What this category of data looks like
This category of data originates from the National Primary and Secondary School Student Status Management System, local enrollment platforms, household registration and property verification data, and school educational administration systems. It is updated daily. Commonly processed documents include enrollment application forms, student status information forms, transfer applications, enrollment plans, admission rosters, and student status change approval forms. Most are structured forms or batch tables. Fields cover student identity information, household registration address, property certificate number, student status change type, and similar items. The volume of single documents or batch data ranges from 100,000-character Chinese Word documents to Excel data with more than 15,000 rows.
Constraints imposed on document parsing and chunking
The batch structured tables and large-volume single documents in this category require parsing tools to support multi-format batch processing and long document splitting. High-frequency daily data update requirements demand that parsing processes have stable timeout fault tolerance and breakpoint resume capabilities. The strong correlation between student identity and student status-related fields requires retaining contextual associations between fields during chunking, to avoid losing relevant information required for qualification verification after splitting. Differences in data formats across sources require parsing configurations to support custom field mapping and format adaptation, reducing manual cleaning costs.
How to Set Configurations
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Parameter | Recommended Setting | Rationale |
|---|---|---|
chunkSize | 800–1200 characters | Adapts to the correlation length of fields such as student identity and student status information in this category of documents, avoiding loss of context required for qualification verification after splitting |
chunkSplitter | Split by paragraph + table header | Adapts to the document structure of structured forms and batch tables, retaining the integrity of field groups |
UPLOAD_FILE_MAX_SIZE | 1000 MB | Supports upload requirements for single 100,000-character Chinese Word documents or Excel data with 15,000+ rows |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Matches parsing time for large-volume batch data, avoiding parsing interruptions in high-frequency update scenarios |
customPdfParse | Enable custom parsing rules | Adapts to field extraction for standardized PDF documents such as enrollment plans and admission rosters |
chunkSettingMode | Manual configuration | Flexibly adjust chunk boundaries and association retention rules for the structured data characteristics of this category |
Three Common Misconfigurations
- Symptom: A timeout error with status code 504 occurs when parsing a 100,000-character Chinese Word document. Cause: The
PARSE_FILE_TIMEOUT_SECONDSvalue is not adjusted to a range suitable for large-volume documents, and the default timeout duration is insufficient to complete full parsing. - Symptom: Some student identity fields are empty after parsing batch Excel student status data. Cause: The corresponding structured table parsing rule is not enabled, so hidden fields nested within the table cannot be correctly identified.
- Symptom: Vector generation fails after chunking, with a prompt that contextual association is broken. Cause:
chunkSplitteris not set to split by table header or paragraph, causing the split to cut off the association content between student status information and corresponding student identity.
How to Verify Correct Configuration
- Upload a single 100,000-character Chinese Word enrollment application form, check that parsing completes within 600 seconds with no timeout errors.
- Upload an Excel student status information table with 15,000+ rows, verify that the number of parsed fields matches the source data fields.
- After enabling
customPdfParse, upload an enrollment plan PDF document, confirm that core fields such as enrollment quota and application requirements are fully extracted without missing content. - Adjust
chunkSizeto the 800–1200 character range, generate vectors, and check that chunked content retains the association between student name and corresponding student status number.
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.