What this category of data entails
This category’s core data originates from health supervision information systems, medical institution electronic registration systems, complaint and reporting platforms, and law enforcement inspection records. Update frequency is monthly. Commonly processed documents include supervision inspection forms, medical institution practice licenses, rectification notices, penalty case files, and other materials. Some documents are in scanned format. Documents contain structured fields such as institution name, practice scope, and rectification requirements, alongside unstructured long text including law enforcement inspection details and penalty reasons. Fields cover core dimensions including institution qualification, personnel qualification, hospital infection control and disinfection, and compliance of diagnosis and treatment behaviors.
Constraints imposed on the document parsing and chunking link
Documents in this category have diverse types and large structural differences. Chunking rules must balance the integrity of structured fields and the coherence of long text. Document formats from different sources are inconsistent. Some scanned documents have layout offsets, requiring adaptation to multi-format parsing. A single processing batch may include hundreds of pages of law enforcement case files, leading to long parsing times. Reasonable timeout settings must be implemented. Core fields such as practice license number and rectification items must be fully retained in a single chunk. Splitting these across chunks prevents association of corresponding information, which affects subsequent review processes.
How to set the configurations
| Configuration Item | Recommended Value Range | Rationale |
|---|---|---|
chunkSize | 800–1200 characters | Adapts to long text segmentation of penalty case files and rectification notices, avoids splitting core fields such as institution qualifications and rectification requirements |
chunkSplitter | Split by paragraph + title | Matches the structured title structure of supervision inspection forms and rectification notices, retains the association between titles and corresponding content |
customPdfParse | Enable pdf-marker parsing | Enables accurate text extraction for multi-page law enforcement records and scanned practice licenses, optimizes parsing effect of scanned documents |
UPLOAD_FILE_MAX_SIZE | 1000 MB | Accommodates batch law enforcement case file archive files, meets the upload requirements for monthly batch review |
PARSE_FILE_TIMEOUT_SECONDS | 600–900 seconds | Addresses parsing time of hundreds-of-page PDF files, avoids timeout errors triggered by oversized files |
chunkSettingMode | Manual configuration | Adjusts chunking rules for different document types. For example, use shorter chunk lengths for supervision inspection forms, and standard chunking for long case files |
Three common misconfigurations
- Symptom: A
Cannot read properties of undefinederror occurs when callingcustomPdfParsein a locally deployed FastGPT v4.17.0 instance. Cause: The local service address of pdf-marker was not configured correctly, preventing normal connection to the parsing service. - Symptom: Parsing times out when uploading hundreds-of-page penalty case files. Cause: The value of
PARSE_FILE_TIMEOUT_SECONDSis too small, which does not match the actual parsing time of large files, leading to premature task termination. - Symptom: The issuance date and institution name of a medical institution practice license are split into different chunks after processing. Cause: The
chunkSizevalue is too large, orchunkSplitteris not set to split by title, resulting in cross-chunk truncation of structured fields.
How to confirm correct configuration
- Upload a single 200-page law enforcement case file PDF, and check whether parsed chunks have complete association between titles and corresponding body text, with no content split breaks.
- Check platform parsing logs to confirm that the
PARSE_FILE_TIMEOUT_SECONDSconfiguration does not trigger timeout errors, and large file parsing tasks complete normally. - Randomly select 10 documents of different types including supervision inspection forms, practice licenses, and rectification notices, and verify that core fields such as institution name, practice scope, and rectification requirements are retained in full after chunking.
- Test batch upload of 5 archive files, confirm that the
UPLOAD_FILE_MAX_SIZEconfiguration does not trigger upload restrictions, and all files can be submitted for parsing normally.
The provided values are common starting points, and should be evaluated against the samples used in the actual deployment environment.
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.