What data for this category looks like
Ledger data for metal material processing primarily comes from production workshop quality inspection records, feeding ledgers, finished product outbound orders, and equipment operation logs. New documents are generated daily or per shift aligned with production batches. Most documents are fixed-format table PDFs, Word files, or PPT files, containing fields such as furnace number, batch number, material grade, mechanical performance indicators, unit weight, and total weight. Common industrial units include megapascals, kilograms, and tons. Some documents include on-site process photos as attachments.
What constraints do these characteristics impose on the "document parsing and chunking" link
Fixed-format table documents require parsers to preserve cell structure, preventing ledger summary errors from misaligned fields. Single document lengths vary widely, from a few lines of tables to dozens of pages with multi-batch data. Chunking processes must avoid splitting complete single-batch data entries. Many industrial-specific units appear in documents, so parsers must retain unit information to prevent unit confusion during subsequent report generation. Some documents include process photos, so systems must extract embedded image text simultaneously to avoid missing key process parameters. High-frequency bulk upload demands require parsers to have stable concurrent processing capabilities.
How to set the configurations
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
chunkSize | 800–1200 characters | Single-batch data entries for metal material processing ledgers are moderately sized. This range fully includes all indicator fields for a single batch, avoiding chunking that splits critical data |
chunkSplitter | Mixed splitting by tables and paragraphs | Documents contain fixed-format tables and a small amount of explanatory paragraphs. Mixed splitting preserves the structural integrity of tables while adapting to paragraph-style explanatory text |
customPdfParse | Enabled | Fixed-format industrial ledger PDFs require enabling custom parsing rules to accurately extract table fields, avoiding cell misalignment caused by general-purpose parsing |
UPLOAD_FILE_MAX_SIZE | 1000 MB | Some PPT documents for batch summaries include multiple process photos, requiring support for larger file uploads while avoiding parsing timeouts from overly large files |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Multi-page long documents require sufficient time for table recognition and text extraction. 600 seconds covers the parsing needs of most single documents |
chunkSettingMode | Manual configuration | The format of metal material processing ledgers is fixed. Manually configuring chunking rules adapts to the unique document structure and improves parsing accuracy |
Three common mistakes
- The symptom is an error "the argument ‘windows-1252’ is invalid encoding" when uploading Word or PPT documents for parsing. The cause is that parsing configurations adapted to industrial document encoding are not enabled, and the general-purpose parsing engine cannot recognize the non-UTF-8 encoding format used in older documents.
- The symptom is that some tasks show a timeout status when uploading multiple ledger documents in bulk. The cause is that the
PARSE_FILE_TIMEOUT_SECONDSparameter is not adjusted, and the default timeout duration is insufficient to complete table recognition and text extraction for multi-page long documents. - The symptom is that calling the document parsing tool in the workflow with a local file address returns an empty result. The cause is that the custom file reading environment variables are not configured correctly, or the passed file address does not have open platform access permissions.
How to confirm the configuration is correct
Reference only; verify against the target FastGPT release and deployment documentation.
- Upload a standard-format metal material processing ledger document, and check if the parsed text fully retains core fields such as furnace number and material grade, with no cell misalignment.
- Adjust the
chunkSizeparameter, then check if the chunking results do not split complete single-batch data entries. This can be verified by comparing the original document and the chunked text content. - Upload a PPT document containing multiple process photos, and confirm that the parsed results include the process parameter text embedded in the photos, with no critical information missing.
- Test bulk uploading multiple ledger documents, and confirm that all parsing tasks are completed within the preset duration, with no bulk timeout errors.
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.