What the data for this category looks like
Core data for continuous basic chemical production comes from DCS/SIS systems, online analyzers, LIMS systems, equipment condition monitoring modules, energy metering systems, and raw material tank data. Daily documents include operating procedures, process index cards, DCS trend charts, laboratory reports, interlock bypass records, special work permits, and shift logs. Data update rhythms fall into three tiers: real-time, per-shift, and daily. Real-time data includes DCS trends and online analyzer readings. Per-shift data includes shift logs and work permits. Daily data includes laboratory reports. Document fields cover physical quantities such as pressure, temperature, and flow, with corresponding units including MPa, ℃, m³/h, and others. Some structured documents use fixed layout formats.
What constraints do these characteristics impose on the document parsing and chunking link?
The data characteristics of this category create multiple constraints for the document parsing and chunking process. Documents from multiple sources with different update rhythms need compatible parsing trigger rules to avoid conflicts between high-frequency real-time data and batch static documents. Structured documents such as process index cards and LIMS laboratory reports have fixed fields and layouts. When chunking, field associations must be retained, and key parameter groups cannot be split. Large volumes of shift logs and work permit documents require batch parsing support. Reasonable timeout and chunking thresholds must be set to prevent parsing interruptions. Quality traceability for continuous production relies on complete process context. Chunking must not disrupt the continuous expression of interlock logic or process steps.
How to set the configuration
This configuration applies to FastGPT v4.17.0.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
chunkSize | 800–1200 characters | Adapts to the field length of process index cards and laboratory reports, avoids splitting key parameter groups |
chunkSplitter | Split by paragraph + heading | Matches the hierarchical structure of operating procedures and interlock bypass records, retains context associations |
customPdfParse | Enable structured parsing | Adapts to the fixed layouts of DCS trend charts and shift logs, extracts traceable structured fields |
UPLOAD_FILE_MAX_SIZE | 1000 MB | Accommodates single-batch DCS trend history files, prevents upload interruptions |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Adapts to the parsing time of long-cycle DCS trend files, prevents task termination due to timeout |
chunkSettingMode | Manual configuration | Adjust chunking parameters for different document types to meet batch parsing requirements |
Three common mistakes
- Symptom: Large-volume document uploads are interrupted mid-process, and parsing cannot be resumed after restarting the container. Cause:
UPLOAD_FILE_MAX_SIZEandPARSE_FILE_TIMEOUT_SECONDSwere not adjusted. Parsing processes exit abnormally after exceeding configuration thresholds, and no parsing breakpoints are retained. - Symptom: No parsing results are returned after uploading files via the dialog box, and no error logs appear in the background. Cause:
customPdfParsewas not enabled. The structured format of DCS trend charts cannot be recognized, and no valid content chunks are generated after parsing. - Symptom: System memory usage spikes immediately after a PDF parsing task is triggered. Cause:
chunkSizewas not limited. Oversized chunks cause memory usage during embedding model loading to exceed the system reserved threshold.
How to confirm the configuration is correct
- Upload a single DCS trend PDF containing pressure and temperature parameters, verify that parsed chunks retain parameter association relationships under the same working condition.
- Upload 10 or more shift log documents, confirm that all tasks complete parsing, and no abnormal records of timeouts or upload failures appear in the background logs.
- Adjust
chunkSizeto the 600-character and 1000-character ranges, verify that the continuous expression of process steps is fully retained in the chunked content with no splitting errors. - Test uploading a single document via the API, confirm that the chunked content can be properly added to the knowledge base with no format errors.
The values provided are common starting points and should be measured against the reader's own samples.