What the data for this category looks like
The main entities in this category are color printing, label, carton, flexible packaging, and pharmaceutical packaging processing enterprises. Daily documents include pre-press files, imposition sheets, printing process sheets, ink color matching records, first article sample approvals, barcode inspection records, and die-cutting and lamination records. Data sources include customer submissions, color management systems, printing press data, ink and substrate batch records, spectrometers, and barcode detectors. Update frequency is per order, per batch, or each time a plate is changed. Documents often have embedded dedicated fields such as version number, batch number, and process parameters, with no unified fixed format, and are flexibly adjusted according to order requirements.
What constraints these characteristics impose on document parsing and chunking
The heterogeneous document formats, high-frequency update rhythm, and dedicated field characteristics of this category impose multiple constraints on document parsing and chunking. First, documents cover unstructured process descriptions, semi-structured imposition sheets, and inspection records with numerical parameters. This requires the parsing module to adapt to multiple input types and avoid format parsing failures. Second, the high-frequency update requirement per order or per batch requires the parsing process to have fast response capabilities and adapt to parallel processing of batch bid documents. Third, documents embed key identifiers such as version number, batch number, and process parameters. Chunking must retain associated context to prevent loss of key information that affects quotation and bidding accuracy after splitting.
How to set the configuration
The following configurations are based on FastGPT v4.17.0.
| Configuration Item | Recommended Approach | Rationale |
|---|---|---|
chunkSize | 800–1200 characters | Category documents include process parameters, batch information, and quotation items. This range can retain a complete single business unit and avoid splitting content across processes or quotation items |
chunkSplitter | By paragraph + semantic boundary | Category documents contain unstructured process descriptions and semi-structured tables. Splitting by paragraph can retain content integrity, and combining with semantic boundaries can avoid forced splitting of long sentences |
customPdfParse | Enabled | Daily documents of this category include PDF files with complex layouts such as imposition sheets and first article sample approvals. Enabling this option optimizes text extraction effects for complex layouts |
PARSE_FILE_TIMEOUT_SECONDS | 300–600 seconds | A single bid document may include multiple associated documents. This duration covers the parsing time of batch heterogeneous documents and avoids timeout interruptions |
UPLOAD_FILE_MAX_SIZE | 1000 MB | Bid documents of this category may include multiple associated large image files. This upper limit covers the total size of conventional bid documents and avoids upload failures |
chunkSettingMode | Manual configuration | Documents of this category have large format differences. Manual configuration allows flexible adjustment of chunking rules to adapt to different types of bid documents and business data |
Three common mistakes
- Symptom: When importing Word or PowerPoint documents and enabling PDF enhanced parsing, the extracted text content is missing or the format is distorted. Cause: PDF enhanced parsing only optimizes PDF format documents. Adaptation to other formats' layouts relies on general parsing logic, and it will not take effect when the dedicated parsing configuration for the corresponding format is not enabled.
- Symptom: When importing Excel format ink color matching records or imposition sheets, the parsing result only extracts part of the column data or has field misalignment. Cause: The general parsing module has insufficient adaptation to Excel tables with multiple columns and merged cells. It cannot fully extract structured business data when custom parsing rules are not configured.
- Symptom: In the chunked document blocks, process parameters associated with the same quotation item are split into different blocks. Cause: The
chunkSizevalue does not match the business unit length of category documents, and content containing complete business logic is forcibly split.
How to confirm the configuration is correct
- Upload typical bid documents of this category, such as PDF files with imposition parameters, and check whether the parsing result covers all core business fields.
- Upload associated documents in multiple formats, verify that the parsing process does not trigger timeout errors, and that the text extraction effects of each format meet expectations.
- Adjust chunking-related parameters, compare chunking results under different configurations, and confirm that a complete piece of business content is not split into multiple blocks.
- Use debugging tools to view parsing logs, and confirm that the parameter values of configuration items match the preset configuration.
The values provided are common starting points and should be evaluated against the reader's own samples.