What this category of data looks like
This category of data primarily originates from bulk commodity trade contracts, delivery warehouse receipts, customs declaration forms, spot price ledgers, annual trade compliance reports, and similar materials. Update frequency varies by document type: transaction ledgers update daily alongside trades, delivery-related documents update upon completion of individual transactions, and annual reports update on a fiscal year cycle. Document structures combine structured tables (with fields including product name, specifications, quantity, unit price, delivery warehouse, and more, with units mostly being tons, yuan per ton, batch numbers) and long text passages. Some single-page or multi-page PDF files have large file sizes.
What constraints do these characteristics impose on the document parsing and chunking stage?
The mixed structure of structured tables and long text passages requires chunking strategies that balance field relevance and contextual completeness. Large, multi-page PDF files increase parsing time and risk triggering timeouts. The association between specific fields and units requires preserving data context during parsing. Frequently updated transaction ledgers require fast parsing workflows to avoid data lag. Additionally, different types of trade documents (such as quotation sheets, delivery reports) have significant differences, so parsing and chunking parameters need flexible adjustments.
The following configurations apply to FastGPT v4.17.0.
How to set the configurations
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
UPLOAD_FILE_MAX_SIZE | 1000 MB | Accommodates large-volume documents from bulk commodity trade, such as multi-hundred-page delivery reports and annual trade ledgers |
PARSE_FILE_TIMEOUT_SECONDS | 600–900 seconds | Addresses bulk commodity trade documents with many pages per file, avoiding parsing timeouts |
chunkSplitter | Paragraph + fixed character boundary | Adapts to the mixed structure of structured tables and long text in trade documents |
chunkSize | 800–1200 characters | Balances field relevance and contextual completeness in bulk commodity trade documents |
customPdfParse | Enable pdf-marker integration | Improves extraction accuracy for headers, footers, and table content in multi-page PDFs |
chunkSettingMode | Manual configuration | Allows flexible adjustment of chunking parameters for different types of trade documents |
Three common mistakes
- Errors occur when using doc2x to parse hundreds-page PDF files, but the function works normally for tens-page files. The cause is failure to adjust the
PARSE_FILE_TIMEOUT_SECONDSparameter; large file parsing time exceeds the default threshold. - The file parsing function fails after locally deploying FastGPT v4.8.22. The cause is failure to correctly configure the third-party parsing service environment variables corresponding to
customPdfParse, or the service not starting normally. - Parsing large files keeps waiting for results and times out after integrating pdf-marker. The cause is failure to set reasonable
UPLOAD_FILE_MAX_SIZEandPARSE_FILE_TIMEOUT_SECONDSvalues, and failure to enable the parsing queue mechanism.
How to confirm the configuration is correct
- Upload a single bulk commodity trade PDF document with more than 100 pages, check that the parsing status completes within a reasonable time frame, and no timeout errors occur.
- Import a structured trade contract table document, confirm that the parsed result retains the corresponding association between fields such as product name, quantity, and unit price.
- After adjusting chunking parameters, review the contextual completeness of the chunked results, ensuring adjacent chunks cover the complete information of the same trade batch.
- Check the file upload limit, confirm that bulk commodity trade documents larger than the default threshold can be uploaded and parsed normally.
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.