What this category’s data looks like
Core data for this category typically comes from ERP, WMS systems, barcode or RFID devices, purchase work orders, storage location records, AGV transport systems and weighing equipment. Daily documents include receiving slips, putaway slips, material picking and return slips, warehouse transfer slips, inventory checklists, lot ledgers, first-in first-out and expiration date records, and similar materials. These include both structured forms and ledgers, as well as semi-structured logistics logs. Data update cycles cover real-time, daily summaries and monthly inventory counts. Core fields include material codes, lot numbers, storage location numbers, expiration dates, quantities and associated work order information. Some documents require matching cross-process material locations and statuses.
Constraints on Document Parsing and Chunking
The heterogeneity of data sources requires the parsing module to support extraction across different document formats, and avoid missing hidden fields in structured forms and line-by-line records in semi-structured logs. Differences in update cycles mean chunking strategies must adapt to both high-frequency updates of real-time logistics data and large-capacity content from monthly inventory checklists, to prevent over-chunking or under-chunking. The interconnected nature of core fields requires retaining material, storage location and expiration date information for the same lot during chunking, to avoid losing association after splitting. The business’s high requirement for field completeness means parsing failures or missing fields will directly affect material completeness verification in tender quotations, so exception capture and completion mechanisms need to be strengthened.
How to Configure Settings
These configurations are written for FastGPT v4.17.0.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
chunkSize | 800–1200 characters | Adapts to the field density of structured forms and ledgers for this category, and avoids splitting associated information for the same lot |
chunkSplitter | Split by paragraph + heading hierarchy | Adapts to receiving slips and lot ledgers with multi-level directories, and retains document structural associations |
customPdfParse | Enable structured PDF parsing mode | Adapts to PDF forms exported from ERP systems, and accurately extracts core fields such as material codes and lot numbers |
PARSE_FILE_TIMEOUT_SECONDS | 300–600 seconds | Covers parsing time for monthly inventory checklists and large lot ledgers, and avoids timeout interruptions |
UPLOAD_FILE_MAX_SIZE | 1000 MB | Adapts to upload requirements for large lot ledgers or multi-lot summary documents |
chunkSettingMode | Manual configuration mode | Adjust chunking parameters for different document types (such as real-time logistics slips and monthly inventory checklists) to meet differentiated needs |
Three Common Misconfigurations
- Symptom: When parsing a multi-level directory lot ledger document, only the top-level directory content is retrievable, and lower-level subdirectory entries are missing. Cause: The chunking rule split by heading hierarchy was not configured, so subdirectory content was not included in the parsing scope.
- Symptom: Calling the API to upload a material picking and return slip PDF returns success, but no material lot field data is present in the parsing results. Cause: The
customPdfParsestructured parsing mode was not enabled, so embedded fields in the PDF form could not be extracted. - Symptom: When parsing logistics logs exported from an AGV transport system, split-related errors are displayed in the log, and the parsing task fails. Cause: The
chunkSizesetting is too small to accommodate the complete field group of a single logistics record, triggering a chunking exception.
How to Confirm the Configuration is Correct
- A lot ledger document with multi-level directories is uploaded, and parsed chunked content is verified to cover all subdirectory entries.
- A structured PDF receiving slip is uploaded via the API, and core business fields such as material codes and lot numbers are verified to be included in the returned results.
- A monthly inventory checklist of around 500 MB is uploaded, and confirmation is made that no timeout error is triggered during parsing.
- The
chunkSizeparameter is adjusted, field integrity is compared across different chunk lengths, and the configuration matching business needs is selected.
The values listed here are common starting points, and should be evaluated against the reader’s own sample documents.