What data in 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. Updates occur daily. Commonly processed documents include social insurance registration forms, payment base declaration forms, personnel change forms, social insurance premium verification slips, and personal social insurance contribution records. Most of these documents are structured standard forms. Core fields include personnel identity information, labor relationship status, payment base, declared personnel lists, and similar items. There are no unified fixed long text paragraphs. The smallest business unit is typically a single personnel business entry.
Constraints these characteristics impose on document parsing and chunking
Multi-source heterogeneous data sources for this category require the parsing engine to support document formats exported from different systems. Daily batch processing needs require the chunking process to have high efficiency. The structured nature of standard forms means chunking must not break the integrity of single personnel business entries. Information misalignment will occur in subsequent verification steps if this rule is violated. The sensitivity of core fields requires retaining the association between fields and corresponding personnel during chunking. Avoid splicing information across multiple personnel. Also, ensure parsing results can be accurately mapped to the standard field system for social insurance business.
How to set configurations
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
chunkSize | 800–1200 characters | This category of documents is mostly structured forms. Each chunk needs to cover a complete personnel social insurance registration or payment declaration unit to avoid splitting critical business information |
chunkSplitter | Chunk by paragraph + chunk by title | Social insurance-related documents have clear personnel and declaration item titles. Retaining paragraph associations ensures complete business logic after chunking |
customPdfParse | Enabled | Most documents in this category are standard forms. Enabling this setting preserves field boundaries from the original layout and reduces parsing misalignment |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Batch processing multiple social insurance documents requires sufficient time for OCR and structured extraction for a single file |
UPLOAD_FILE_MAX_SIZE | 100 MB | Personnel change summary forms submitted by employers may contain multi-page bulk data, so support for large file uploads is needed |
chunkSettingMode | Manual mode | The document structure for this category is fixed. Manually configuring chunking rules adapts to field splitting requirements for specific forms |
Three common mistakes
- Symptom: Chunk preview returns "unable to read file content". Cause: The
customPdfParseconfiguration is not enabled. The structured layout of standard social insurance forms cannot be recognized by the basic PDF parsing engine. - Symptom: OCR error appears in logs after deploying Marker. Cause:
PARSE_FILE_TIMEOUT_SECONDSis not configured with a sufficient duration. OCR processing times out and triggers an error when batch parsing large-volume social insurance premium verification slips. - Symptom: Feishu knowledge base cannot sync PPT and PDF documents. Cause:
UPLOAD_FILE_MAX_SIZEis not configured correctly. Document volume exceeds the limit, causing sync failure.
How to confirm the configuration is correct
- Upload a standard social insurance registration form, check the chunk preview results, and confirm that each personnel's declaration information is not split across chunks.
- Upload a single batch personnel change form under 100 MB, verify that no timeout errors occur during the parsing process.
- Check the switch status of
customPdfParse, and confirm that the field boundaries of standard forms are preserved. - Attempt to sync social insurance-related documents on the Feishu end, and confirm that there are no errors related to file type or volume limits.
Reference only; verify against the target FastGPT release and deployment documentation. The values provided are common starting points and should be evaluated against local 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.