What the Data for This Category Looks Like
The data sources for this category include government information disclosure platforms, agency archive systems, document management systems, and departmental business ledgers. Update frequency is irregular. Commonly processed documents include government information disclosure application forms, supplementary notice letters, third-party opinion solicitation letters, response letters, delivery receipts, and administrative reconsideration response materials. Most documents contain structured fields such as fixed application numbers, applicant information, application content, and response content. Some documents have multi-column tables, embedded images, or multi-page attachments.
Constraints on Document Parsing and Chunking
Diverse document types and structured fields require parsing and chunking to retain contextual integrity for each module, preventing separation of key government information such as relief pathways. Multi-column tables and embedded images require parsing functions to adapt to complex layouts and accurately extract table content and image descriptions. Scattered data sources and inconsistent formats require support for custom parsing rules to accommodate files from different sources. Irregular update frequencies require a stable, reliable parsing process with no redundant pre-checks that block batch processing.
Configuration Settings
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
chunkSize | 800–1200 characters | Adapts to the typical length of government response texts in this category, avoiding chunking that splits key information such as application numbers and relief pathways |
chunkSplitter | Split by paragraph + title | Documents in this category have fixed titles and structured fields. Splitting by title preserves the contextual integrity of each business module |
customPdfParse | Enabled | Adapts to the complex layouts of multi-column tables and embedded images in documents of this category, accurately extracting table content and image descriptions |
PARSE_FILE_TIMEOUT_SECONDS | 120 seconds | Meets the parsing time requirements for large files containing multi-page administrative reconsideration materials, avoiding parsing timeout failures |
UPLOAD_FILE_MAX_SIZE | 50 MB | Matches the typical size of a single application material in this category, avoiding parsing exceptions caused by oversized files |
Three Common Misconfigurations
- Parsed image fields are empty, or embedded PDF image content cannot be extracted. The cause is that the
customPdfParseconfiguration is not enabled; the default parsing does not enable image extraction. - Multi-column table content is disorganized after parsing and cannot be displayed in column-aligned format. The cause is that
chunkSplitteris not configured to split by title; the default chunking does not recognize multi-column layout structures. - Parsing tasks time out and fail, returning status code 504. The cause is that
PARSE_FILE_TIMEOUT_SECONDSis not adjusted to a value suitable for large files; the default timeout duration does not cover parsing time.
How to Verify Successful Configuration
- Upload a PDF of a government information disclosure response document containing multi-column tables and embedded images, and check whether the parsed content retains table column alignment and image descriptions.
- View the parsing task log to confirm that the
PARSE_FILE_TIMEOUT_SECONDSconfiguration is active, with no timeout errors. - Test the chunked text fragments to confirm that each chunk contains complete key fields such as application numbers and response content, with no content separation.
- Upload a file of the maximum allowed size, and confirm that the parsing task completes normally without triggering upload limits.
The provided values are common starting points and should be evaluated against samples for the specific deployment.
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.