What the data for this category looks like
This category serves public service entities including disease control institutions, medical facilities, public health departments, and disease control divisions of health commissions. Documents used in party building learning Q&A scenarios fall into two types:
- Daily business documents, including infectious disease report cards, epidemic analysis reports, case correction records, clustered epidemic reports, flow investigation reports, and more
- Policy documents and training materials related to party building learning
Data sources include the China Disease Prevention and Control Information System, hospital HIS and infectious disease reporting systems, laboratory testing systems, and public documents from party building learning platforms. Business documents update daily. Party building materials update quarterly or monthly. Most documents mix structured tables and long text. Business documents contain standardized fields such as case identification, reporting time limits, and diagnosis information. Party building materials include policy entries, learning points, and similar content.
What constraints these characteristics impose on document parsing and chunking
Document characteristics in this scenario create multiple constraints for parsing and chunking:
- High-frequency daily updates for business documents require stable, efficient parsing processes to avoid delays in epidemic monitoring and party building learning content updates
- Structured table documents need full extraction of all fields to ensure accurate retrieval of infectious disease reporting specifications and compliance requirements in party building Q&A
- Correction records have a strong association with original reports. Chunking processes must retain these associations to avoid information contradictions in party building Q&A
- Bulk uploaded summary files have large file sizes. Parsing capabilities must adapt to large files to support bulk import of monthly party building learning materials and business data
- The completeness of legally required report fields directly impacts business compliance, and forms the core content of compliance education in party building learning. Parsing processes must not miss key fields
How to set configurations
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
chunkSize | 800–1200 characters | Documents in this scenario mix structured tables and long text. Excessively large chunk sizes reduce retrieval accuracy. Excessively small chunk sizes destroy the association of case information and the paragraph integrity of party building materials. This range adapts to most document structures |
chunkSplitter | Split by paragraph + table | Fixed character-based splitting breaks the association of case fields within tables and the paragraph logic of party building materials. Splitting by paragraph and table units retains full data integrity |
customPdfParse | Enable mineru API parsing | Native parsing cannot fully extract correction record fields and party building policy entries from multi-column PDFs and Excel files. The mineru API meets the parsing needs of structured disease control documents and party building materials |
PARSE_FILE_TIMEOUT_SECONDS | 300–600 seconds | Single monthly epidemic summary reports or party building learning packages contain multiple days of case data and multiple documents, leading to long parsing times. This range covers the parsing needs of most bulk files |
UPLOAD_FILE_MAX_SIZE | 1000 MB | Monthly summary packages and party building learning material packages uploaded by disease control institutions have large file sizes. This setting supports bulk data upload scenarios |
chunkSettingMode | Manual mode | Document structures in this scenario are standardized. Manually specifying chunking rules ensures that legally required report fields and core party building points are not split during processing |
Three common configuration mistakes
- After uploading multi-column Excel format infectious disease report cards or party building material tables, the knowledge base only recognizes the first two columns of content. Cause: The multi-column table parsing mode of
customPdfParseis not enabled. The default parsing logic only identifies the first two columns of text. - After uploading a single-day epidemic summary file or a single long party building material, the parsing task times out and fails. Cause: The value set for
PARSE_FILE_TIMEOUT_SECONDSis lower than the actual parsing time, and does not adapt to the bulk data processing needs of documents in this scenario. - After chunking and storage, retrieval cannot associate correction records for the same case or related clauses of the same policy. Cause: The
chunkSizesetting is too small, splitting the report information and correction information of the same case, or different clauses of the same policy, into different chunks and destroying data association.
How to confirm the configuration is correct
- Upload a single standard infectious disease report card, and check whether the parsed text contains all preset fields, such as case identification, report date, diagnosis type, as well as policy entries in party building materials.
- Test uploading multi-column Excel files, and confirm that the number of parsed table columns matches the source file, with no field omissions.
- Upload a single monthly epidemic analysis report or party building learning package, and verify that the parsing task does not time out, and that chunked text does not break case association information or policy association clauses.
- Enter keywords that combine business and party building content, such as "party building requirements for infectious disease reporting", and confirm that associated chunks containing relevant content can be retrieved.
The values given 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.