What this category’s data looks like
Core data for this category comes from annual export results of the budget management integrated system, centralized treasury payment system, accounting system, and asset management system. Routine documents include multiple types of structured financial documents, such as department final account statements, balance sheets, income and expenditure final account statements, and final account explanations. The data update cycle is annual. Documents typically use a multi-table combined structure, with unified financial revenue and expenditure, asset and liability fields. The total content of a single annual final account report increases as the unit’s hierarchy level rises.
What constraints do these characteristics impose on the document parsing and chunking step
The annual centralized update feature requires the parsing process to support batch data processing and avoid single-task timeouts. Documents from multiple systems have minor format differences. The field associations of original data must be preserved, and table-to-table verification logic must not be broken during splitting. Improper splitting of multi-column structured financial tables will prevent association of corresponding revenue and expenditure, asset data during retrieval. Excel format reports may have column count recognition limits during upload, so parsing rules need to be configured specifically.
How to set configurations
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
chunkSize | 800–1200 characters | Adapts to the single-table field density of department final account reports, and avoids splitting that breaks logical associations of financial data |
chunkSplitter | Split by paragraph + table boundary | Matches the multi-table combined document structure, and preserves row and column associations within a single table |
customPdfParse | Enabled | Adapts to formatted final account report PDFs exported from business systems, and preserves the original table layout and field correspondence |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Handles the batch data parsing duration of annual final account reports, and avoids interruptions when parsing large files |
UPLOAD_FILE_MAX_SIZE | 1000 MB | Supports packaged upload requirements for batch subordinate unit reports |
Three common misconfigurations
- When uploading a multi-column department final account Excel file, only the first two columns of data are recognized. This occurs because the column mapping configuration for custom chunking is not enabled, and the default setting only reads the first two columns of the document.
- After enabling the
customPdfParseconfiguration, the PDF parsing task throws an error and returns no valid content. This occurs because the mineru API key or interface address is not configured correctly, preventing the enhanced parsing function from being called normally. - Boolean data parsed from the HTTP component becomes a null value after being processed by the conditional judgment component. This occurs because the parsing process does not preserve the original data type information, and only the string-formatted description content is exported, causing the conditional judgment component to fail to recognize the boolean value.
How to confirm the configuration is correct
- Upload a single standard-format department final account report PDF, and check if the parsed knowledge base text retains the table's row and column structure and field correspondence.
- Upload an Excel template for final accounts with multiple columns, and check if the imported knowledge base entries fully cover the content of all columns.
- Upload a batch-compressed package of subordinate unit reports, and confirm that the parsing task does not trigger a timeout error.
- Test final account data containing boolean-type fields, and confirm that the parameters are not lost after being processed by the conditional judgment component.
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.