What the data for this category looks like
Data for this category comes from social insurance management systems, tax social insurance premium collection systems, market entity registration information, and shared public security and civil affairs data. Daily processed documents include insurance registration forms, payment base declaration forms, personnel change forms, social insurance premium verification notices, personal benefit records, and other mostly fixed-format structured forms or reports. Data updates daily. Core fields include personnel identity identifiers, labor relationship information, payment bases, personnel change statuses, and other fields tightly bound to business processes.
What constraints these characteristics place on the document parsing and chunking step
Data from multiple sources has varying formats. Document parsing must adapt to form styles exported by different systems. High-frequency daily data volume requires chunk processing to support batch tasks without breaking business logic associations. Core fields are tightly bound to personnel identity and payment status. Chunk operations must not truncate field groups that contain complete business information. Otherwise, errors will occur in subsequent verification links. Data errors directly affect personal benefits and payment compliance. Parsing and chunking must retain contextual associations between fields, and avoid splitting critical business units.
Reference only; verify against the target FastGPT release and deployment documentation.
How to set the configurations
| Configuration Item | Recommended Value Range | Rationale |
|---|---|---|
chunkSize | 800–1200 characters | Adapts to the field group length of insurance registration forms and personnel change forms, avoids splitting complete information related to personnel identity and payments |
chunkSplitter | Chunk by paragraph + semantics | Adapts to format differences in documents exported from multiple systems, retains contextual associations of business logic |
customPdfParse | Enable structured parsing | Targets the fixed table structure of social insurance forms, accurately extracts core fields such as personnel ID and payment base |
UPLOAD_FILE_MAX_SIZE | 1000 MB | Supports batch submission of large-volume documents such as personnel change forms and monthly premium verification notices |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Adapts to the parsing time of long documents after merging data from multiple systems, avoids task timeout failures |
chunkSettingMode | Manual configuration | Targets the fixed field rules of social insurance documents, customizes boundary conditions for chunking |
Three common mistakes
- Phenomenon: Personnel identity fields are empty, or payment base information is missing after parsing. Cause: Structured parsing via
customPdfParseis not enabled, and only the default general text parsing is used. This cannot accurately extract fixed table fields within forms. - Phenomenon: Batch parsing tasks time out and return timeout status codes. Cause:
PARSE_FILE_TIMEOUT_SECONDSis not adjusted to match task duration. This cannot handle batch documents containing dozens of personnel records. - Phenomenon: Insurance information for the same personnel is split into two different chunks. Cause:
chunkSizeis set too small, truncating complete paragraphs containing personnel IDs and multiple change records.
How to confirm the configuration is correct
- Upload a single standard insurance registration form. Check if parsed fields fully cover core information such as personnel name, ID number, and insurance type.
- Adjust the
chunkSizeparameter. Upload a document containing multiple personnel change records. Confirm that all relevant information for the same personnel is not split into different chunks. - Submit a batch document task. Check that there are no timeout errors in the parsing log. Confirm that
PARSE_FILE_TIMEOUT_SECONDSmeets task requirements. - View parsed chunk results. Confirm that
customPdfParseis active, and no unstructured, chaotic text content appears.
The values provided are common starting points and should be measured 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.