What the Data for This Category Looks Like
Documents for internal office and employee services in the coal chemical industry mainly come from production shift reports, equipment operation and maintenance manuals, safety operation procedures, employee training materials, attendance and salary documents, and similar sources. The update rhythm varies significantly: production reports are updated daily, safety procedures are revised quarterly, and equipment manuals are updated alongside equipment technical upgrades. Most documents are in long text format. Some include structured tables and specialized terminology tags. Fields include equipment numbers, inspection cycles (unit: hours), safety thresholds (unit: MPa), and other industry-specific content.
What Constraints These Characteristics Impose on Document Parsing and Chunking
The high proportion of long text means chunks cannot be too short or too long, to avoid breaking the contextual links of specialized terms. The presence of structured tables requires the parsing step to retain the full table structure and field units, to prevent data disorder after splitting. Differences in update rhythms across documents mean parsing nodes must adapt to both one-time uploaded temporary documents and batch-updated bulk documents. The high number of industry-specific terms means chunks should avoid truncating terms, to ensure subsequent processing steps can accurately identify relevant content.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
chunkSize | 1000–1500 characters | Most internal documents for coal chemical industry are long-form production procedures and equipment manuals. This range balances context integrity and chunk granularity, and avoids truncating specialized terminology |
chunkSplitter | Split by paragraph + heading | Internal documents often have hierarchical headings such as shift procedures and equipment chapters. Splitting by headings preserves the logical structure of documents, and prevents splicing of content across chapters |
customPdfParse | Enable table retention mode | Internal documents include structured content such as material lists and inspection record sheets. Enabling this mode fully extracts table fields and units, and prevents table disorder after parsing |
UPLOAD_FILE_MAX_SIZE | 2000 MB | Single files such as coal chemical industry equipment manuals and annual safety reports have large file sizes. This upper limit covers the upload needs of most internal documents |
PARSE_FILE_TIMEOUT_SECONDS | 300–600 seconds | Parsing large PDF documents takes a long time. This timeout range prevents mid-parsing interruptions for large files, and adapts to the processing rhythm of long documents for coal chemical industry |
chunkSettingMode | Manual configuration | Internal office documents have large format differences. Manual configuration allows adjusting chunking rules for different document types, and adapts to multi-scenario needs |
Three Common Mistakes
- Phenomenon: After server deployment, uploading a file triggers a 404 error during parsing, and file content cannot be read. Cause: The server-side file upload directory permissions are not configured correctly, or the front-end upload path does not match the file reading path of the FastGPT parsing node, causing the parsing node to fail to locate uploaded PDF and DOCX files.
- Phenomenon: Specified response fields cannot be extracted from parsed documents. Cause: The structured content retention mode of
customPdfParseis not enabled, causing tables and specialized terminology fields to be split or lost, and preventing subsequent processing steps from correctly identifying them. - Phenomenon: Parsing of large documents is interrupted mid-process due to timeout. Cause: The value set for
PARSE_FILE_TIMEOUT_SECONDSis too low, and does not adapt to the parsing time requirements of long coal chemical industry documents.
How to Confirm the Configuration Is Correct
- Confirm that the currently running FastGPT version is v4.17.0, to avoid configuration ineffectiveness caused by version differences.
- Upload a single coal chemical industry equipment manual with more than 1000 pages, and check that the parsing task completes within 300–600 seconds, with no timeout errors.
- Upload a DOCX document containing a material list table, and confirm that the parsed chunks retain the complete table structure and unit fields.
- After deploying to the server, upload a test file, and check that the parsing node returns no 404 errors for the file content, and that the content can be read normally.
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.