What this category of data looks like
Fertilizer and pesticide ledger data primarily comes from docx and pdf files exported from production ERP systems, plus scanned paper records of field farming activities. Update frequency: Production ledgers are updated synchronously with daily material withdrawals and completed production batches. Quarterly summary reports are generated monthly. Field records are updated in real time with farming cycles. Document structures include structured tables with fixed headers, plus unstructured long-text analysis reports. Some documents contain nested tables and cross-page content. Core fields include production batch number, active ingredient identifier of raw materials, application dosage, application date. Units for application dosage include kilograms, liters, tons.
What constraints do these characteristics impose on the document parsing and chunking step?
Documents that mix structured tables and nested content require parsing components to distinguish between table and paragraph boundaries, and avoid splitting complete tables across pages. Ledger data with multiple batches and multiple fields requires that chunking preserves the integrity of individual business logic, and avoid merging records from different batches into the same chunk. Large annual reports uploaded in batches require parsing components to support parallel processing and timeout fault tolerance, and avoid interruptions during large file parsing. Scanned pdfs of field records require parsing components to support nested table recognition, and avoid losing detailed content.
Configuration Settings
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
chunkSize | 800–1200 characters | Fertilizer and pesticide ledgers mostly contain complete individual business entries. This range preserves field associations and business logic integrity, and avoids splitting critical information across chunks |
chunkSplitter | Split by paragraph + table boundaries | Tables and text are mixed in ledgers. Following this rule avoids separating table rows from surrounding text, and preserves the integrity of structured data |
customPdfParse | Enable nested table parsing mode | Some quarterly summary reports are scanned pdfs. Enabling this mode recognizes nested raw material withdrawal detail tables, and avoids missing parsed content |
UPLOAD_FILE_MAX_SIZE | 1000 MB | Supports uploading multiple large production ledgers and annual reports in a single batch, and adapts to bulk summary business needs |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Large annual reports take longer to parse. This duration prevents tasks from being interrupted due to timeout |
chunkSettingMode | Manual configuration mode | For the structured characteristics of ledgers, manually adjusting chunking parameters adapts to the need to preserve associations between fixed fields |
Three Common Mistakes
- Phenomenon: Parsed ledgers lack detailed content from nested tables. Logs show no parsing errors, but corresponding fields are empty. Cause: Nested table parsing mode in
customPdfParsewas not enabled. The component cannot recognize nested raw material withdrawal detail tables in docx or pdf files. - Phenomenon: Chunked text blocks contain cross-business irrelevant content. For example, production records from different batches are merged into the same chunk. Cause: Default chunking parameters were used, and
chunkSizeand chunking rules were not adjusted for the fixed business entries in ledgers. - Phenomenon: Some files fail to parse when uploading multiple ledgers in bulk. The interface shows upload success, but no corresponding entries appear in the knowledge base. Cause:
UPLOAD_FILE_MAX_SIZEandPARSE_FILE_TIMEOUT_SECONDSwere not adjusted. Large files exceed the single-file limit, or parsing takes too long and times out.
How to Verify Proper Configuration
- Upload a fertilizer and pesticide production ledger docx containing nested tables. Check if the parsed text includes complete nested table detail content.
- Adjust
chunkSizeto 800 characters. Upload a document containing a single production record. Check if the chunked text preserves complete field associations for the individual business entry. - Enable
customPdfParsemode. Upload a quarterly summary report converted from a scanned pdf. Check if the parsed result includes table content from the original document. - Upload multiple large ledger files. Check if all bulk parsing tasks complete, with no timeouts or missing entries.
The values listed above are common starting points. They should be evaluated against local 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.