What the Data for This Category Looks Like
This category of data comes from DCS/APC control systems, LIMS laboratory systems, tank farm metering systems, crude oil evaluation databases, equipment management systems, and energy management systems. Daily generated documents include operating procedures, production plans, material balance reports, distillation outlet quality reports, interlock ledgers, shift handover records, and change management documents. Data update frequencies cover real-time, per-shift, and daily. Most documents contain fields such as process parameters, material indicators, and equipment status, with clear unit annotations such as temperature, flow rate, and distillation range values.
What Constraints Do These Characteristics Impose on the Document Parsing and Chunking Link
Multi-source heterogeneous data sources create mixed format issues. Both structured reports and unstructured documents are present, so parsing logic must adapt to different file types. Real-time and high-frequency updated data require parsing processes with low latency. This prevents parsing timeouts from affecting subsequent audit links. Documents contain a large number of process parameters and interlock thresholds with units. Chunking must retain the association between fields and units to avoid broken parameter explanations. Multi-device coupled business logic requires chunked content to retain cross-document connection clues. This avoids splitting process links.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
chunkSize | 800–1200 characters | Adapts to the paragraph length of process parameters with units in refinery documents, avoids splitting associated fields |
chunkSplitter | By paragraph and semantic boundary | Adapts to natural segmentation of unstructured documents such as shift handover records and operating procedures, retains complete process logic |
customPdfParse | Enabled | Used to parse encrypted or complexly formatted interlock ledgers and change management documents, adapts to multi-page tables and embedded charts |
UPLOAD_FILE_MAX_SIZE | 1000 MB | Supports importing large crude oil evaluation database files and multi-device combined reports |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Addresses parsing time for large structured reports, prevents task interruptions from timeouts |
chunkSettingMode | Manual configuration | Adjusts chunking rules for different document types such as Excel reports and PDF process procedures to adapt to multi-source data formats |
Three Common Mistakes
- Phenomenon: After importing an Excel file, sheet names cannot be retrieved, and the parsing result only contains the content of the default first worksheet. Cause: No parsing rule for multi-sheet documents is configured. The system parses only the first sheet by default.
- Phenomenon: When importing a PPT or DOC document, enabling the PDF enhancement feature produces no parsing effect. Cause: The PDF enhancement feature only applies to PDF format files, and does not work across formats.
- Phenomenon: After importing an Excel file into the knowledge base, only two columns of data are recognized, and complete table content cannot be read. Cause: The default CSV compatibility mode is not disabled. This mode limits the number of identifiable columns.
How to Confirm Proper Configuration
- Upload a single Excel report with multiple sheets. Check if the parsing result includes the names and corresponding content of all sheets.
- Upload a PDF-format interlock ledger file. Confirm that the parsed result retains the parameters and unit annotations in the table, with no content splitting.
- Upload a large crude oil evaluation database file of approximately 100 MB. Confirm that the parsing process does not trigger a timeout error.
- View the parsing logs of FastGPT v4.17.0. Confirm that the chunk length falls within the preset
chunkSizerange.
The values provided are common starting points and should be measured against the reader's own samples.