What data for this category looks like
The data for coal chemical industry intelligent due diligence reports primarily comes from public industry statistical bulletins, annual disclosure documents of coal processing enterprises, environmental impact assessment approval public notices, and capacity verification reports. There are two update cycles: regular industry data is updated quarterly or annually, while due diligence documents for individual projects are updated only once when the project is approved or put into operation. Most documents follow a fixed structure: basic project information, raw coal quality parameters, production process parameters, capacity scale, environmental protection indicators, and financial calculation summaries. Some documents include structured supplementary tables with continuous numeric fields, with units including ten thousand tons per year, cubic meters per hour, mass percentage, and others.
What constraints do these characteristics impose on the "document parsing and chunking" link
The multi-module structure of coal chemical due diligence reports requires precise identification of chapter boundaries during parsing, to avoid semantic fragmentation caused by cross-module chunking. Documents contain a large number of numeric fields with varied units, so the correspondence between fields and units must be preserved. Otherwise, complete business information cannot be restored after chunking. Some documents include structured supplementary tables; if the table structure is not retained during parsing, scattered numeric data cannot be linked. Public documents have inconsistent formats, including scanned copies and encrypted content, which increases adaptation difficulty for the parsing stage. The differing update cycles of different documents require that associated timestamp information be retained during chunking, to ensure timely matching for subsequent retrieval.
How to set the configurations
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
PARSE_MODE | auto | Adapts to the varied PDF and Word formats of coal chemical due diligence reports, automatically matching the appropriate parsing logic |
CHUNK_SIZE | 800–1200 characters | Covers the complete semantics of long paragraph process descriptions and numeric tables, avoiding business logic fragmentation after chunking |
CHUNK_OVERLAP | 100–150 characters | Retains contextual association between adjacent chunks, ensuring continuity of cross-chapter process information |
PARSE_TABLE_ENABLE | true | Retains the complete structure and field correspondence of structured supplementary tables in coal chemical due diligence reports |
PARSE_SCAN_ENABLE | Set based on actual measurement | Adapts to due diligence documents in scanned copy format, requiring adjustment based on the actual scan quality of documents |
PARSE_FILE_TIMEOUT_SECONDS | 300 seconds | Adapts to long-form due diligence reports, ensuring complete parsing of multi-page supplementary tables |
The parameter values provided on this page are conventional recommendations used as a starting point for configuration. Actual values are affected by material format, data volume, and business rules. Specific issues require individual analysis, and it is recommended to test on your own samples before finalizing settings.
Three common mistakes
- Uploading non-standard documents with modified file extensions results in no parsing output. The cause is that parsing adaptation for the corresponding non-standard format is not enabled. FastGPT matches parsing logic via file extensions, and modifying the extension cannot trigger the correct parsing process.
- Using chunk mode to call the pushdata API for upload results in long-term display of "indexing". The cause is that chunking parameters are set beyond the system processing threshold, leading to indexing task backlog, or that automatic indexing trigger conditions after chunking are not configured.
- Image association information is missing from parsed document content. The cause is that image parsing configuration is not enabled, or images in the document are scanned copies and the OCR parsing switch is not turned on.
How to confirm the configuration is correct
- Upload a typical coal chemical industry due diligence report document, check the parsed text content, and confirm whether chapter boundaries and the association between fields and units are complete.
- Call the document parsing interface, check whether the returned chunked data retains the complete structure of structured supplementary tables, to verify that the table parsing configuration is effective.
- Check the task execution logs, confirm that no timeout errors occurred during the parsing and chunking process, to verify that the timeout parameter setting adapts to the document length.
- Upload a due diligence report in scanned copy format, confirm that the OCR parsing result can be read normally, to verify that the scan parsing configuration is correct.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-09-14.