What This Category's Data Looks Like
Typical entities for this category include cement plant mining, raw material preparation, calcination, grinding, quality control, and energy departments. Daily documents include raw material batching plans, kiln operation logs, laboratory test reports, quality control notices, equipment inspection records, and energy reports. Data sources cover online composition analysis, DCS systems, laboratories, kiln and grinding equipment, raw and fuel ledgers, and energy metering devices. Data update frequencies fall into three categories: real-time, per shift, and daily. Document structures include structured tables and non-pure text records. Fields include batching ratios, test values, operating parameters, and more. Corresponding units include tons, kilograms, degrees Celsius, hours, and others.
What Constraints Do These Characteristics Impose on the "Document Parsing and Chunking" Link
The multi-source, mixed update frequency, and diverse document type characteristics of this category create multiple constraints for document parsing and chunking. Real-time DCS logs and shift-based inspection records have large differences in update frequency. Different chunking granularities are needed to match the timeliness requirements of audits. Structured laboratory reports and batching plans have obvious format differences from unstructured kiln operation logs. Parsing needs to balance retaining table layout and connecting text context. Documents from cross-system sources have inconsistent fields. Chunking must retain associated context across documents to avoid breaking the complete logical chain required for quality audits. Additionally, quality audits for this category have high requirements for data accuracy. Chunking errors may cause critical parameters to be truncated, affecting subsequent audit judgments.
How to Set the Configurations
The following configurations are based on FastGPT v4.17.0.
| Configuration Item | Recommended Approach | Rationale |
|---|---|---|
chunkSize | 800–1200 characters | Adapts to documents with tables such as raw material batching plans and laboratory reports. Retains context for critical parameters including clinker strength and batching ratios, and avoids breaking at indicators that impact quality judgments |
chunkSplitter | Split by paragraph + header | Balances parsing for structured tables and unstructured operation records, and retains the integrity of table fields and paragraph logic |
customPdfParse | Enabled | Adapts to PDF documents of laboratory reports and batching plans that contain complex embedded tables, and retains original layout and field associations |
UPLOAD_FILE_MAX_SIZE | 1000 MB | Adapts to batch upload requirements for cumulative single-shift kiln operation records, and avoids large file upload failures |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Adapts to parsing duration for large DCS log files, and avoids interrupting the parsing process due to timeout |
chunkSettingMode | Manual mode | Supports adjusting chunking rules for different document types such as inspection records and laboratory reports, and adapts to multi-source data formats |
Three Common Errors
- Phenomenon: After uploading an Excel-format raw material batching plan, parsing results show missing fields or layout chaos. Cause: Structured file parsing rules are not configured, and format-specific extraction adapters are not enabled, resulting in incomplete parsing of table content.
- Phenomenon: A timeout error is displayed in the interface when parsing a single large kiln operation record PDF. Cause: The value set for
PARSE_FILE_TIMEOUT_SECONDSis lower than the actual parsing duration, or the single file exceeds theUPLOAD_FILE_MAX_SIZElimit. - Phenomenon: Chunking results split the free calcium test value in a laboratory report and subsequent strength judgment basis into different chunks. Cause:
chunkSizeis set too small, and thechunkSplitterrule for splitting by paragraph and header is not enabled, resulting in truncation of key associated content.
How to Confirm Proper Configuration
- Upload a single raw material batching plan PDF, and check if the parsing result retains complete fields including batching ratios and raw material sources, with no layout chaos.
- Upload a single-shift equipment inspection record, and confirm that the chunking results do not truncate critical operating parameters and inspection conclusions, with coherent paragraph logic.
- Upload a DCS log file under 100 MB, and confirm that the parsing process does not trigger timeout prompts, and the chunking granularity adapts to the audit requirements of real-time data.
- Switch
chunkSettingModeto automatic mode, compare the chunking results with manual mode, and confirm that it can adapt to parsing requirements for multiple document types.
The values given are common starting points and should be measured against the reader's own samples.