What this category of data looks like
Documents and materials in the coal chemical industry primarily originate from production operation logs, safety operation procedures, environmental impact assessment filing documents, equipment maintenance records, and project feasibility study reports. Data update frequency varies by document type: operation logs are updated per shift, procedure documents are updated annually or after major technical renovations, and project documents are updated phase-by-phase as projects progress. Most documents include fixed fields such as equipment number, process parameters, and timestamps. Some documents contain large numbers of embedded tables and structured data, using industrial standard units including tons per hour, megapascals, and cubic meters. Long text paragraphs mostly focus on process details and safety regulations.
What constraints do these characteristics impose on the document parsing and chunking process?
Coal chemical industry documents with large numbers of embedded tables and structured data will break the relational links between table rows and columns when using default text chunking logic. This causes parsed data to fail to restore original business logic. Long text paragraphs about process details require retained contextual connections. Chunks that are too short will disrupt the coherence of process steps, while chunks that are too long will introduce irrelevant information and increase retrieval redundancy. Parameter fields with industrial units must be bound to their corresponding descriptions. Accidental splitting of parameters and units during chunking will prevent subsequent retrieval from matching complete business information. Shift-updated operation logs contain large numbers of repeated equipment number fields. Chunking must avoid embedding repeated content multiple times in vectors, which reduces retrieval accuracy.
How to configure the settings
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
chunkSize | 800–1200 characters | Coal chemical documents mostly contain coherent process description paragraphs. This range retains contextual connections while controlling the information density of each chunk |
chunkSplitter | Split by paragraph + table boundaries | Adapts to coal chemical documents with large numbers of embedded material balance tables and energy consumption statistics tables, avoiding splitting the row and column relational structures of tables |
customPdfParse | Enabled | Documents such as procedures and environmental impact assessment files in the coal chemical industry are mostly formatted PDF documents. Enabling this setting retains original typesetting and table integrity |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Large feasibility study reports and monthly production reports take a long time to parse. This duration covers the complete parsing process |
chunkSettingMode | Manual configuration | For the structured characteristics of coal chemical documents, manually adjusting chunking rules better aligns with business data logic than automatic mode |
Three common misconfigurations
- Symptom: Knowledge base search tests fail to match target process parameter content. Cause: Chunking accidentally splits parameters and their corresponding units, resulting in incomplete information embedded in vectors. Retrieval cannot match complete business keywords.
- Symptom: After uploading multiple coal chemical industry documents, parsed results cannot distinguish content blocks from corresponding files. Cause: File metadata binding configuration is not enabled. Chunking does not carry identification fields such as file name and document type, leading to mixed results.
- Symptom: Timeout errors occur when parsing large equipment operation logs. Cause: The
PARSE_FILE_TIMEOUT_SECONDSparameter is not adjusted. The default duration is insufficient to complete full parsing of large log files.
How to confirm correct configuration
- Upload a coal chemical PDF document with tables, check parsed chunked content to confirm table structures are not split.
- Initiate a knowledge base search test, input complete process parameter and unit combinations, confirm that corresponding chunked content can be matched.
- Upload multiple different types of coal chemical documents, check metadata identifiers in chunked results to confirm each content block corresponds to the correct source file.
- Upload a single large operation log, confirm that no timeout errors occur during the parsing process.
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.