Reference only; verify against the target FastGPT release and deployment documentation.
What the Data for This Category Looks Like
Daily documents for this category include audit notices, inspection work drafts, suspicion lists, interview records, handling decision documents, and rectification reports. Data sources include medical insurance intelligent monitoring systems, fund supervision rule bases, medical insurance settlement data, drug and consumable traceability codes, and complaint clues. Data updates occur monthly. Documents combine unstructured government document formats with structured settlement details and traceability code information. Core fields include document numbers, inspected entities, violation matters, handling opinions, and more. Some documents include tabulated charge records and consumable information.
Constraints on Document Parsing and Chunking From These Characteristics
Monthly update frequency eliminates the need for high-frequency real-time parsing. Moderate batch processing time is acceptable. Documents use a mixed format of unstructured text and structured tables. Parsing must extract paragraph hierarchies and structure table content. The integrity of core fields such as violation matters and handling decision document numbers directly impacts subsequent audit work. Chunking must avoid splitting key information units. Data sources include standardized codes like traceability codes. Parsing must ensure no loss of coded information.
Configuration Settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
chunkSize | 800–1200 characters | Adapt to the typical paragraph length of audit-related documents, avoid splitting key title lines that include document numbers and violation matters |
chunkSplitter | Split by paragraph + title | Match the hierarchical structure of audit documents, retain title hierarchy information for notices and drafts, ensure chunking logic aligns with document structure |
customPdfParse | Enable structured parsing mode | Adapt to documents with settlement detail tables, extract structured fields such as charge amounts and drug names within table cells |
UPLOAD_FILE_MAX_SIZE | 1000 MB | Accommodate collections of multiple documents from single-batch special inspections, match monthly batch update upload requirements |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Process complaint clue documents with large numbers of drug and consumable traceability codes, avoid parsing timeout interruptions due to large content volume |
chunkSettingMode | Manual configuration | Adjust chunking parameters for different document types (such as handling decision documents, suspicion lists), ensure parsing accuracy across different scenarios |
Three Common Mistakes
- Local frontend environments can parse uploaded files normally, but server deployments report 404 errors during file upload. The cause is unconfigured correct file storage directory permissions, preventing parsing components from reading uploaded PDF and DOCX files.
- Using the Qwen3-14B model fails to extract response fields from parsing results, while the Qwen2.5-14B model works normally. The cause is that the
customPdfParsestructured parsing mode is not enabled, so Qwen3 cannot recognize tabulated settlement detail fields. - Post-parsing chunking results lose complete document number information for handling decision documents. The cause is an overly small
chunkSizesetting, splitting title lines that include document numbers into two separate chunks.
How to Verify Proper Configuration
- Upload a single audit notice document, check that title and violation matter fields in the parsing results are fully extracted, with no truncation or loss.
- Check the file size limit configuration on the file upload interface, confirm it is set to a threshold no smaller than the total size of monthly batch upload documents.
- Test a document with settlement detail tables, confirm parsing results retain structured information such as charge amounts and drug names within table cells.
- Adjust the
chunkSizeparameter, re-upload a long document, check that chunking retains complete paragraph hierarchy, with no splitting of key information.
The values provided 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.