Data Profile for This Category
Data for this category originates from China’s national government procurement websites, local government procurement websites, fiscal integration systems, procurer budget systems, and supplier credit records, with a daily update cadence. Commonly processed documents include procurement requirements, procurement plans, bidding documents, tender submissions, bid evaluation reports, winning bid announcements, procurement contracts, and inquiry responses. Most document structures include fixed fields such as project number, budget amount, supplier qualification requirements, and scoring rules. Some documents feature multi-chapter nested formatting.
Constraints for Document Parsing and Chunking
The daily updated volume of standardized documents requires parsing and chunking workflows to adapt to multiple official government procurement formats, and avoid omitting core fields such as project number and budget amount. Multi-chapter nested document structures require chunking logic to retain contextual connections, preventing associated content like scoring rules and qualification requirements from becoming disconnected after splitting. Structured data such as supplier credit records must be processed separately from unstructured procurement documents to ensure consistent priority of core business fields during retrieval. Regulatory requirements for document integrity also demand that complete clause associations are preserved during chunking, to avoid losing key information related to bid disqualification due to improper splitting.
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 content length of single chapters such as procurement requirements and scoring rules in government procurement documents, avoiding splitting core business clauses |
chunkSplitter | Separate by paragraph + heading | Matches the multi-heading nested structure of government procurement documents, retaining contextual association logic between chapters |
customPdfParse | Enable official format adaptation | Adapts to PDF bidding document formats released by China’s government procurement websites, accurately extracting tables and hierarchical headings |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Addresses parsing time for large bid evaluation reports and tender submissions, avoiding interrupting the parsing process due to timeout |
chunkSettingMode | Manual configuration | Adjusts chunking parameters for different types of government procurement documents such as announcement notices and contracts, adapting to differentiated content structures |
Three Common Configuration Errors
- Phenomenon: Core business fields (such as project number and budget amount) are not prioritized over auxiliary content during retrieval, leading to search results that do not align with business needs. Cause: No chunking priority rules are configured for the fixed fields of government procurement documents, and default chunking does not differentiate between core and auxiliary data.
- Phenomenon: Abnormal search results occur after uploading locally chunked files to the server. Cause: No unified adaptation rules are set between the vector model and chunking logic, and differences in vector spaces across models cause chunked data to fail normal matching.
- Phenomenon: Parsed documents do not retain original formatting in context references, resulting in layout inconsistencies. Cause: The format retention configuration for
customPdfParseis not enabled, leading to loss of structured tables and heading hierarchies.
How to Verify Correct Configuration
- Upload a typical government procurement bidding document, review the parsed chunked content, and confirm that core clauses are not incorrectly split.
- Compare chunking results across different document types, such as winning bid announcements and procurement contracts, to confirm the chunking logic adapts to the structural characteristics of each document type.
- Test uploading a large bid evaluation report, confirm that the parsing process does not trigger timeout errors, and that all chapter content is fully extracted.
- Verify the formatting of context references, confirming that heading hierarchies and table content are displayed according to the original document structure.
The provided values are common starting points, and should be evaluated against applicable local 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.