What this category of data looks like
Data for this category comes from manufacturing enterprise IPQC, FQC teams, quality engineering departments, and laboratories. Daily generated documents include control plans, patrol inspection records, SPC reports, finished product inspection reports, nonconforming product review forms, release forms, quality monthly reports, and other materials. These documents act as quality supporting materials for bid documents and quotation preparation.
Data sources cover MES systems, online testing equipment, laboratory test results, process parameter logs, customer standard documents, and historical defect databases. Updates are collected continuously based on production batches and team shifts. Documents contain fields such as inspection items, nonconforming judgments, release identifiers, batch numbers, and test values. They are linked to parameters and standard requirements of specific production links.
What constraints this category of data imposes on document parsing and chunking
The multi-source mixed characteristics of this category of data require the document parsing link to adapt to both structured reports and unstructured records. It must avoid splitting content that links across fields. For example, it must preserve the binding relationship between finished product inspection reports and corresponding release forms. This ensures complete context when quality data is referenced in bid documents.
High-frequency batch-level data requires chunk length to fit the complete logic of a single batch inspection process. It must avoid truncating key judgment bases, which would affect the effectiveness of quality supporting materials for bid quotations.
The presence of professional quality terminology and standardized fields requires the parsing link to retain original fields and units. This avoids ambiguity that would cause compliance issues in bid documents.
The need to support multiple document formats requires parsing configurations to be compatible with file formats exported by different systems. This includes adapting to hand-scanned patrol inspection records and spreadsheet-format SPC reports, meeting the diverse submission requirements of bid materials.
How to configure the settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
chunkSize | 800–1200 characters | Fits the complete logic of single-batch quality documents for this category, avoids truncating key linked content such as inspection items and judgment results, and ensures complete context for references in bid documents |
chunkSplitter | Split by title and paragraph boundaries | Matches the structure of documents in this category, which include control plan titles and patrol inspection record paragraphs, and preserves the binding relationship between quality judgments and bid requirements |
customPdfParse | Enabled | Optimizes parsing effects for scanned patrol inspection records and SPC reports with formulas, adapts to the multi-format bid material submission requirements of this category |
PARSE_FILE_TIMEOUT_SECONDS | 300–600 seconds | Meets the parsing time requirements of multi-source complex documents, avoids interrupting parsing tasks due to timeout, and ensures processing efficiency for batch bid materials |
UPLOAD_FILE_MAX_SIZE | 1000 MB | Supports the upload needs of batch historical quality reports, adapts to batch data import and bid material submission scenarios for this category |
chunkSettingMode | Manual configuration | Adjusts chunking rules for different types of quality documents, adapts to differences between structured reports and unstructured records, and accurately supports content organization for bid documents |
Three common misconfigurations
- Symptom: After uploading a PDF document to the FastGPT knowledge base, clicking chunk preview shows that the file content cannot be read. Cause: The
customPdfParseconfiguration is not enabled, or thePARSE_FILE_TIMEOUT_SECONDSsetting is too short, causing complex SPC reports or scanned patrol inspection records to fail to complete parsing. - Symptom: The locally deployed FastGPT v4.8.12 version cannot return complex formulas in documents normally, while the same type of online version can return results normally. Cause: The marker_images parsing image version does not match the FastGPT version. The parsing plugin for FastGPT v4.17.0 requires a matching image version to ensure formula recognition effects.
- Symptom: After configuring the Feishu knowledge base, PPT and PDF files cannot be synchronized. Cause: The cross-document type parsing whitelist is not configured, or the uploaded file size exceeds the
UPLOAD_FILE_MAX_SIZElimit, causing the synchronization task to be blocked.
How to confirm the configuration is correct
- Upload a single finished product inspection report PDF, check the chunk preview result, and confirm that key content such as inspection items and judgment results is not truncated.
- Upload an SPC report containing complex formulas, verify that the parsing result can display formulas and test values normally.
- Upload batch historical quality documents, check the status of parsing tasks, and confirm that there are no frequent timeout errors.
- Synchronize PPT and PDF files in the Feishu knowledge base, confirm that the files can be normally retrieved and previewed in chunked form.
The values listed here are common starting points. They should be assessed against the specific samples in use.