What the Data for This Category Looks Like
This category’s data primarily originates from China’s national government procurement website, local government procurement websites, fiscal integration systems, purchaser budget systems, and supplier credit records. The update frequency is daily. Commonly processed documents include procurement requirements, procurement plans, bidding documents, tender documents, bid evaluation reports, winning bid announcements, procurement contracts, and response to bidder inquiries. Most documents contain fixed fields such as project numbers, budget amounts, supplier qualification requirements, and scoring rules. Units involved include ten thousand yuan, item, batch, and others. Document structures vary significantly; for example, bidding documents include two parts: general terms and special terms.
Constraints Imposed by These Characteristics on Document Parsing and Chunking
Mass documents updated daily require parsing and chunking workflows to have stable batch processing capabilities to avoid timeouts. Diverse types and widely varying structures of government procurement documents require adaptation to the fields and formats of different documents, to prevent chunking from destroying the integrity of key content such as procurement requirements and scoring rules. The presence of fixed fields requires retaining field associations during chunking, to avoid splitting that breaks the link between project numbers and corresponding budget information. Supplier credit records are mostly structured tables; parsing must accurately identify sheet pages and table content to avoid missing key qualification information. When processing time-sensitive documents such as response to bidder inquiries, chunking must retain contextual associations to ensure large models can fully understand the inquiry content and response basis.
Configuration Settings
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
chunkSize | 800–1200 characters | Adapts to the semantic integrity of long text such as procurement requirements and scoring rules in government procurement documents, avoiding splitting of key clauses |
chunkSplitter | Chunk by paragraph + heading | Matches the structure of government procurement documents organized by chapter and clause, retaining contextual associations |
customPdfParse | Enable OCR mode | Adapts to non-editable PDFs such as scanned bidding documents and tender documents, accurately extracting text content |
UPLOAD_FILE_MAX_SIZE | 100 MB | Adapts to batch-uploaded procurement project document packages, avoiding upload failures due to oversized files |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Addresses parsing time requirements for large bid evaluation reports and supplier credit tables with multiple sheets |
chunkSettingMode | Manual configuration | Adjusts chunking rules for different types of government procurement documents, adapting to differences between structured tables and unstructured text |
Three Common Mistakes
- After uploading a scanned government procurement bidding document, the parsing result is empty or only contains a small amount of garbled text. The cause is that the OCR mode of
customPdfParseis not enabled, so text in scanned images cannot be recognized. - When parsing a supplier credit Excel file with multiple sheets, only the content of the first sheet is extracted, and data from other sheets is missing. The cause is that sheet-by-sheet chunking is not configured or the multi-sheet table recognition logic is not enabled.
- After uploading a procurement requirements document with images and text, the parsing result only retains text content, original images are lost, and no corresponding image placeholders are generated. The cause is that forced OCR mode is enabled, and the extraction path for original images is not retained.
How to Verify Proper Configuration
- Upload a scanned government procurement bidding document, check whether the parsing result contains complete text content, to confirm that the OCR mode has taken effect.
- Upload a supplier credit Excel file with multiple sheets, check whether the parsing result contains table content from all sheets, to confirm that the chunking rules adapt to multi-sheet documents.
- Upload a procurement requirements document with images and text, check whether the parsing result retains original images or corresponding placeholders, to confirm that the image extraction logic has been correctly configured.
- Batch upload government procurement documents, check the completion status of parsing tasks, to confirm that the timeout setting and file size limit adapt to batch processing requirements.
The values provided are common starting points and should be evaluated against samples relevant to 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.