Reference only; verify against the target FastGPT release and deployment documentation.
What this category of data looks like
Ledger and report data in the grain reserve field mainly comes from daily inspection records of grassroots grain depots, grain in-warehouse and out-warehouse documents, inventory check ledgers, and quality inspection reports. Data update cadence follows business processes: in-warehouse and out-warehouse data updates daily, quarterly and annual inventory data syncs on fixed cycles. Most documents are structured tables or fixed-format forms, with fields including depot code, grain type, stored quantity, quality inspection grade, storage period, and batch number. Units are mostly tons, kilograms, and batch numbers. Some documents include paper scans or PDF files with electronic signatures.
What constraints these characteristics impose on document parsing and chunking
Fixed field order for structured table documents requires retaining contextual association during chunking, and avoids splitting cross-row and cross-column business combined fields. Electronic signed paper scan PDFs need support for signature area parsing to prevent loss of critical credential information. Daily high-frequency updated in-warehouse and out-warehouse data requires chunk processing adapted to batch upload scenarios, and avoids timeout blocking. Fine-grained ledgers with multiple fields need to retain semantic association of adjacent fields during chunking, and avoids splitting business logic during retrieval. Exclusive quality inspection fields for different grain types must be bound to document content, and prevents cross-category retrieval confusion.
Configuration settings
| Config Item | Recommended Setting | Rationale |
|---|---|---|
chunkSize | 800–1200 characters | Adapts to the number of single-page table fields and semantic length of ledgers, avoids splitting cross-business field combinations |
chunkSplitter | Table line break + fixed delimiter | Matches the table structure of structured ledgers, retains the integrity of each row of fields |
customPdfParse | Enable signature area recognition mode | Adapts to paper scan PDF documents with electronic signatures, avoids losing credential metadata |
PARSE_FILE_TIMEOUT_SECONDS | 120 seconds | Adapts to batch uploads of multiple ledger documents, avoids parsing timeout for large single files |
chunkSettingMode | Manual mode | Adjusts chunking rules for exclusive fields of different grain types, adapts to segmented business scenarios |
Three common errors
- Phenomenon: Chunking results include field splits across table rows, leading to broken business logic during retrieval. Cause: No chunking delimiter configured for structured documents, only the default general line break rule is used.
- Phenomenon: Unrendered Markdown format tags appear in context references, with fields displayed as raw code format. Cause: The text formatting switch in custom PDF parsing is not enabled, resulting in parsed documents retaining original typesetting tags.
- Phenomenon: Parsing timeout-related errors occur when batch uploading ledger documents. Cause: The
PARSE_FILE_TIMEOUT_SECONDSparameter is not adjusted, and using the default value causes parsing failure of large quarterly inventory PDF documents.
How to confirm correct configuration
- Upload a single structured ledger PDF, check the chunking preview interface, and confirm that fields of adjacent table rows are not split.
- Upload a document with an electronic signature, verify that the signature area in the parsing result is correctly identified and retained.
- Batch upload multiple ledger documents of different grain types, confirm that no timeout errors occur in parsing tasks.
- Conduct retrieval tests on documents, confirm that fields in context references are displayed as plain text, with no unrendered format tags.
The values provided 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.