What the data for this category looks like
Infrastructure construction ledger data mostly comes from on-site construction logs, material entry ledgers, process acceptance forms, measurement and payment documents, etc. The data is updated dynamically as construction progresses. The length of individual documents varies widely, ranging from a few pages for material entry slips to dozens of pages for monthly summary reports. The document structure is mainly tables nested with text, containing fields such as construction section, material model, acceptance date, completed project volume, unit price, and others. Units include cubic meters, tons, working hours, ten thousand yuan, and more.
What constraints do these characteristics impose on the document parsing and chunking step
Long-span documents for infrastructure construction ledgers result in poor adaptability with fixed chunk lengths. Too short a chunk length will split associated fields within tables. Too long a chunk length will exceed context limits. The nested table document structure requires the parsing step to retain associations between cells, rows, and columns. This avoids losing data correspondence after splitting. The feature of multiple fields and multiple units requires retaining contextual association within the same ledger during chunking. Cross-field information must not be split into different chunks. Dynamically updated documents require the parsing process to have reusable template adaptation capabilities. This avoids frequent configuration adjustments.
How to set the configurations
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Value Range | Rationale for This Setting |
|---|---|---|
chunkSize | 800–1200 characters | Adapts to the mixed table and text structure of infrastructure ledgers, avoids splitting associated key fields |
chunkSplitter | Table-first mode | Retains the association between table rows, columns, and cells within ledgers, avoids damaging data integrity |
customPdfParse | Enable structured parsing | Adapts to ledger documents with multiple fields and multiple units, extracts standardized fields from tables |
UPLOAD_FILE_MAX_SIZE | 500 MB | Covers the typical size of individual monthly summary ledgers, avoids upload failures |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Adapts to the parsing time required for long documents, avoids mid-process timeout interruptions |
chunkSettingMode | Manual mode | Adjust chunk parameters for different types of ledger documents (such as material slips, progress reports) to improve adaptability |
Three common errors
- Symptom: After uploading an Excel ledger file, the parsing result is empty or fields are misaligned. Cause: The structured table parsing mode of
customPdfParseis not enabled. The default text parsing cannot recognize the row and column association of Excel cells. - Symptom: A timeout error is returned when parsing large monthly summary documents. Cause: The value set for
PARSE_FILE_TIMEOUT_SECONDSis lower than the actual parsing time of the document, and does not adapt to the processing rhythm of long documents. - Symptom: The corresponding relationship between material models and project volume is lost in the chunked content. Cause: The
chunkSizesetting is too small, splitting associated fields within the same table into different chunks.
How to confirm the configuration is correct
- Upload a typical material entry ledger document, check whether the parsed table retains complete rows, columns, and cell content.
- Adjust the chunk parameters, then upload a long document, and check whether the chunked result retains the field association within the same ledger.
- Upload a single large-volume document, confirm that the upload and parsing processes are not interrupted.
- Switch between different types of ledger documents, check whether the parsing mode can adapt to structural differences.
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.