parsing and chunking workflow to have stable batch processing capabilities, to avoid timeouts.
Case documents include both structured fields and unstructured descriptive content. Chunking must balance field integrity and contextual coherence, to avoid splitting associated information related to violation determination.
How to configure the settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
chunkSize | 800–1200 characters | Urban management law enforcement case documents often include associated fields and on-site descriptions. This range balances contextual integrity and retrieval accuracy within a single chunk |
chunkSplitter | Split by paragraph + fixed character boundaries | Documents such as inspection records and penalty decisions mostly use paragraphs as logical units. Combining fixed character boundaries prevents splitting of key content such as penalty basis and rectification requirements |
customPdfParse | Enabled | Official documents such as rectification orders and penalty decisions mostly use standard PDF formats. Enabling custom parsing accurately extracts form fields and signature metadata |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Single case documents that include on-site photo attachments have long parsing times. This duration covers the parsing needs of most batch documents |
chunkSettingMode | Manual configuration | Adjustment of chunking rules is required for different document types such as inspection records and penalty decisions. Manual configuration adapts chunking logic to multiple scenarios |
UPLOAD_FILE_MAX_SIZE | 50 MB | Urban management law enforcement case documents often include on-site photo attachments. This size covers the storage and parsing needs of most single case documents |
Three common configuration errors
- Parsed document content fails to render as Markdown, and only raw tags appear in context references. This occurs because the format adaptation switch for
customPdfParseis not enabled, leading to failure to correctly convert parsed metadata into renderable formats. - Passing external links fails to extract document content, and only a version update prompt is returned. This occurs because the configured
PARSE_FILE_TIMEOUT_SECONDSvalue does not match the loading speed of the target link, or the document format corresponding to the link is not supported. - Chunking configuration does not match business requirements, leading to missed associated case information during retrieval. This occurs because the
chunkSizeandchunkSplitterparameters are not adjusted based on the logical units of inspection records and penalty decisions, and generic chunking rules are used blindly.
How to confirm the configuration is correct
- Upload a single standard penalty decision PDF, and verify that the parsed result fully extracts violation determinations, penalty content, and execution requirements.
- Review the chunked text blocks, and confirm that each block has coherent logical content, and no key associated information is split.
- Test passing an external law enforcement document link, and confirm that the parsing workflow has no timeout errors and can extract valid text.
- Check the chunked chunk identifiers, and confirm that corresponding content can be copied normally.
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.