What This Category of Data Looks Like
Policy and regulatory basis documents for expressway operations originate primarily from official normative documents issued by the national transport authority and provincial transport departments, plus internal management systems of local expressway operation enterprises. Document updates align with changes to national or local transport policies, with no fixed schedule. Some annual compilation files have large file sizes. Typical document structures include issuing authority, document number, effective date, chapters and clauses, and attachment lists. Common formats are PDF and Word. Some older policy documents are scanned images. Individual document lengths range from a few pages to hundreds of pages.
Constraints for Document Parsing and Chunking
The clear hierarchical structure of policy documents requires chunking to retain the association between chapters and clauses, to avoid breaking complete policy logic during splitting. Some older documents are in scanned image format, requiring high-precision OCR to restore full text, which adds parsing complexity. The lack of fixed update cycles and variable file sizes means parsing functions must support incremental updates and large file processing. Documents include metadata such as document numbers and effective dates, which must be retained during chunking to improve retrieval accuracy. Policy compilation files with multiple attachments may use multiple formats, so parsing rules must support different file types.
Configuration Settings
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
chunkSize | 800–1200 characters | The length of a single clause in expressway policy documents mostly ranges from 500 to 1000 characters. This range avoids splitting that breaks clause integrity |
chunkSplitter | Split by chapter titles | Policy documents have clear chapter and clause hierarchies. Retaining structure facilitates associated retrieval |
customPdfParse | Enable high-precision OCR mode | Some older policy documents are in scanned image format, requiring complete text restoration |
PARSE_FILE_TIMEOUT_SECONDS | 300–600 seconds | Single policy compilation files may include multi-chapter attachments, requiring sufficient time to complete parsing |
chunkSettingMode | Manual configuration | Adjust chunking rules based on the hierarchical structure of policy documents to adapt to retrieval needs |
UPLOAD_FILE_MAX_SIZE | 500 MB | Single policy compilation files often have large sizes. Raising the upper limit prevents upload failures |
Three Common Mistakes
- No search results and a parsing failure error appear after uploading scanned policy documents: The
customPdfParsehigh-precision mode is not enabled, so text cannot be correctly extracted from scanned documents. - Policy clause retrieval results are dispersed and have low matching accuracy: The
chunkSizevalue is too small, splitting complete clauses into multiple fragments and causing matching information to be dispersed and truncated during retrieval. - Some policy documents do not trigger the parsing process in simple mode: The
UPLOAD_FILE_MAX_SIZEsetting does not match the document size, or thePARSE_FILE_TIMEOUT_SECONDSvalue is insufficient, causing large file parsing to time out without completion.
How to Confirm Successful Configuration
- Upload a single scanned policy document, check if the parsed text fully restores clause content to confirm the high-precision OCR configuration is active.
- Upload a policy compilation file with multiple chapters, verify that chunked segments are bounded by chapter titles and do not break complete clauses.
- Upload a policy file larger than 100 MB, confirm the upload succeeds and the parsing task completes normally to verify the
UPLOAD_FILE_MAX_SIZEconfiguration is appropriate. - Run a search test, input keywords from a policy clause, confirm retrieval results include the complete clause content with no fragment loss.
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.