What data for this category looks like
Data for this category originates from centralized treasury payment systems, unified budget management systems, electronic invoice platforms, and contract management systems. Updates occur daily. Processed documents include payment applications, fund appropriation plans, invoices, contracts, acceptance receipts, reimbursement approval slips, and payment vouchers. Most documents contain structured fields such as economic classification codes, budget indicator quotas, and payment amounts, plus multi-level text from approval workflows. Some documents have nested multi-level directories and attachments.
What constraints do these characteristics impose on document parsing and chunking
Daily batch document updates require the parsing process to deliver stable processing efficiency and fault tolerance. Single-document parsing timeouts must not disrupt overall ledger summarization progress. Multiple document types include structured fields and multi-level approval text. When chunking, the association between fields and context must be retained. This prevents loss of key associated information such as economic classifications and budget indicators after splitting. Documents with nested multi-level directories must avoid incorrect merging of cross-level content. The process must also be compatible with differences in document formats exported by different systems. This ensures that text and table content of all types of vouchers can be accurately extracted and chunked.
How to set configurations
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
chunkSize | 800–1200 characters | Adapts to the mixed length of structured fields and approval text in documents of this category, avoiding splitting of key associated information |
chunkSplitter | Chunk by paragraph + heading | Retains contextual associations of multi-level directories and approval workflows, aligns with the logical structure of documents |
customPdfParse | Enable built-in parser | Compatible with fixed-format PDF vouchers exported from fiscal systems, avoids extraction bias of structured fields by third-party parsers |
UPLOAD_FILE_MAX_SIZE | 100 MB | Meets size requirements for large single documents such as contracts and acceptance receipts uploaded in batches |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Meets time consumption requirements for parsing large multi-attachment documents, avoids parsing failure due to timeout |
chunkSettingMode | Manual configuration | Flexibly adjusts chunking rules and parameters for the mixed structure of documents in this category |
Reference only; verify against the target FastGPT release and deployment documentation.
Three common misconfigurations
- Phenomenon: After uploading a Feishu multi-level directory document, search results only include the top-level heading, and subdirectory text is not parsed. Cause: Nested document recursive parsing configuration is not enabled, and sub-level content is not traversed during chunking.
- Phenomenon: When using marker to parse documents, logs report split-related exceptions, and the chunking step cannot be completed. Cause: The
chunkSizeconfiguration value does not match the actual length of long text in the document, causing the chunking logic to trigger an exception. - Phenomenon: In a Docker-deployed FastGPT instance, the file parsing module does not receive uploaded document files, and parsing fails after upload. Cause: Network connectivity between the parsing module and the main service is not properly configured, causing the file transfer link to be interrupted.
How to confirm configurations are correctly set
- Upload a typical reimbursement approval slip PDF for this category. Check if the parsed text includes key fields such as economic classification and budget indicators, and confirm that no fields are missing.
- Upload a document containing a multi-level approval workflow. Check if the chunked content is split by approval nodes, with no cross-node content merging.
- Upload a contract document larger than 50 MB. Confirm that the parsing process does not trigger a timeout error, and that the full document content is returned.
- Call the file parsing API to upload a test document. Check if the returned result includes complete chunked text, with no empty fields or missing content.
The values provided 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.