What the data for this category looks like
Manufacturers of cabinet chassis, ventilation equipment, electrical cabinets, and non-standard equipment form the core entities of this category. Daily generated documents include 3D part unfolding drawings, CNC cutting programs, bending process cards, nesting diagrams, first-piece records, and process flow cards. Data is sourced from CAD/CAM software, order BOMs, sheet metal inventory systems, laser cutters, bending machines, and MES systems. Update frequency is triggered by orders, daily cycles, or each production changeover. Most documents contain professional fields such as bending coefficients, hole position dimensions, process sequences, and sheet metal specifications. Common units include millimeters and kilograms, standard in machining operations.
Constraints imposed on the document parsing and chunking workflow
Documents from multiple sources have significant format differences. CAD-exported unfolding drawings use vector formats. Bending process cards are mostly PDF documents with tables. Parsing logic must be adapted to extract content from different formats. Update frequencies tied to orders, daily cycles, or production changeovers require parsing tasks to align with production rhythms, to avoid blocking workflows. Single document size varies widely, ranging from a few pages of first-piece records to hundreds of pages of nesting diagrams. This requires flexible adjustment of chunking and timeout settings. Professional fields such as bending compensation coefficients and cutting allowances must be accurately bound, to avoid splitting critical parameter combinations during chunking.
How to set configurations
This guidance is based on FastGPT v4.17.0.
| Configuration Item | Recommended Range | Rationale |
|---|---|---|
chunkSize | 800–1200 characters | Adapts to process cards and nesting diagrams with tables in sheet metal documents, avoids splitting critical parameter rows |
PARSE_FILE_TIMEOUT_SECONDS | 300–600 seconds | Matches parsing time for hundreds of pages of nesting diagrams, avoids timeout errors for large files |
UPLOAD_FILE_MAX_SIZE | 1000 MB | Accommodates large nesting diagrams and multi-page unfolding drawing collections, meets production document storage needs |
customPdfParse | Enable pdf-marker adaptation mode | Improves parsing accuracy for tables and vector elements in bending process cards |
chunkSplitter | Split by paragraph + table boundaries | Avoids splitting bending processes and their corresponding process parameters into different chunks |
chunkSettingMode | Manual configuration | Adapts chunking needs for different document types, matches production characteristics of multi-variable, small-batch production |
Three common configuration mistakes
- Symptom: Timeout error triggers when parsing hundreds of pages of nesting diagrams, and task status shows failure. Cause:
PARSE_FILE_TIMEOUT_SECONDSwas not adjusted to a higher value. Default duration is insufficient for full parsing of large sheet metal documents. - Symptom: After local deployment of pdf-marker, a Cannot read properties of undefined error occurs during parsing of large-volume sheet metal PDF documents. Cause: Insufficient memory resources were configured for large drawing parsing, or the deployed version does not match the FastGPT version.
- Symptom: When parsing bending process cards, bending coefficients and their corresponding processes are split into different chunks. Cause: Chunking rules for splitting by paragraph + table boundaries were not enabled, and content was only truncated by character count.
How to confirm configurations are correct
- Upload a typical sheet metal nesting diagram, verify that parsed chunks retain complete tables and parameter combinations.
- Review system logs to confirm no timeout errors occur during parsing of large-volume documents.
- Test different types of sheet metal documents, including unfolding drawings and process cards, to confirm proper parsing format adaptation.
- Check the file upload limit, confirm that maximum-volume production documents can be uploaded.
The values provided are common starting points and should be measured against the reader's own samples.