What the data for this category looks like
Daily documents for this category include spot check plans, inspection object lists, inspection item lists, on-site inspection records, rectification notices, and spot check result announcements. Data sources include the "Double Random, One Public" regulatory platform, enterprise credit information public disclosure system, industry regulatory systems, and law enforcement officer directory. Data updates occur monthly. Most documents contain structured fields and unstructured explanatory content. Some documents include tabular inspection items, law enforcement officer matching information, and spot check result details.
What constraints these characteristics impose on document parsing and chunking
Monthly data updates require document parsing and chunking to support batch processing, to avoid single-run processing timeouts. Mixed input of multiple document types requires chunking logic to adapt to structured tables, long-text records, and short announcement content. Inconsistent document formats from multiple regulatory systems require configuring parsing rules compatible with non-standard layouts. Documents contain key business fields such as law enforcement officer IDs and inspection item details. Chunking must preserve field associations, to avoid splitting that breaks business logic. Some documents have cross-page tabular content. Configure cross-page merging chunking strategies to ensure complete information retention.
How to configure settings
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
chunkSize | 800–1200 characters, 100-character overlap | Balances long text from on-site inspection records and structured paragraphs from spot check plans, avoids splitting that breaks business logic |
chunkSplitter | Split by paragraph + title | Adapts to multiple document structures, preserves association between titles and corresponding business content |
customPdfParse | Enabled | Handles non-standard PDF layouts from multiple regulatory systems, adapts to cross-page tables and irregular content |
PARSE_FILE_TIMEOUT_SECONDS | 300–600 seconds | Covers processing duration for monthly batch documents, prevents single batch task timeout interruptions |
UPLOAD_FILE_MAX_SIZE | 1000 MB | Fits the size range of most regulatory documents, meets monthly batch upload requirements |
chunkSettingMode | Manual configuration | Adjusts chunking rules for multiple document types, matches associations between key business fields such as law enforcement officer IDs and inspection items |
Three common configuration errors
- When
customPdfParseis not enabled, uploading non-standard layout on-site inspection record PDFs results in lost table content or cross-page information breaks. The default PDF parsing rules cannot adapt to the special layout formats of regulatory documents. - When calling external document parsing scripts, returned results lack key business fields such as law enforcement officer IDs and inspection items. The root cause is failure to configure dedicated structured field extraction rules for this category of documents, leading to incomplete recognition of core business information.
- Timeout errors occur when batch uploading monthly updated inspection object lists. The root cause is that the
PARSE_FILE_TIMEOUT_SECONDSconfiguration value is too low, failing to cover the total processing duration of batch documents.
How to verify correct configuration
- Upload a typical spot check result announcement document, check if the parsed chunked content preserves the association between the announcement title and corresponding details.
- Upload an on-site inspection record PDF containing cross-page tables, confirm that table content is complete and intact after
customPdfParseis enabled. - Batch upload 10 monthly updated inspection object list documents, verify that the processing process does not experience timeout interruptions.
- Call the document parsing interface, confirm that returned results include key business fields such as law enforcement officer IDs and inspection items.
These values are common starting points, and should be evaluated against samples from the relevant deployment environment.
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.