What the Data for This Category Looks Like
Data sources include food safety sampling monitoring systems, the State Administration for Market Regulation's sampling results query system, laboratory LIMS, and food producer and operator ledgers. Daily documents cover sampling plans, sampling slips, inspection reports, unqualified food verification and disposal reports, and risk control announcements. Data is updated monthly. Most document structures include structured fields and tabular inspection data, with fields such as sampling number, inspection items, non-conforming items, and disposal measures. Document formats vary across different sources, and some documents contain multi-level nested attachments.
What Constraints Do These Characteristics Impose on the Document Parsing and Chunking Link?
Monthly updated batch documents require the parsing process to adapt to batch processing rhythms. Differences in document formats from multiple sources require flexible chunking rules. Structured inspection reports and sampling slips contain nested tables and numerical fields, so chunking must avoid breaking table logic. Long text paragraphs in non-conforming item disposal reports must be split according to business logic, to avoid arbitrary character-based truncation that splits business information. Differences in fields across documents require chunking rules to adapt to document types, to avoid inconsistent chunking standards across documents that reduces the accuracy of subsequent party building learning Q&A.
Configuration Settings
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
chunkSize | 800–1200 characters | Adapts to the length of single-paragraph business information in sampling reports and disposal announcements, avoiding splitting critical business units |
chunkSplitter | By paragraph + heading | Adapts to the structure of multiple document types, preserving heading hierarchies and paragraph logic for sampling slips and inspection reports |
customPdfParse | Enable MinerU adaptation mode | Adapts to nested tables and complex typesetting in sampling reports, improving the accuracy of structured data extraction |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Covers parsing time for large inspection reports and batch sampling plan documents, avoiding timeout interruptions |
UPLOAD_FILE_MAX_SIZE | 1000 MB | Adapts to large LIMS export documents for single-batch bulk uploads, meeting monthly bulk data processing requirements |
chunkSettingMode | Customize by document type | Adjust chunking rules separately for tabular documents like sampling slips and long-text documents like disposal reports |
Three Common Configuration Mistakes
- Parsing fails after uploading a docx document, with the interface showing "File parsing failed" error. Cause: The custom parsing mode adapted to market supervision documents is not enabled, and some embedded structured fields cannot be recognized by the standard parsing engine.
- Some tables in knowledge base documents cannot be chunked properly, with chunking results showing truncated tables or messy field splits. Cause:
chunkSplitteris configured to split only by characters, without preserving table structure associations, leading to table content being incorrectly split across different chunks. - A video memory overflow error occurs after deploying the MinerU parsing service, and GPU resources cannot be detected. Cause: GPU drivers and CUDA environments are not correctly mounted during Docker deployment, so the parsing service cannot call local graphics card resources, exceeding the video memory limit allocated to the container.
How to Verify Proper Configuration
- Upload a single food safety sampling inspection report, check the parsed Markdown result, confirm that table content is complete and not split.
- Upload monthly sampling plan documents in bulk, check the completion rate of parsing tasks, confirm that there are no timeout errors.
- Switch between different document types (sampling slips, disposal reports), verify that chunking results conform to business logic, with no critical information split apart.
- Check the running logs of the MinerU service, confirm that GPU resources are properly detected, with no video memory overflow prompts.
The values provided here are common starting points and should be evaluated against the reader's own samples.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-09-28.