What this category of data looks like
Data for this category comes from state-owned enterprise and public sector procurement platforms, public resource trading platforms, supplier databases, contract management systems, and audit issue repositories. The update frequency is daily. Documents processed daily include procurement plans, requirement specifications, bidding documents, bid evaluation records, contracts, acceptance documents, and supplier complaint materials. This covers structured tabular data and unstructured text. Fields involved include procurement method, budget basis, scoring rules, and supplier qualification requirements. Some documents contain multi-page tables and nested formatting.
What Constraints These Characteristics Impose on Document Parsing and Chunking
Parsing for this category’s multi-source, high-frequency updated documents must adapt to multiple formats, including PDFs with nested tables and structured CSV files. Procurement documents often include cross-page compliance clauses and scoring rules. Chunking must retain contextual connections to avoid splitting critical compliance logic. Daily updated batch documents require controlled parsing duration, while accurately extracting table fields to avoid missing key data. Some documents involve audit and discipline inspection content. Original details must be fully retained to prevent loss of evidence important for compliance review.
Configuration Settings
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
chunkSize | 800–1200 characters | Adapts to cross-page compliance clauses and table paragraphs in procurement documents, retains contextual integrity |
chunkSplitter | Split by paragraph + filter headers and footers | Matches the chapter structure of procurement documents, avoids splitting continuous compliance content such as bid evaluation records and contract clauses |
customPdfParse | Enabled | Adapts to PDF files with nested tables and mixed formats in this category of documents, overcoming limitations of the default parsing method |
PARSE_FILE_TIMEOUT_SECONDS | 300–600 seconds | Addresses parsing duration for large batch procurement documents, avoids timeout interruptions |
UPLOAD_FILE_MAX_SIZE | 100–200 MB | Meets upload requirements for large bidding documents and supplier complaint materials |
chunkSettingMode | Manual configuration | Adjusts chunking rules for different document types (such as bidding documents and contracts) to meet accuracy requirements for compliance review |
Three Common Misconfigurations
- Phenomenon: Only the first two columns of CSV table data are imported, and fields are missing after parsing. Reason: Parsing rules were not adjusted for multi-column structured data in procurement documents. The default parsing logic limits the field extraction scope.
- Phenomenon: Custom PDF parsing service calls time out, and the task status shows failure. Reason: The
PARSE_FILE_TIMEOUT_SECONDSparameter was not adjusted. The parsing time of large bidding documents exceeds the default threshold. - Phenomenon: Compliance clauses are split after chunking, and context cannot be associated. Reason: The
chunkSizevalue is too small, truncating cross-page key compliance content such as procurement methods and budget basis.
How to Verify Proper Configuration
- Upload a standard bidding document PDF, and check that the parsed text includes complete scoring rules and supplier qualification clauses, with no obvious content omissions.
- Upload structured CSV procurement data, and confirm that extracted fields cover necessary items such as procurement number, budget amount, and supplier qualifications. Do not retain only the first two columns.
- View parsing task logs, and confirm that the
PARSE_FILE_TIMEOUT_SECONDSparameter is active, with no timeout error records. - Adjust the
chunkSizeparameter, then compare chunking results to ensure cross-page compliance paragraphs are not 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.