What this category’s data looks like
This category’s data originates from cement enterprise mining, raw material, calcination, grinding, quality control, and energy departments. It covers documents such as raw material batching plans, kiln operation records, laboratory reports, quality control notices, equipment inspection records, and energy reports. Data sources include online composition analysis systems, DCS control systems, laboratory ledgers, kiln and mill equipment sensors, raw and fuel inventory ledgers, and energy metering devices. Update frequencies cover real-time, shift-based, and daily updates. Documents include fixed fields and dynamic parameters, such as equipment runtime, raw material ratio values, and kiln temperature monitoring point data. Units include tons, degrees Celsius, cubic meters, and other standard units.
What constraints do these characteristics impose on document parsing and chunking?
Real-time updated DCS and online composition data requires parsing and chunking to support fast loading and sharding. This avoids processing timeouts caused by overly large single chunks. Mixed uploads of documents from multiple departments and types require parsing rules to adapt to different document structures. For example, short entries in inspection records and long texts in batching plans require differentiated handling. Shift-based and daily batch reports require support for batch parsing. Chunking must retain cross-document field relevance to avoid splitting critical parameters. Multi-column laboratory reports and energy reports require the parsing module to accurately identify table column structures. This prevents field misalignment. Critical clinker production parameters such as kiln temperature and ratios must retain context during chunking. This ensures subsequent audit links can associate complete logical workflows.
How to configure settings
The following configurations are formulated for FastGPT v4.17.0.
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
chunkSize | 800–1200 characters | Adapts to the length of single-segment core parameters in laboratory reports and kiln operation records, avoiding splitting critical logical units |
chunkSplitter | Split by paragraph and table boundaries | Matches the structure of multi-column reports and inspection records, retaining field relevance |
customPdfParse | Enable image embedding parsing | Adapts to documents containing kiln temperature curve screenshots and laboratory result images, fully extracting content associated with images and text |
PARSE_FILE_TIMEOUT_SECONDS | 300 seconds | Covers the parsing time of daily batch reports, avoiding parsing interruptions for large PDF files |
chunkSettingMode | Manual configuration mode | Adjust chunking rules separately for different document types, adapting to differences between raw material batching plans and inspection records |
Three common misconfigurations
- Symptom: After uploading a PDF containing kiln temperature curve screenshots, the parsing result only extracts text content with no associated image information. Cause: The
customPdfParseconfiguration item is not enabled. The default parsing rule does not activate image embedding extraction. - Symptom: After batch uploading daily energy reports, fields in some multi-column tables become misaligned. The number of columns in the parsing result does not match the original document. Cause: The
chunkSplitteris not configured to split by table boundaries. The default chunking logic mistakenly splits cross-column tables into independent paragraphs. - Symptom: After uploading a single raw material batching plan PDF larger than 100 MB, a parsing task timeout error triggers. Cause: The
PARSE_FILE_TIMEOUT_SECONDSis not adjusted to a value suitable for large files. The default timeout duration is insufficient to complete parsing.
How to confirm configurations are properly set
- Upload a single laboratory report PDF containing multi-column tables and embedded images. Verify that the parsing result fully extracts table column content and corresponding accompanying images.
- Upload batch daily energy reports. Check that chunking results retain the field relevance of each report without cross-document content confusion.
- Adjust
chunkSizeto different value ranges. Compare whether chunked text retains the contextual logic of critical parameters. - Upload a single kiln operation record PDF larger than 200 MB. Verify that the parsing task completes within the preset duration.
The values provided are common starting points and should be measured against the reader's own samples.