What the Data for This Category Looks Like
Water utility ledger data mainly comes from business systems including pipeline inspection records, water quality monitoring reports, water supply scheduling ledgers, and drainage operation logs. Data update cadence follows daily single-point records generated during routine inspections, monthly and quarterly summary reports, and annual official summary documents. Document structures include three categories: structured tables (with fields such as monitoring point instantaneous flow and turbidity), long-text operation logs, and scanned paper ledger PDFs. Specialized fields and units include pipeline pressure (unit MPa), instantaneous flow (unit m³/h), turbidity (unit NTU), and others.
What Constraints Do These Characteristics Impose on the Document Parsing and Chunking Link
Multiple structured tables and specialized field units require accurate identification of table headers and field mapping to avoid losing data associations after chunking. Long-text operation logs contain specialized water utility terminology. Chunking must preserve context integrity to prevent semantic breaks caused by truncated terms. Mixed-format documents (editable Excel and scanned PDFs) require parsing modes adapted to different file types to ensure text extraction accuracy for non-editable documents. Frequently updated business data requires a stable and efficient parsing process to avoid delays in ledger aggregation caused by timeouts or parsing failures.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
chunkSize | 800–1200 characters | Adapts to the splitting needs of long-text operation logs and structured reports in water utility documents, avoiding truncation of specialized terms or complete data |
chunkSplitter | Split by paragraph + header | Adapts to the mixed structure of water utility documents, preserves the association between table headers and corresponding data rows, and avoids field confusion after splitting structured data |
customPdfParse | Enable OCR mode | Addresses scanned paper inspection ledger PDFs, ensures text extraction accuracy for non-editable documents, and meets the needs of digitizing paper archives in water utility scenarios |
UPLOAD_FILE_MAX_SIZE | 1000 MB | Adapts to batch-uploaded monthly/quarterly water utility summary reports, avoiding system restrictions during large file uploads |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Addresses the full parsing time of large water utility reports, preventing parsing failures due to insufficient default duration |
chunkSettingMode | Manual configuration | Adapts to the mixed structure characteristics of water utility documents, allows flexible adjustment of chunking rules, and avoids using generic default configurations |
Three Common Mistakes
- Phenomenon: After uploading a large monthly water utility summary report, the interface displays a parsing timeout, and the log returns a timeout error. Cause: The
PARSE_FILE_TIMEOUT_SECONDSparameter is not adjusted, and the default short duration is used, which cannot complete full parsing of large reports. - Phenomenon: After uploading a structured Excel ledger, some monitoring point data is empty or fields are missing after importing into the knowledge base. Cause: The
chunkSplitteris not configured to split by header, causing the association between table rows and headers to break, and field mapping relationships are lost during parsing. - Phenomenon: After locally deploying FastGPT v4.17.0, the first parsing works normally, but subsequent file uploads trigger request failures, and restarting the server does not improve the situation. Cause: The model cache relied on by
customPdfParseis not mounted correctly, orUPLOAD_FILE_MAX_SIZEis not adapted to large water utility files, causing the parsing process to exit abnormally.
How to Confirm the Configuration Is Properly Set Up
- Upload a typical water utility inspection log PDF, check whether the parsed text fully retains the associated information of inspection points, times, and fault descriptions.
- Upload a structured Excel ledger, verify that all specialized fields such as pipeline pressure and instantaneous flow are fully present with no null values or missing rows after importing into the knowledge base.
- Upload a monthly summary report larger than 500MB, confirm that the parsing time does not exceed the preset
PARSE_FILE_TIMEOUT_SECONDSparameter value, and no timeout errors occur. - Export the current knowledge base configuration file, check that parameters such as
chunkSizeandchunkSplittermatch the preset configuration, and ensure that the configuration can be migrated stably.
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.