What Data Looks Like for This Category
Daily documents for this category include process sheets, patterns, layout plans, cutting orders, first sample seals, process quality forms, and packaging size matching lists. Data sources include order and size charts, CAD patterns, fabric and accessory inspection records, hanging system data, needle detector data, and customer sample seal information. Data updates occur per order, per style, per batch. Most documents include fields such as size parameters, fabric direction requirements, cut piece quantity, and packaging ratio. Some pattern files exported from CAD have formats that differ from common office documents.
Constraints on Document Parsing and Chunking
Multiple document types in this category have significant structural differences. Files such as CAD patterns and layout plans use formats that differ from common office documents. Parsing must adapt to the field logic of each file type. Data updates happen frequently. Documents for a single batch of orders must be parsed and chunked quickly to avoid disrupting subsequent process handoffs. Key information such as cut piece quantity, size parameters, and fabric direction must retain full contextual association. Chunking must not split content linked across fields. Otherwise, subsequent equipment inspection and maintenance Q&A cannot match corresponding process requirements. Some documents contain graphical data. Parsing must extract both text and associated graphical information.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
chunkSize | 800–1200 characters | Adapts to the paragraph length of multi-field documents in this category, avoids splitting key process and size associated information |
chunkSplitter | Split by paragraph + semantic meaning | Adapts to structured paragraphs in documents such as process sheets and layout plans, retains contextual association across fields |
customPdfParse | Enable CAD format adaptation mode | Corrects extraction deviations of graph-associated text by general parsers for CAD-exported pattern PDF files |
UPLOAD_FILE_MAX_SIZE | 500 MB | Accommodates multiple large-size layout plans and pattern files included in a single batch of orders, prevents upload interception |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Adapts to the parsing duration of batch process sheets with hundreds of pages, avoids timeout errors triggered by oversized files |
chunkSettingMode | Custom mode | Switches chunking rules for different document types, adapts to structural differences between process sheets and packaging size matching lists |
Three Common Configuration Mistakes
- Symptom: An error is triggered when using doc2x to parse a hundreds-page layout plan PDF. Files with tens of pages parse normally. Cause: The
PARSE_FILE_TIMEOUT_SECONDSparameter is not adjusted. Large file parsing time exceeds the default threshold, triggering timeout interruption. - Symptom: Locally deployed FastGPT v4.17.0 cannot enable the file parsing function. Cause: Dependencies for
customPdfParseare not configured correctly, or corresponding port permissions are not opened. - Symptom: After enabling pdf-marker, parsing of large-size process sheets hangs waiting for results and fails to complete. Cause: No parsing task queuing mechanism is set. Multiple tasks submitted simultaneously exhaust resources, preventing timely return of parsing results.
How to Verify Proper Configuration
- Upload a single 500-page process sheet PDF, check if parsing completes within 600 seconds with no timeout errors.
- Upload a CAD-exported pattern file, verify that the parsed result retains associated content for key fields such as fabric direction and cut piece quantity.
- Submit multiple documents of different types, confirm that parsing tasks execute in sequence with no task backlog or unresponsive status.
- Adjust the
chunkSizeparameter, verify that chunking results do not split process paragraphs corresponding to the same size, and meet chunking logic requirements.
The values provided are common starting points and should be evaluated against the reader's own samples.