What This Category of Data Looks Like
Data for this category originates from social insurance management systems, tax social premium collection systems, market entity registration information, and shared public security and civil affairs data. The update frequency is daily. Commonly processed documents include enrollment registration forms, payment base declaration forms, personnel change forms, social premium verification notices, and personal benefit records. Most document fields contain personnel identity identifiers, insured unit information, payment bases, and personnel change details. Some tables have multi-row nested structures. Data fields must strictly correspond to social insurance management rules.
What Constraints Do These Characteristics Impose on the Document Parsing and Chunking Step
Multi-source data format differences require the parsing module to support standardized PDFs, Excel tables, and a small number of scanned files exported from systems. The daily update business rhythm requires the parsing process to have low latency, to avoid delaying the overall progress of batch review. The fixed header and multi-row personnel detail structure of enrollment documents requires chunking to retain the integrity of single personnel declaration records, to avoid breaking business logic through incorrect splitting. The strong binding between fields and social insurance management rules requires the parsing result to accurately extract core fields such as identity identifiers and payment bases, to prevent field misalignment or omission.
How to Set Configurations
For FastGPT v4.17.0, the following configuration recommendations apply to document parsing and chunking for this category:
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
chunkSize | 800–1200 characters | The length of a single personnel declaration record in enrollment documents typically ranges from 500 to 1000 characters. This range avoids splitting complete declaration information for a single personnel record |
chunkSplitter | Split by paragraph + title | Documents have fixed headers and detail paragraphs. Splitting by title retains the integrity of business modules such as insured unit information and personnel details |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Batch processing multiple social premium verification notices results in long parsing time per file. Sufficient time must be reserved for format conversion and field extraction |
UPLOAD_FILE_MAX_SIZE | 1000 MB | Some employers submit large Excel files with batch personnel change forms. Large file upload support is required |
customPdfParse | Enable Marker parsing mode | Social insurance PDFs are mostly structured formats exported from systems. Marker accurately extracts tables and text content to reduce parsing errors |
chunkSettingMode | Manual configuration | Parameters must be adjusted for different document types to adapt to the business structure of enrollment registration and premium payment verification |
Three Common Mistakes
- When processing social insurance PDFs after deploying Marker, an error occurs with a response containing error information. The cause is failure to correctly configure environment variables to adapt to the structured table parsing logic for social insurance PDFs.
- Chunking results split the change declaration information for a single personnel record, with core fields misaligned. The cause is an overly small
chunkSizevalue, which cuts the connection between personnel information and insured unit details during splitting. - Batch uploaded Excel files of personnel change forms fail to upload. The cause is failure to adjust the
UPLOAD_FILE_MAX_SIZEparameter, exceeding the default file size limit.
How to Confirm Proper Configuration
- Upload a standard enrollment registration form PDF, review the parsed table extraction and text content, confirm no field missing or misalignment.
- Check the FastGPT backend parsing logs, confirm the
PARSE_FILE_TIMEOUT_SECONDSparameter is active, and no timeout errors occur during single file parsing. - Adjust
chunkSizeto different ranges, test whether chunking results retain the integrity of single personnel declaration records. - Upload a batch Excel file of personnel change forms, confirm upload proceeds normally, and no errors related to file size limits are triggered.
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.