What the Data for This Category Looks Like
Coal mine production ledger data primarily comes from underground work shift logs, electromechanical equipment operation reports, ventilation safety monitoring ledgers, and on-site safety inspection records. Data is updated per production shift, with multiple structured documents generated daily. Most documents use tables with fixed headers, containing fields such as equipment number, operating duration, gas concentration, inspection date, and more. Units include hours, ppm, cubic meters, and some documents include on-site photos and handwritten annotations.
Constraints Imposed on Document Parsing and Chunking
Structured ledgers with fixed headers require parsing to preserve the correspondence between fields and values, to avoid field misalignment after chunking. High-frequency shift ledgers create demand for batch document processing, so single-task parsing duration must be controlled. Recognition of specialized units such as ppm and cubic meters requires adaptation to technical terminology; general-purpose parsing models often produce recognition errors. Embedded handwritten annotations and on-site photos require the parsing step to support content extraction from mixed-format documents, to avoid losing non-table supplementary information.
Configuration Settings
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
chunkSize | 800–1200 characters | Coal mine ledgers are mostly a mix of structured tables and short text. This range ensures a single chunk contains a complete field group, avoiding field breakage after splitting |
chunkSplitter | Split by paragraph and table boundaries | Adapts to the alternating structure of tables and text descriptions in ledgers, avoiding chunking across tables or paragraphs |
customPdfParse | Enable specialized coal industry mode | Adapts to technical terminology and handwritten annotations in coal mine ledgers, improving recognition accuracy for non-standard format content |
PARSE_FILE_TIMEOUT_SECONDS | 120 seconds | Single ledger documents contain multiple pages of data. Extending the timeout duration avoids parsing interruptions for large files |
UPLOAD_FILE_MAX_SIZE | 500 MB | Supports batch uploading of multiple monthly ledger documents, adapting to batch summary requirements |
chunkSettingMode | Manual configuration | Adjust chunking parameters for different types of ledger documents such as equipment ledgers, safety ledgers, to ensure compatibility |
Three Common Configuration Errors
- After uploading ledger files, the parsing node has no response, and the status shows timeout. The cause is failure to adjust the
PARSE_FILE_TIMEOUT_SECONDSparameter; the parsing duration of a single multi-page ledger exceeds the default threshold. - Parsing results only capture some table fields, with misaligned field and value correspondences. The cause is failure to enable the specialized mode in
customPdfParse; general-purpose parsing cannot adapt to the specialized field format of coal mine ledgers. - After batch uploading multiple ledgers, only some files are parsed. The cause is failure to adjust
UPLOAD_FILE_MAX_SIZE; large-volume monthly summary ledgers exceed the default upload limit.
How to Verify Proper Configuration
- Upload a standard coal mine equipment ledger document, and review the parsing results to confirm all headers and values are correctly extracted.
- Check the parsing logs to confirm the
PARSE_FILE_TIMEOUT_SECONDSparameter is active, with no timeout error records. - Test batch uploading multiple ledger documents of different types, and confirm all files are properly parsed and enter the chunking step.
- Manually adjust the
chunkSizeparameter, compare chunking results across different values, and confirm a single chunk contains a complete field group.
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.