What this category's data looks like
Core data for this category originates from design history files, device and material batches, MES systems, clean environment monitoring equipment, sterilization equipment, and inspection and calibration systems. Daily documents include production process specifications, batch production records, clean zone records, sterilization batch records, inspection reports, software version records, adverse event and traceability materials. Update frequency follows per batch or per produced device, or aligns with the environmental monitoring plan. Documents contain multi-column tables and scanned content embedded in text. Fields include unique device identification (UDI), batch numbers, sterilization temperature, clean zone differential pressure, and others. Units include degrees Celsius, pascals, batch numbers, and dates.
Constraints on Document Parsing and Chunking
Data sources for this category are scattered and have diverse formats. Documents exported from multiple systems use different layout standards, requiring precise matching of structural features across different document types. Multi-column clean zone records and batch records often suffer from cross-column data fragmentation, requiring multi-column text merging processing. Key fields such as UDI and sterilization parameters must be bound to corresponding batch information. Chunking logic must retain the associative relationships between fields. High-frequency updated single-batch documents require the parsing process to quickly adapt to single-batch data, avoiding damage to batch and parameter binding logic from overly large or small chunks. Documents with embedded scanned content must support OCR parsing to ensure accurate extraction of unstructured text.
Configuration Settings
These configurations are compatible with FastGPT v4.17.0.
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
chunkSize | 800–1200 characters | This category's documents contain multi-column tables and key fields such as UDI and sterilization parameters. Excessively large chunks will lose field associations, while excessively small chunks will damage the integrity of process steps |
chunkSplitter | Paragraph + semantic boundary | Production ledgers include structured process specifications, semi-structured batch records, and other content. Semantic boundary chunking retains the associative logic of batches and parameters |
customPdfParse | Enable multi-column text merging | Clean zone records and inspection reports often use multi-column layouts. This prevents cross-column data from being fragmented during parsing |
PARSE_FILE_TIMEOUT_SECONDS | 300–600 seconds | Single-batch sterilization batch records and adverse event traceability materials may contain multiple pages of scanned content, requiring sufficient parsing time |
chunkSettingMode | Manual configuration | Document formats vary widely across this category. Manual adjustment of chunking parameters adapts to the extraction accuracy of key fields such as UDI and batch numbers |
Three Common Mistakes
- Symptom: After parsing multi-column clean zone records, cross-column batch numbers and differential pressure data are misplaced or missing. Cause: Multi-column text merging configuration for
customPdfParseis not enabled. The default parsing logic splits content based on page flow, breaking cross-column data associations. - Symptom: After uploading a single-batch sterilization batch record PDF, the parsing task times out and fails. Cause:
PARSE_FILE_TIMEOUT_SECONDSis not adjusted to a reasonable range. The default timeout duration is insufficient to process large documents containing multiple pages of scanned content. - Symptom: The model output only includes PDF text content, and does not synchronize embedded sterilization parameter image descriptions. Cause: Associated image text extraction logic is not configured. Only plain text content is extracted, without associating annotation information attached to images.
How to Verify Proper Configuration
- Upload a clean zone record document containing multi-column tables, and check if parsed chunks fully retain cross-column batch numbers and monitoring data.
- Upload a sterilization batch record containing multiple pages of scanned content, and confirm that the parsing task completes within 600 seconds with no timeout errors.
- Upload an inspection report containing embedded images, and check if the output content includes parameter description text attached to the images.
- Extract chunked content, and confirm that key fields such as UDI and sterilization temperature are not split into unrelated chunks.
The values provided are common starting points and should be measured against the reader's own samples.