What the Data for This Category Looks Like
Daily documents from spinning and weaving enterprises typically include cotton blending or ingredient lists, process setup sheets, equipment operation records, yarn inspection reports, grey fabric inspection reports, defect records, and similar materials. Data sources cover raw fiber inspection reports, ERP systems, spinning and loom operation data, evenness testers, fabric inspection machine collected data, and order specification documents.
Data update frequency changes based on raw material batches, team shifts, and fabric roll counts. Single documents contain both structured parameters and free-text descriptions. Fields include fiber indicators, twist, weaving structure, defect types and quantities, and some fields use dedicated units.
What Constraints Do These Characteristics Impose on Document Parsing and Chunking
Multi-source heterogeneous data formats require flexible parsing rules to avoid breaking the associativity of structured fields. High-frequency updated batch documents need efficient parsing and chunking workflows to prevent task backlogs.
Short texts and repeated descriptions in defect records require retaining contextual connections during chunking, to ensure complete defect generation scenarios can be traced during audits. Accurate identification of dedicated fields and units directly impacts the effectiveness of subsequent inspection and audit work. Chunking logic must avoid breaking the binding relationship between fields and their corresponding descriptions.
How to Configure
This configuration is based on FastGPT v4.17.0, adapted to the document parsing and chunking needs of spinning and weaving scenarios:
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
chunkSize | 800–1200 characters | Adapted to documents mixing structured parameters and defect descriptions, to avoid splitting that breaks the contextual associativity of process logic |
chunkSplitter | Split by paragraph + punctuation | Aligns with the natural segmentation habits of process sheets and inspection records, preserving complete logic of operation procedures and problem descriptions |
customPdfParse | Enabled | Adapted to formatted PDF documents exported from ERP systems, preserving the recognizability of tables, field layouts, and embedded images |
UPLOAD_FILE_MAX_SIZE | 1000 MB | Adapted to the total size of multiple documents corresponding to a single batch of raw materials, to prevent upload tasks from failing due to volume limits |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Addresses batch parsing scenarios for multiple documents corresponding to a single batch of raw materials, to prevent timeout failures due to excessive task volume |
chunkSettingMode | Manual configuration | Adjust chunking parameters separately for different document types, to adapt to format differences across multiple data sources such as inspection records and defect logs |
Three Common Mistakes
- Uploading non-standard format documents with modified file extensions results in no parsing output. The cause is that custom parsing adaptation is not enabled; relying only on default rules cannot recognize the structured content of the document.
- Uploading data in chunk mode results in long-term display of "indexing". The cause is that the
chunkSizesetting is too small, leading to an excessive number of chunks that exceed the system's parallel processing capacity limit. - Uploading PDF documents results in ignored image content. The cause is that the OCR parsing switch for
customPdfParseis not enabled, and only plain text content is extracted.
How to Confirm the Configuration is Properly Set
- Upload a typical cotton blending list PDF, check if the parsed text retains structured fields such as fiber proportion and cotton blending batch.
- View the parsing task log information, confirm that the task duration does not exceed the duration set by
PARSE_FILE_TIMEOUT_SECONDS, and there are no timeout-related errors. - Compare the chunked text fragments, confirm that process parameters and their corresponding defect descriptions are divided into the same chunk, and are not forcibly split.
- Upload fabric inspection records containing images, confirm that image content is correctly recognized and associated with the corresponding inspection text.
The values provided here are common starting points, and should be evaluated against the reader's own samples.