What the data for this category looks like
The data for this category comes from EHS departments and production maintenance teams of manufacturing enterprises across chemical, metallurgical, machinery, light industry and other sectors. Daily documents include risk identification records, work tickets for hot work, confined space work, lifting operations and similar tasks, environmental monitoring records, hazardous waste ledgers, and accident and hidden danger rectification reports. Data sources include regulatory standard documents, online environmental monitoring systems, gas detectors, personnel qualification files, equipment isolation lists and supervision platforms. Update frequencies fall into three scenarios: generated with each operation, updated in real time or per monitoring requirements, and archived through regular inspections. Documents contain both structured fields and unstructured paragraphs. Some documents include on-site photos or monitoring screenshots. Fields include content with specific units, such as operation time, gas concentration and qualification number.
Constraints for document parsing and chunking
The multi-source heterogeneous document structure, high-frequency update characteristics and business attributes of this category create clear constraints for document parsing and chunking. First, work tickets and monitoring records often include embedded images and structured tables. Parse text and associated images simultaneously to avoid missing key visual evidence from on-site operations. Second, real-time monitoring data and batch work tickets require fast parsing and chunking. Do not let parsing timeouts delay business processes. Third, retain complete boundaries for structured fields such as gas concentration values and qualification numbers. Avoid splitting key business information across chunks. Finally, format differences vary widely across document types. Adapt parsing rules for multiple formats including PDF, HTML and tables. Ensure all types of business documents can be correctly chunked.
How to configure settings
This document applies to FastGPT v4.17.0.
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
chunkSize | 800–1200 characters | Adapt to the text length of work tickets and monitoring records, avoid splitting key business fields such as risk points and monitoring values |
chunkSplitter | By paragraph + semantic boundary | Retain logical paragraphs of work steps in work tickets and rectification reports, avoid splitting risk identification entries |
customPdfParse | Enable embedded image extraction | Resolve the issue that on-site photos and monitoring data screenshots in PDFs are overlooked, matching the common text-image combined format of business documents |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Match the parsing time required for batch-uploaded work tickets and monthly hazardous waste ledgers, avoid timeout errors for large file parsing |
chunkSettingMode | Manual configuration | Adjust chunking parameters for different document types such as work tickets, monitoring reports and hazardous waste ledgers, adapting to heterogeneous data structures |
Three common configuration mistakes
- After uploading a work ticket PDF that includes on-site photos, the parsing result only returns text content. Cause: The
customPdfParseconfiguration is not enabled. The default PDF parsing logic ignores embedded images and cannot retrieve key visual evidence from the work site. - After uploading a JavaDoc-generated HTML interface document, the parsing result is empty. Cause: Parsing rules for the corresponding document type are not configured. The default parsing rules cannot recognize the tag hierarchy of structured HTML interface documents, preventing valid content from being extracted.
- After batch-uploading more than 10 monthly hazardous waste ledger PDFs, the parsing task reports a timeout error. Cause: The
PARSE_FILE_TIMEOUT_SECONDSsetting is too low, with insufficient time allocated to process large ledger documents containing multi-page tables.
How to verify correct configuration
- Upload a work ticket PDF that includes embedded on-site photos, check if the parsing result includes text descriptions or image indexes linked to the images, confirming the
customPdfParseconfiguration is active. - Upload a JavaDoc-formatted HTML interface document, check if the parsing result includes valid content such as interface fields and parameter descriptions, confirming custom parsing rules are configured correctly.
- Upload a monthly hazardous waste ledger PDF larger than 10MB, wait for parsing to complete and check for timeout errors, confirming the
PARSE_FILE_TIMEOUT_SECONDSsetting is appropriate. - Split a continuous environmental monitoring record document, check if the chunking result retains complete fields for a single monitoring data entry, confirming the
chunkSizesetting meets business requirements.
The values given are common starting points and should be measured against the reader's own samples.