What Data for This Category Looks Like
This category of data originates from cement enterprise mining, raw material, calcination, grinding, quality control, and energy departments. It covers raw material batching plans, kiln operation logs, laboratory reports, quality control notices, equipment inspection records, and energy reports. Data sources include online composition analysis systems, DCS control systems, laboratories, kiln and grinding equipment, raw and fuel ledgers, and energy metering devices. Update frequencies cover real-time, shift-based, and daily updates. Most documents use structured formats, with fields such as raw material ratio values, kiln temperature, material flow rates, and test indicator values. Units include degrees Celsius, tons per hour, hours, and others.
What Constraints Do These Characteristics Impose on Document Parsing and Chunking?
The multi-source and heterogeneous document characteristics of this category create multiple constraints for parsing and chunking. First, data with update frequencies spanning real-time, shift-based, and daily updates requires matching chunk granularities to avoid over-splitting real-time data or merging low-frequency reports into overly long chunks. Second, a large number of structured documents such as batching plan tables and laboratory report tables require accurate retention of cell-to-cell associations to prevent disordered table content after parsing. In addition, specific fields including kiln temperature, feed rate, and strength indicators must be bound to their corresponding units. The corresponding logic between fields and units must not be broken during chunking. At the same time, document formats vary significantly across different departments, so adapted chunking rules are needed to ensure key traceability information is not lost.
Configuration Settings
This configuration is based on FastGPT v4.17.0, adapted to the document characteristics of the cement clinker and grinding category. The specific configuration items are as follows:
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
customPdfParse | Enabled | Most documents in this category contain structured tables and complex layouts. Enabling this option improves parsing accuracy for table content and field associations, ensuring complete data required for traceability |
chunkSize | 800–1200 characters | Balances the information density of laboratory reports and kiln operation logs, avoiding overly fine splitting of key traceability information or overly long chunks that harm retrieval accuracy |
chunkSplitter | Split by paragraph and table boundaries | This category of documents contains a large number of shift-recorded paragraphs and structured tables. Preserving boundaries ensures the integrity of operational logic and table content |
PARSE_FILE_TIMEOUT_SECONDS | 300–600 seconds | Parsing large kiln operation logs and batch laboratory reports takes a long time. This range prevents parsing failures caused by timeout interruptions |
UPLOAD_FILE_MAX_SIZE | 1000 MB | Single files of enterprise archived monthly energy reports and equipment inspection archives are large in size. This setting adapts to the demand for uploading and parsing large files |
chunkSettingMode | Manual configuration | Document formats vary significantly across different departments in this category. Manual adjustment allows adapting chunking rules for different types of documents such as raw material batching plans and laboratory reports |
Three Common Misconfigurations
- Symptom: Some table fields in laboratory reports are empty after enabling
customPdfParse. Cause: Adaptation rules for enhanced parsing have not been configured for the dedicated table formats of the cement clinker category, leading to failure to parse specific table headers. - Symptom: Incomplete kiln operation record paragraphs appear in knowledge base retrieval results. Cause: The
chunkSizesetting is too small, splitting a single shift’s continuous operation records into multiple chunks and losing operational logic associations. - Symptom: Parsing tasks time out when uploading monthly energy reports in bulk. Cause:
PARSE_FILE_TIMEOUT_SECONDSis set to 120 seconds, which does not adapt to the parsing time requirements of large archived files.
How to Confirm Proper Configuration
- Upload a single typical laboratory report, check the parsed text structure, and confirm that table content is complete and fields and units are not lost.
- Upload a single kiln operation record, verify that the chunked content retains the logical association of continuous operations, with no unnecessary paragraph splits.
- Upload a single large archived file, confirm that no timeout prompt appears for the parsing task and that parsing completes normally.
- Test uploading a mix of multiple document types, verify that chunking rules for different documents all take effect as configured.
The values provided are common starting points and should be measured against the reader's own samples.