What data in this category looks like
Data for this category comes from the unified budget management system, centralized treasury payment system, accounting system, and asset management system. Updates occur annually. Commonly processed documents include department final account statements, balance sheets, income and expenditure final account statements, final account explanations, and government financial reports. Most documents combine structured tables and explanatory text. Fields include budget codes, income and expenditure amounts, original asset values, and similar items. Units are mostly ten thousand yuan or yuan. Some reports include fixed row orders and verification rules.
Constraints on the document parsing and chunking link
Annual batch-updated documents require parsing processes to support stable batch adaptation. Structured statements need accurate identification of row orders and field correspondence. Chunking must not break table association logic. Document formats exported from multiple systems vary widely. Parsing rules must support different export specifications. Final account statements include embedded verification rules and associated fields. Context associations must be retained during chunking. Otherwise, subsequent account statement verification cannot proceed. Large annual summary documents have significant file sizes. Parsing processes must support large files to avoid transmission or parsing interruptions.
How to set configurations
The following configurations follow the functional specifications of FastGPT v4.17.0.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
chunkSize | 800–1200 characters | Adapts to the structured field length of final account statements, retains complete context for core fields such as income and expenditure and assets |
chunkSplitter | Split by paragraph and table boundaries | Avoids breaking the association between table row orders and explanatory text, adapts to the mixed format of final account documents |
customPdfParse | Enable structured parsing mode | Accurately identifies fixed row orders and fields of final account statements, prevents field misalignment caused by general parsing |
UPLOAD_FILE_MAX_SIZE | 1000 MB | Supports batch upload of multiple annual summary documents, meets the transmission needs of large-volume final account statements |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Matches the parsing time required for complex final account documents, prevents mid-parsing timeout interruptions for large files |
Three common mistakes
- Symptom: When uploading PDF or image format final account documents, chunking recognition results are empty or have missing fields. Cause: The structured parsing mode of
customPdfParseis not enabled. General parsing cannot adapt to the fixed row order format of final account statements. - Symptom: When uploading a large annual summary PDF file, the upload progress reaches 90% and an "offset out of range" error occurs. Cause:
UPLOAD_FILE_MAX_SIZEis not adjusted to a value suitable for large files, or the deployment environment's upload timeout setting is insufficient. - Symptom: Chunking results for final account documents uploaded via API differ from those uploaded directly through the platform. Cause:
chunkSplitterandchunkSizeparameters are not uniformly configured. Default chunking rules vary across different upload channels.
How to confirm configurations are set correctly
- Upload a single typical final account statement. Check if the chunking result retains complete table row orders and associated explanatory text.
- Upload the largest volume annual summary document. Confirm that no timeout or offset error occurs during the parsing process.
- Upload the same document through the platform frontend and API respectively. Verify that the paragraph and field division of the chunking results are consistent.
- For structured statements, verify that parsed fields accurately correspond to the row orders and codes of the original document.
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.