What the data for this category looks like
Documents related to internal office and employee services for power grid enterprises come from sources including internal operation and maintenance logs, safety work procedures, employee training manuals, power grid dispatch records, and repair work order documents. Update frequency aligns with business process updates, regulatory specification revisions, or monthly archiving. Document structures include structured text with fixed business fields, long-form procedure documents, and operation and maintenance reports with tables. Fields include work order number, voltage level, maintenance duration, and similar items. Units include kilovolts, hours, person-times, and similar units.
What constraints these characteristics impose on document parsing and chunking
Long-form procedures and dispatch records require chunking that retains complete business semantics. Avoid splitting content that breaks logical connections of individual work items or procedures. Operation and maintenance reports with tables require the parsing stage to retain original layout and field correspondence. Otherwise, subsequent retrieval loses data associations. Large annual log-style documents have large file sizes, raising higher requirements for upload and parsing limits. Multiple document types exist together, requiring flexible adjustment of chunking rules to adapt to different document structures.
How to Set Configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
chunkSize | 800–1200 characters | Power grid internal procedures and work order documents are mostly long-form text. This range retains complete semantics of individual work items or procedures. |
chunkSplitter | Split by paragraph + heading | Power grid documents mostly have hierarchical headings and structured paragraphs. This preserves business logical connections. |
customPdfParse | Enabled | Power grid internal documents are mostly compliant PDFs with tables and annotations. Enabling this retains original layout and field information. |
UPLOAD_FILE_MAX_SIZE | 1000 MB | Large documents such as annual operation and maintenance logs may exceed standard upload limits. |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Long document parsing requires longer processing time to avoid mid-process timeouts. |
chunkSettingMode | Manual configuration | Power grid documents have large type differences. Manual configuration adapts chunking requirements for different scenarios. |
Three Common Mistakes
- Symptom: A boolean parameter returned by the HTTP component becomes empty after being received by the conditional judgment component. Cause: The parsing format of returned data was not explicitly specified in the HTTP component, causing the boolean value to be incorrectly converted or have its type lost.
- Symptom: Parsing timeout errors occur when parsing large power grid operation and maintenance documents. Cause: The
PARSE_FILE_TIMEOUT_SECONDSconfiguration was not adjusted based on document length. The default duration is insufficient for long document parsing. - Symptom: The number of chunks per file after knowledge base splitting exceeds the threshold, making storage into the knowledge base impossible. Cause: The original file was not split in advance according to document content logic, or the chunking configuration was not adjusted to adapt to the chunk count limit for large documents.
How to Confirm Configuration is Properly Set
- Upload a typical power grid safety procedure PDF, and check if the text parsed by FastGPT v4.17.0 retains heading hierarchy and table content.
- Manually set
chunkSizeto 800–1200 characters, generate a chunking preview, and confirm that single chunk length meets expectations. - Check the
UPLOAD_FILE_MAX_SIZEconfiguration, upload the largest internal enterprise document, and confirm that the upload and parsing process is not interrupted. - Simulate the component flow for boolean type parameter transfer, and confirm that parameters are not lost or have type errors during transfer.
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.