What the Data for This Category Looks Like
Ledger data for power generation equipment manufacturing mainly comes from equipment factory inspection reports, daily inspection records, monthly operation and maintenance ledgers, and annual maintenance archives. Data updates follow this rhythm: daily inspections update single-device operating parameters in real time, full-batch equipment ledger summaries are completed monthly or quarterly, and formal maintenance reports are finalized annually.
Document structures include structured tables (fields such as equipment number, model, rated power, and operating duration) and unstructured text paragraphs. Field units include kilowatt (kW), hour, and day. Some documents contain scanned paper ledger files.
Constraints Imposed on Document Parsing and Chunking
Power generation equipment ledgers have a high proportion of structured tables and diverse field units. Parsing processes must retain table structures and unit associations, to avoid separating parameters from their units after chunking.
Long documents and documents with multiple equipment categories require chunks that are not overly fragmented. Overly fragmented chunks break the connection between a single device’s parameters and maintenance records. Chunks also cannot be too long, as this exceeds context window limits.
Mixed document formats of scanned files and native formats require parsing processes to support enhanced parsing, to adapt to complex layouts.
Ledger data has strong interconnections. Chunking must retain context information for equipment groups, to avoid mixing content across devices.
Configuration Settings
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
chunkSize | 800–1200 characters | Power generation equipment ledgers contain both structured parameters for single devices and long sections of operation and maintenance descriptions. This length retains complete information for a single device and avoids semantic fragmentation |
chunkSplitter | Split by paragraph + title | Ledger documents are categorized by equipment and organized by chapter. Splitting by title retains context for equipment groups, and splitting by paragraphs ensures complete semantic content per chunk |
customPdfParse | Enabled | Most power generation equipment ledgers are PDF reports with tables. Enabling this retains table structures and text formatting, and adapts to scanned files and documents with complex layouts |
PARSE_FILE_TIMEOUT_SECONDS | 300–600 seconds | Large annual ledger files have significant size. This duration covers parsing needs for batch files, and avoids parsing interruptions due to timeout |
chunkSettingMode | Manual configuration | Field density and document length vary widely across different equipment ledgers. Manual configuration accurately matches the parsing and chunking needs of this category of documents |
Three Common Configuration Mistakes
- No parsed data appears after uploading a power generation equipment ledger document via a custom link. The cause is either failing to configure the allowed domain whitelist in the document parsing node, or the file format pointed to by the link is not supported by the current parsing rules.
- Fields are misaligned after importing a Word ledger table. The cause is either failing to enable the table retention mode for
chunkSplitter, or the document contains merged cells that cause the parsing logic to split incorrectly. - The model cannot read uploaded files after configuring the document parsing node. The cause is either failing to enable
customPdfParseto adapt to complex formats, or the uploaded file exceeds theUPLOAD_FILE_MAX_SIZElimit.
How to Verify Proper Configuration
- Upload a ledger document for a single device. Check if the parsed text blocks retain complete equipment model, rated power parameters, and single maintenance records, to confirm that chunking does not break semantic connections.
- Test uploading an encrypted PDF or Word document with merged cells. Check that the parsing result has no missing fields or formatting errors, to verify that the
customPdfParseconfiguration takes effect. - Batch upload 5–10 ledger files of different sizes. Check the completion status of parsing tasks, to confirm that the
PARSE_FILE_TIMEOUT_SECONDSvalue matches the current file scale. - Adjust the
chunkSizevalue. Compare the number of text blocks under different chunk lengths, to confirm that the chunk length matches the semantic unit size of the document.
The values provided here 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.