Data Profile for This Category
The primary entities in this category are bakeries, cookie manufacturers, instant noodle factories, and frozen pastry producers. Daily documents include formulas and feeding lists, production records, baking or steaming curves, metal detection logs, cleaning and disinfection records, and factory inspection reports. Data sources cover raw and auxiliary material qualification certificates, ERP/MES systems, weighing systems, production equipment, laboratories, and food traceability ledgers. Updates occur per production batch, shift, or daily. Document fields include allergen labels, feeding quantities, baking temperatures, shelf lives, and some documents include charts and structured tables.
Constraints for Document Parsing and Chunking
Mixed document types require parsing tools to support plain text, table, and chart formats simultaneously, to avoid splitting critical sensitive information such as allergen labels and feeding parameters. Frequently updated batch documents require efficient parsing workflows to prevent audit delays from parsing lag. Document formats vary widely across different sources, so custom parsing rules must be supported to adapt to files exported from various systems. The accuracy of allergen and production parameter data is directly tied to compliance and recall risks. Chunking must fully retain field association relationships to avoid information fragmentation.
Configuration Settings
This configuration is based on the functional logic of FastGPT v4.17.0.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
chunkSize | 800–1200 characters | Adapts to the field density of formulas and production records, avoids splitting critical associated information such as allergen labels and feeding quantities |
chunkSplitter | Split by paragraph + table boundaries | Preserves the structural integrity of multi-row tables and baking curve charts, adapts to mixed layouts of multiple document types |
customPdfParse | Enable pdf-marker parsing | Adapts to production records and inspection reports with charts and structured tables, improves parsing accuracy for complex PDFs |
PARSE_FILE_TIMEOUT_SECONDS | 300–600 seconds | Adapts to the upload and parsing time of batch production records, prevents timeout errors caused by oversized single files |
UPLOAD_FILE_MAX_SIZE | 1000 MB | Adapts to the maximum file size limit for single-batch production records, supports batch upload of multiple documents |
chunkSettingMode | Manual configuration | Adjust chunking and parsing parameters for different document types such as formula documents, production records, and test curves |
Three Common Configuration Errors
- Encoding error messages appear during document upload, such as
the argument ‘windows-1252’ is invalid encoding| Documents contain legacy comments or fields encoded in non-UTF-8 formats, and multi-encoding adaptive parsing configurations are not enabled - Document source cannot be traced after knowledge base chunking | Binding rules between chunking and document metadata are not configured, preventing association with original documents during responses
- Fields are scrambled after parsing multi-row XLSX tables | Chunking rules that split by table row and column boundaries are not configured, leading to confusion of cross-row and cross-column field information
How to Verify Correct Configuration
- Upload a single formula PDF, confirm that parsed chunks include complete allergen labels, feeding parameters, and batch information
- Upload batch production record files, verify that parsing time falls within the preset range of
PARSE_FILE_TIMEOUT_SECONDS - Upload XLSX-format metal detection tables, check that chunking results retain the table’s row and column structure
- View parsing logs to confirm no encoding errors or timeout errors occur, and that chunking results have no obvious information missing
The values provided are common starting points and should be measured against the reader's own samples.