What the Data for This Category Looks Like
Expressway operation document data mainly comes from toll systems, road patrol systems, emergency command platforms, and maintenance management systems. Daily update cycles cover real-time (toll receipts), daily (patrol logs), and irregular (policy notices, maintenance plans). Document types include three categories: structured tables, long-text reports, and standardized official documents. Common fields include road section number, toll amount, patrol time, and responsible disposal personnel. Units involve yuan, kilometers, hours, and others.
Constraints on Document Parsing and Chunking
Improper chunking of structured table documents will split headers from corresponding data rows, leading to field association failure. Long-text patrol reports and emergency response documents have fixed chapter structures. Chunking must retain chapter integrity to avoid splitting key information across chapters. Real-time generated toll receipts and patrol logs have parsing speed requirements. Excessively long documents must limit per-chunk parsing duration. Standardized official documents include fixed header and footer metadata. Parsing must exclude redundant duplicate content while retaining key identifiers such as document numbers and issuing units.
Configuration Settings
| Configuration Item | Recommended Approach | Rationale |
|---|---|---|
chunkSize | 800–1200 characters | Adapts to the per-chunk information density of expressway operation documents, avoiding splitting key business fields or chapters |
chunkSplitter | Split by paragraph + chapter | Adapts to the fixed chapter structure of long-text reports, retaining business logic integrity |
customPdfParse | Enable structured parsing mode | Targets structured PDF documents such as toll receipts and maintenance reports, retaining table field associations |
UPLOAD_FILE_MAX_SIZE | 1000 MB | Meets upload requirements for single large maintenance plans and annual statistical reports |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Meets complete parsing duration requirements for long documents and multi-page PDFs |
chunkSettingMode | Manual configuration mode | Allows adjustment of chunking rules for different document types (tables/long text/official documents), adapting to the multi-category document scenario of expressway operations |
Reference only; verify against the target FastGPT release and deployment documentation.
Three Common Mistakes
- Phenomenon: After passing in an external document link, the parsing result only returns the page title and link information, with no actual business content. Cause: No adaptation rules for web page parsing are configured, or chunking rules do not adapt to dynamically loaded web text content.
- Phenomenon: The document chunk ID in the knowledge base page cannot be copied, and cannot be used for custom index association. Cause: The front-end interface does not enable the copy interaction function for chunk IDs; the corresponding ID must be obtained through the system interface.
- Phenomenon: After custom-chunked documents are stored in the knowledge base, some chunks are missing, and the index order does not match the custom chunking result. Cause: The system's built-in duplicate content deduplication rule automatically deletes duplicate chunks, and does not retain user-defined chunking configurations.
How to Verify Proper Configuration
- Upload a structured toll table PDF, and check if the parsed chunks retain the association between headers and corresponding data rows.
- Upload a long-text emergency response report, and check if chunks are split by chapter without truncating key information across chapters.
- Upload a large maintenance plan document, confirm that the upload size does not exceed the configured limit, and no timeout prompt appears during the parsing process.
- Try clicking the document chunk ID area in the knowledge base page, and confirm that the copy interaction option appears.
The configuration values provided are common starting points, and should be evaluated 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.