What Data for This Category Looks Like
The core users of this category are manufacturing enterprise IPQC, FQC, quality engineering, and laboratory personnel. Daily processed documents include control plans, patrol inspection records, SPC reports, final product inspection reports, nonconforming product review forms, release forms, and quality monthly reports. Data sources include MES systems, online testing equipment, laboratory instruments, process parameter libraries, customer standards, and historical defect libraries. Updates occur per product batch, per shift, or via continuous collection. Documents contain structured fields and unstructured text, with some fields using dedicated units.
What Constraints These Characteristics Impose on Document Parsing and Chunking
The mixed multi-type structure of category documents requires parsing and chunking logic to balance structured field extraction and free text retention. It must avoid splitting key inspection items or exception descriptions. High-frequency updated batch documents require parsing processes with high efficiency, to support simultaneous processing of multiple files. Dedicated fields and units require retaining data associations during chunking, to avoid breaking the corresponding relationship between parameters and qualification judgments. Scanned documents or documents with nested tables, such as SPC reports, require accurate text extraction capabilities. Otherwise, content missing or format confusion may occur.
Configuration Settings
This configuration is based on FastGPT v4.17.0, and is adapted to document processing needs for the process quality and final product release scenario:
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
chunkSize | 800–1200 characters | Category documents include fixed inspection fields and coherent exception descriptions. This range avoids splitting single inspection items or key review opinions |
chunkSplitter | Paragraph-first + fixed character truncation | Balances field integrity for structured reports and natural paragraph retention for exception reports |
customPdfParse | Enabled | Adapts to non-pure-text PDF documents such as scanned SPC reports and control plans with nested tables, improving content extraction completeness |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | A single batch task may include multiple patrol inspection records or SPC reports. This duration covers parsing needs for batch documents |
UPLOAD_FILE_MAX_SIZE | 1000 MB | Supports batch uploading of patrol inspection record files for a single batch, adapting to team-level data processing needs |
chunkSettingMode | Manual mode | Category documents have large structural differences. Manual configuration allows flexible adjustment of chunking rules to adapt to different document types |
Three Common Mistakes
- The symptom is that some detected numerical fields are missing from the parsed final product inspection report. The cause is that
customPdfParseis not enabled, so table content in scanned or nested table documents cannot be accurately identified. - The symptom is that chunking results split a single inspection item into multiple independent segments. The cause is that
chunkSizeis set too small, and the chunking logic does not adapt to the fixed field structure of category documents. - The symptom is that batch patrol inspection record parsing tasks return timeout prompts. The cause is that
PARSE_FILE_TIMEOUT_SECONDSis set lower than the actual required duration for parsing batch documents.
How to Verify Proper Configuration
- Upload a typical control plan PDF, check whether all inspection parameters and qualification judgment fields are fully extracted in the parsed text, to confirm that the
customPdfParseconfiguration takes effect. - Adjust
chunkSizeto different ranges, compare the completeness of chunking results, to confirm that the chunking logic does not break key data associations. - Upload batch SPC report files, check whether parsing tasks complete within the preset
PARSE_FILE_TIMEOUT_SECONDSduration, to confirm that the timeout configuration adapts to the business scenario. - Check the returned text stream format, confirm that paragraph and field associations of the original document are retained after chunking, and the result can be directly used for front-end structured display.
The values given are common starting points and should be measured against the reader's own samples.