This document is written based on FastGPT v4.17.0.
What This Category of Data Looks Like
Data sources for this category include MES systems, online testing equipment, laboratory reports, process parameter documents, customer quality standards, and historical defect databases. Data is collected continuously according to production batches and team shift cycles.
Daily documents include control plans, patrol inspection records, SPC reports, finished product inspection reports, nonconforming product review forms, release approval forms, and monthly quality reports. Document fields include inspection item identifiers, defect type codes, qualified judgment intervals, batch numbers, inspector information, and review conclusions. There is no unified fixed format. Some documents are structured tables, while others are semi-structured text.
Constraints on the Document Parsing and Chunking Link
Multi-source heterogeneous data types require parsing components that support adaptive processing for mixed structured tables and semi-structured text. The high-frequency update rhythm based on batches and shift cycles requires parsing efficiency to match collection frequency, to avoid slowing down the ledger summary process.
Non-standardized document structures require retaining contextual associations during chunking, to prevent splitting the logical binding between inspection items and judgment results, or between approval nodes and conclusions. Batch parsing of long-text documents such as annual quality reports and historical defect databases requires sufficient processing time and space, to avoid content truncation.
Format differences across documents also require flexible configuration capabilities, to adapt to scenarios ranging from short-text patrol records to long-form quality reports.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
chunkSize | 800–1200 characters | Adapts to the contextual length of inspection items and judgment results in this category of documents, avoiding splitting the complete logic of a single inspection record |
chunkSplitter | Split by paragraph + table | Adapts to document types with mixed structured tables and semi-structured text, retaining the association between inspection tables and corresponding descriptions |
customPdfParse | Enabled | Supports accurate extraction of structured tables in control plans and inspection reports, preventing incorrect splitting of table content |
UPLOAD_FILE_MAX_SIZE | 1000 MB | Adapts to the upload needs of large-volume documents such as batch quality reports and historical defect databases |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Matches the parsing time required for long-text documents such as annual quality reports, avoiding parsing failure due to timeout |
chunkSettingMode | Manual configuration | Allows adjustment of chunking parameters for different document types such as patrol records and release forms, adapting to non-standardized document structures |
Three Common Misconfigurations
- Phenomenon: Parsed documents lack table fields, or inspection items in patrol records are not fully extracted. Cause: The
customPdfParseconfiguration is not enabled, resulting in structured tables failing to be accurately identified, and only plain text content is extracted. - Phenomenon: Table-type documents that have been uploaded cannot be found when filtering datasets in the knowledge base. Cause: The
customPdfParseconfiguration is not set to enabled, so table files are not correctly recognized as indexable datasets. - Phenomenon: Only partial content of long parsed documents is loaded, and the complete text is not fully parsed. Cause: The
PARSE_FILE_TIMEOUT_SECONDSparameter is not adjusted, and long documents trigger a timeout during parsing, leading to interrupted parsing.
How to Verify Proper Configuration
- Upload a PDF copy of a finished product inspection report, check if the parsed content includes complete inspection tables and corresponding text descriptions, and confirm that table fields are not lost.
- Upload a single quality report document with a volume not exceeding the set limit, wait for parsing to complete, then check the parsing progress status, and confirm that no timeout errors occur.
- Adjust the
chunkSizeparameter for the same patrol record document, compare the parsing results, and confirm that the chunked content can fully retain the logic of a single inspection record. - Enter the dataset filtering interface, confirm that table-type files can be normally selected and added to the knowledge base.
The values provided here are common starting points, and should be evaluated against the reader's own samples.