What this category of data looks like
This category of data comes 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 insurance registration forms, premium base declaration forms, personnel change forms, social premium verification notices, and personal benefit records. Most documents contain fields such as personnel identity identifiers, labor relationship information, premium bases, and verified amounts. Some batch documents combine multiple pages of content by unit or payment cycle.
Constraints on document parsing and chunking
This category’s data characteristics impose multiple constraints on the document parsing and chunking stage. Documents from cross-system sources have inconsistent formats, with field misalignment and mixed layouts. Parsing tools must support multiple formats. Daily updated batch documents have large scale. A single file may contain hundreds of personnel records. Parsing and chunking must support large file processing to avoid timeouts or interruptions. Personnel identity and premium-related fields are core business fields. Chunking must retain field associations. Splitting must not break business connection logic. Doing so would reduce the accuracy of subsequent ledger summary and report generation. The system must also accommodate layout differences across different source documents, to ensure parsed text can be accurately identified and linked.
Configuration Settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
chunkSize | 800–1200 characters | Adapts to the field density and business association of insurance-related documents, prevents loss of association between personnel and premium data after splitting |
chunkSplitter | Split by paragraph + semantics | Accommodates layout differences across multi-format documents, preserves the integrity of business paragraphs such as personnel changes and base declarations |
customPdfParse | Enable local pdf-marker parsing | Adapts to complex layouts of batch social insurance documents, improves field recognition accuracy |
UPLOAD_FILE_MAX_SIZE | 1000 MB | Supports single-batch large-volume unit monthly premium summary documents, prevents upload blocking |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Covers parsing time for hundreds-page social insurance documents, prevents timeout interruptions during large file parsing |
chunkSettingMode | Manual configuration | Adjusts chunking rules based on the field characteristics of social insurance documents, meets association requirements for business data |
Three common misconfigurations
- Symptom: Long unresponsive periods or timeout errors after calling the parsing tool. Cause: The
PARSE_FILE_TIMEOUT_SECONDSparameter is not adjusted, and parsing time for large-volume social insurance documents exceeds the default threshold. - Symptom: Large amounts of duplicate content or incorrect splitting of core fields in chunking results. Cause: The
chunkSizesetting is unreasonable, and semantic chunking rules are not enabled, leading to repeated splitting or forced truncation of the same business paragraph. - Symptom: Undefined property read errors appear on the page after locally deploying pdf-marker. Cause: The local service address for
customPdfParseis not configured correctly, preventing the parsing tool from being called normally.
How to confirm configurations are properly set
- Upload a single 500-page social insurance premium summary document. Check upload progress and parsing status, confirm no upload blocking or timeout errors are triggered.
- Review chunked text fragments. Confirm core fields such as personnel identity numbers and premium bases are not split across different chunks.
- Test batch upload of multiple social insurance documents in different formats. Confirm consistent field recognition across parsing results.
- Check FastGPT v4.17.0 backend logs. Confirm parsing tool call parameters match configuration items.
The values listed are common starting points, and should be evaluated 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.