What the data for this category looks like
Business data for this category comes from centralized treasury payment systems, unified budget management systems, electronic invoice platforms, and contract management systems. The system processes these documents daily: payment applications, fund appropriation plans, invoices, contracts, acceptance documents, reimbursement approval forms, and payment vouchers. Daily data updates run automatically. Core coverage includes business content for individual fund payment execution links. Fields include budget indicators, economic classifications, approval nodes, and payment amounts. This data falls under segmented business data for daily payment execution in fiscal management.
What constraints these characteristics impose on the "document parsing and chunking" link
Documents from multiple systems have inconsistent formats. These formats include plain text, tables, packaged files, and other types. The parsing engine must support extracting content from complex formats. Daily batch update business scenarios require parsing functions to support batch task processing. This avoids timeout interruptions. Documents related to individual payments have strong relevance. For example, reimbursement approval forms must link to corresponding contracts and acceptance documents. Chunking must retain contextual relevance. It must avoid splitting content across business nodes. Business errors directly affect fund compliance. Parsing results must be accurate. They must not lose key fields or mix payment data from different batches.
How to set configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
chunkSize | 800–1200 characters | Adapts to the standard text length of individual payment applications and reimbursement approval forms, avoiding splitting contextual content across approval nodes |
chunkSplitter | By paragraph + semantic boundary | Adapts to multi-format documents, retains the association between table paragraphs in contracts and acceptance documents, and avoids splitting table rows and their corresponding explanatory text |
customPdfParse | Enable pdf-marker parsing mode | Handles complex tables in invoices and contracts, fully extracts field information within cells, and avoids content missing |
PARSE_FILE_TIMEOUT_SECONDS | 300–600 seconds | Adapts to the multi-document processing scenario of daily batch uploads, avoiding parsing task interruptions due to timeouts |
UPLOAD_FILE_MAX_SIZE | 50 MB | Adapts to batch uploads of payment vouchers and contract packaged files, avoiding upload failures due to oversized files |
chunkSettingMode | Manual configuration | Adjust chunking parameters for different document types (such as invoices, payment applications) to meet the precise retrieval needs of party building learning Q&A |
Three common configuration errors
- After uploading a contract PDF with complex tables, the knowledge base chunking result lacks table fields. Cause: The
customPdfParseconfiguration is not enabled. The default parsing engine cannot extract cell content from complex tables. - When batch uploading daily payment vouchers, parsing tasks trigger timeouts. Cause: The
PARSE_FILE_TIMEOUT_SECONDSparameter is not adjusted. The default short timeout setting cannot complete batch parsing of multiple documents. - Search results after chunking include irrelevant cross-batch payment application content. Cause: The
chunkSizesetting is too large. It merges text from multiple payment applications into one chunk. This prevents accurate matching of party building learning Q&A needs for individual businesses.
How to confirm configurations are correctly set
- Upload a contract PDF containing complex tables. Check if the knowledge base chunking result retains the corresponding text content of table cells.
- Upload a batch payment voucher package under 50 MB. Confirm that the parsing task completes within the preset timeout period without timeout errors.
- Upload individual payment application documents and multiple payment application documents separately. Check if chunking is split by individual business and does not merge content across batches.
- In the knowledge base management interface of FastGPT v4.17.0, modify the
chunkSizeparameter. Re-upload the test document, and confirm that the chunk length adjusts with the configuration.
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.