What Data for This Category Looks Like
Documents for internal office and employee services for urban water utilities come primarily from pump station operation logs, pipeline inspection reports, water quality test reports, internal approval process documents, and employee operation and maintenance training manuals. Update frequency varies by business type:
- Inspection logs are updated per shift or daily
- Water quality test reports are updated weekly or monthly
- Annual operation and maintenance summaries are updated annually
Document structures include multi-row tables, on-site topology diagrams, device photos, and long text with hierarchical headings. Fields include exclusive business identifiers such as device number, pipeline segment number, and test value unit.
Constraints Imposed on Document Parsing and Chunking
Document structures with multiple tables and images require parsing to retain structured content. Without this, subsequent retrieval cannot match complete business logic. Long text documents need reasonable chunking to fit context windows, to avoid overloading single chunks. Accurate identification of exclusive business fields depends on adapted parsing rules. Without this, field omission or association errors may occur. Frequently updated business documents require parsing speed to match their update rhythm. Parsing timeouts will cause data import delays. Differences in content density across document types require chunking rules to have flexible adjustment space.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
chunkSize | 800–1200 characters | Urban water utility documents often include tables and long sentences. This range preserves complete single business logic, such as a single set of water quality test data or a single section of inspection records |
chunkSplitter | Split by paragraph + heading | Water utility documents have clear chapter divisions. Splitting by heading preserves business context and avoids mixing content across chapters |
customPdfParse | Enabled | Adapts to the structure of water utility documents with multiple tables and topology diagrams, retains table rows and columns and image association information, and avoids scattered content |
UPLOAD_FILE_MAX_SIZE | 1000 MB | Covers the common file size of single annual operation and maintenance summaries or pipeline topology image collections, and avoids upload failures |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Matches the parsing time required for large-volume water utility documents, and avoids parsing task failures due to timeouts |
chunkSettingMode | Manual mode | Supports adjusting chunking parameters for different document types such as inspection logs and water quality reports, to adapt to exclusive business fields |
Three Common Misconfigurations
- Phenomenon: Table content in imported Word documents is split into scattered text, and images have no associated descriptions. Cause: The
customPdfParseconfiguration is not enabled. The default parsing process does not retain structured content for water utility documents that include tables and images. - Phenomenon: When importing inspection logs in bulk, some documents fail parsing with a timeout error, and the task status shows failed. Cause: The
PARSE_FILE_TIMEOUT_SECONDSsetting is too low, and does not match the actual parsing time required for water utility documents. - Phenomenon: Changes to chunking parameters do not take effect, and imported documents still use the default chunking rules. Cause: The
chunkSettingModeis not switched to manual mode, and the initial automatic chunking configuration remains in use.
How to Verify Proper Configuration
- Upload a Word document that includes water quality test tables and pipeline topology diagrams, and confirm that the parsed content retains table row and column structures and image descriptions.
- Access the FastGPT v4.17.0 backend configuration page, and check that the values of parameters such as
chunkSizeandcustomPdfParsematch the preset configuration. - Import a document with a file size close to
UPLOAD_FILE_MAX_SIZE, and confirm that the parsing task does not trigger upload failure or timeout errors. - For exclusive documents that include pipeline segment numbers and device numbers, verify that parsed fields are fully retained with no omissions or misplacements.
The values given 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.