What this category of data looks like
Ledger data for oilfield engineering services mainly comes from on-site construction daily reports, equipment operation logs, material requisition forms, well site acceptance reports, and other paper or electronic documents. The update frequency ranges from daily to weekly. The main document formats are Excel, PDF, and Word. Some Excel files contain embedded well site layout photos and equipment appearance images. PDF reports include professional parameter tables and hand-drawn annotations. Core fields include well ID, construction period, material model, pressure value (unit: MPa), temperature (unit: ℃), construction team information, and others. There are strong correlations between fields, and context integrity must be maintained when splitting chunks.
What constraints do these characteristics impose on the "document parsing and chunking" link
The presence of embedded images requires the parsing process to support extracting and associating image metadata, to avoid information loss from only extracting plain text. The strong association between professional fields and their units requires that chunks cannot arbitrarily truncate cross-field paragraphs, as this will affect the accuracy of subsequent ledger summarization. Mixed multi-format document sources require parsing tools to support non-standard text elements such as Excel embedded objects and PDF annotations. Frequently updated documents require the parsing process to have stable throughput, to avoid delays in the overall summarization process caused by single-document parsing timeouts.
How to set the configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
chunkSize | 800–1200 characters | Matches the length of core paragraphs in oilfield field ledgers, avoids splitting professional terms and associated fields |
chunkSplitter | Split by title + paragraph | Adapts to the structured layout of ledgers that use well IDs and construction items as titles |
customPdfParse | Enabled | Supports extracting embedded images and handwritten annotations in PDF reports, and generates formatted Markdown content at the same time |
UPLOAD_FILE_MAX_SIZE | 1000 MB | Compatible with multiple construction ledger packages submitted in a single batch |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Adapts to the full parsing time of large Excel/PDF documents |
chunkSettingMode | Manual mode | Allows adjusting chunk boundaries for professional fields, avoiding disruption to data associations |
Reference only; verify against the target FastGPT release and deployment documentation.
Three common mistakes
- Phenomenon: After parsing an Excel file containing embedded images, no image-related information appears in the parsing result. Cause: The
customPdfParseconfiguration is not enabled, or the extraction switch for Excel embedded objects is not turned on. - Phenomenon: When uploading a large PDF acceptance report, the parsing task returns a timeout error. Cause: The value set for
PARSE_FILE_TIMEOUT_SECONDSis lower than the actual parsing time required for the document. - Phenomenon: In the chunked ledger data, a single construction record is split into two separate chunks. Cause: The
chunkSizesetting is too small, truncating the paragraph containing complete fields.
How to confirm the configuration is correctly set
- Upload an Excel ledger file containing well site photos, and check whether the parsing result includes text descriptions or associated metadata of the images.
- Upload a PDF construction report larger than 500 MB, and confirm that the parsing task does not trigger a timeout exception.
- View the chunked result list, and confirm that core professional fields such as well ID and pressure value are not split into different chunks.
- Check the configured value of
UPLOAD_FILE_MAX_SIZE, and confirm that it meets the maximum volume requirement for a single uploaded document.
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.