What the data for this category looks like
This data comes from EHS departments and maintenance teams of manufacturing enterprises including chemical and metallurgical facilities. Daily documents cover risk identification records, work tickets such as hot work and confined space entries, environmental monitoring records, hazardous waste ledgers, accident rectification reports, and more. Data sources include regulatory standards, online environmental monitoring equipment, gas detectors, personnel qualification lists, equipment isolation lists, and supervision platforms. Updates occur immediately after each work is completed, in real time per monitoring cycles, or during regular inspections. Document fields include work time, work type, gas concentration values, disposal volume, and other items, with dedicated units attached.
What constraints do these characteristics impose on the document parsing and chunking link
Documents in this category have significant structural differences. Some are well-formatted work ticket tables, while others are long-text monitoring records and rectification reports. When chunking, avoid splitting core related fields of work tickets, such as work location and approver information. Data from multiple sources has varying formats, so support is needed for PDF, Excel, and image format monitoring records. Parsing logic must balance semantic integrity across different document types. High-frequency update business scenarios require the parsing process to have high efficiency, to avoid delaying ledger summary due to parsing delays. The existence of dedicated fields and units requires that the field correspondence of original data be retained after parsing, with no arbitrary merging or splitting allowed.
How to set the configurations
The following configurations are formulated based on FastGPT v4.17.0.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
chunkSize | 800–1200 characters | Balances short fields in work tickets and long text in monitoring records, avoids splitting core related information from the same work ticket |
chunkSplitter | Split by title + paragraph | Adapts to structured titles and paragraph structures of work tickets and ledgers, retains document semantic integrity |
customPdfParse | Enabled | Addresses commonly seen formatted work tickets and monitoring reports in this category, prevents the default parser from losing table and field information |
PARSE_FILE_TIMEOUT_SECONDS | 120 seconds | Meets parsing duration requirements for large hazardous waste ledgers and batch work tickets, avoids parsing timeout failures |
UPLOAD_FILE_MAX_SIZE | 500 MB | Adapts to common needs of enterprises uploading batch monitoring record compression packages, covers file size limits for most business scenarios |
chunkSettingMode | Manual configuration | Documents in this category have large structural differences, manual parameter adjustment allows more precise adaptation to parsing needs for different document types |
Three common mistakes
- Scenario: When calling the create file collection API, the
customPdfParseparameter is not specified, resulting in lost table fields after parsing PDF format work tickets. Cause: The custom PDF parsing switch is not configured in the API request, and the default parsing logic is used for formatted documents. - Scenario: After uploading a PDF hot work ticket, the work location and approver information are split into different chunks. Cause: The
chunkSizesetting is too small, splitting core related paragraphs from the same work ticket. - Scenario: When uploading batch quarterly hazardous waste ledgers, parsing tasks trigger timeout errors. Cause: The
PARSE_FILE_TIMEOUT_SECONDSsetting value is lower than the actual required parsing duration, unable to complete the parsing process for large files.
How to confirm the configuration is correct
- Upload a single complete PDF hot work ticket, check if the parsed text retains all core fields including work type, work time, guardian, gas detection values, and other key details.
- Call the file collection creation API, send a request with the
customPdfParseparameter, confirm that the return result shows parsing status as successful and has no field missing prompts. - Upload a 400 MB batch environmental monitoring record compression package, confirm that the upload and parsing process does not trigger size limit or timeout error prompts.
- View the chunked document fragments, confirm that the title, approval information and work content of the same work ticket are not split into different chunks.
The values provided are common starting points and should be measured against the reader's own samples.