What the data for this category looks like
The core documents for this category come from the unified budget management system, centralized treasury payment system, accounting system, and asset management system, with an annual update frequency. Daily submitted materials include five categories: department final account statements, balance sheets, income and expenditure final account statements, final account explanations, and government financial reports. Most documents use a fixed structure of nested tables paired with standardized explanatory paragraphs, including uniformly coded revenue and expenditure subjects, amount fields, and detailed explanatory items.
What constraints do these characteristics impose on the document parsing and chunking link
The annual update requirement means parsing and chunking must handle multiple documents with the same structure in bulk to avoid repeated configuration. Fixed-format nested tables and standardized fields require that the association between subjects and amounts is retained during chunking. Content linked across cells cannot be split. Documents imported from multiple source systems may have format differences, so adaptation to different PDF, Word, and table layouts is needed. The chunking results must also match the account statement verification logic of subsequent review links, otherwise review failures or data caliber errors will occur.
How to set the configuration
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
chunkSize | 800–1200 characters | Department final account documents contain nested tables and long explanatory paragraphs. This range preserves the complete meaning of a single report page or single explanatory section |
chunkSplitter | Split by heading + paragraph | Matches the fixed chapter structure of final account documents, avoiding splitting table content linked across subjects |
customPdfParse | Enabled | Adapts to the standardized PDF report format submitted by budget units, preserving the correspondence between table cells |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Single annual final account documents usually contain multiple pages of reports and explanations, reserving sufficient parsing time |
chunkSettingMode | Manual configuration | Adjust chunking rules for different document types (statements/explanations) to adapt to format differences from multi-source system imports |
Three common misconfigurations
- Some tables fail to chunk correctly: Nested tables in final account report PDFs uploaded to the knowledge base are split into scattered fragments. This occurs because the
customPdfParseconfiguration is not enabled, or thechunkSizesetting is too small, causing splitting of subject-linked content across cells. - The parsing service reports out-of-memory errors or fails to recognize the GPU: Docker containers are deployed without correctly mapping GPU hardware, or the CUDA version required by parsing dependencies is not matched, causing parsing load to exceed allocated resources.
- Image domain names are lost after importing Word documents: Image path retention rules are not configured, or images are not linked to corresponding final account explanation paragraphs during the Markdown conversion process, making it impossible to match image context during conversations.
How to confirm the configuration is correct
- Upload a single department final account report PDF, check if the chunking results parsed by FastGPT v4.17.0 retain the complete association between subjects and amounts for a single table.
- View the parsing service logs to confirm that the GPU hardware is properly recognized and there are no out-of-memory error reports.
- Import a Word-format final account explanation document, check if the converted Markdown retains the complete path of the original images and binds them to corresponding paragraphs.
- Test multiple final account documents from different sources to confirm that the parsing and chunking results comply with the preset chapter splitting rules.
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.