What This Category of Data Looks Like
This category of data primarily comes from purchase orders, drawings and specification documents, supplier quality certificates, data collected by inspection equipment, historical quality records, and supplier portals. Commonly processed documents include inspection specifications, sampling plans, incoming material inspection reports, supplier audit reports, abnormality contact sheets, 8D correction reports, and concession acceptance approval forms. Data updates are generated with each batch of incoming materials. Supplier quality evaluations are completed monthly or quarterly, and special audits are carried out irregularly. Document fields include batch identifiers, supplier information, inspection parameters, qualified judgment results, sampling quantities, descriptions of non-conforming items, and more. Supported formats include structured tables, scanned documents, plain text, and semi-structured forms.
Constraints Imposed on Document Parsing and Chunking
The data characteristics of this category impose multiple constraints on the document parsing and chunking process. Documents from multiple sources have significant format differences. Different parsing logic must be adapted to fully extract structured and unstructured content. Frequent batch-level updates and irregular special audit documents require chunking strategies that balance the compactness of single-batch data and the integrity of complex documents. The need to retain professional quality terminology requires avoiding chunking that breaks the connection between terminology and its context. Scanned documents require OCR parsing. The binding relationship between inspection items and judgment results must also be distinguished to prevent chunking from destroying content associations.
Configuration Settings
The following configurations are based on FastGPT v4.17.0.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
chunkSize | 800–1200 characters | This category of documents contains professional terminology and structured fields. Chunks that are too long will cause semantic fragmentation, while chunks that are too short will break the connection between inspection items and judgment results. This empirically calibrated range adapts to the content density of quality documents |
chunkSplitter | Paragraph + fixed character boundary | This category of documents includes both structured paragraphs and continuous inspection records. A mixed chunking strategy balances terminology context and content integrity |
customPdfParse | Enable structured table parsing | Most documents in this category include inspection parameter tables. Enabling this setting preserves the correspondence between table fields and their content, preventing field confusion after parsing |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | OCR parsing of some scanned documents takes a long time. This duration covers the complete parsing process for batch incoming material inspection reports |
chunkSettingMode | Manual configuration | This category of documents has large format differences. Manual configuration allows adjustment of chunking parameters for different document types, adapting to the parsing needs of professional quality documents |
Three Common Configuration Mistakes
- Issue: After upgrading the FastGPT version, uploading the same CSV-format incoming material inspection report triggers parsing failure, returning a timeout or format error prompt. Cause: The default chunking rules of the new version have been updated, and they do not adapt to the special layout of structured fields such as batch numbers and inspection items included in this category of documents.
- Issue: After configuring the minerU document parsing function, the parsed result of the uploaded supplier quality certificate is empty. Cause: The minerU connection configuration was not completed correctly, causing the parsing node to fail to correctly receive the uploaded file.
- Issue: When attempting to directly call the large model using the uploaded original PDF inspection report, the large model returns a prompt that it cannot read the file content. Cause: The system default text parsing process was not configured to be skipped, and the file was automatically converted to generic text before being passed to the node, so the original file was not directly transferred.
How to Verify Successful Configuration
- Upload a typical incoming material inspection report PDF, check the parsed text content, and confirm that inspection items and their corresponding qualified judgment results are not split apart.
- Check the parsing task logs, confirm that the parsing time does not exceed the configured
PARSE_FILE_TIMEOUT_SECONDSthreshold, and there are no timeout or format error prompts. - Generate a test index after manually adjusting the chunking parameters, retrieve content containing professional quality terminology, and confirm that the chunks fully retain the connection between terminology and its context.
- Upload a scanned supplier audit report, confirm that the parsed result preserves the field correspondence of the original table, with no content loss or confusion.
The values provided are common starting points and should be measured against the user's own samples.