What Data for This Category Includes
The daily documents for this category mainly include purchase orders, arrival acceptance slips, serial number lists, and invoice materials. Data sources mostly come from ERP systems, supplier shipping documents, logistics information, and equipment manufacturer backends. Updates are issued per order or weekly. Each document contains unique fields such as equipment model, serial number, arrival date, and amount. Document formats provided by different suppliers vary widely, including both structured tables and plain text. Some documents include multi-page attachments.
Constraints for Document Parsing and Chunking
The wide variation in document formats, unique dedicated fields, and per-order update rhythm of this category create multiple constraints for document parsing and chunking. First, multi-source, heterogeneous document formats require parsing tools to adapt to multiple forms such as tables and plain text. This avoids missing structured fields. Second, dedicated fields such as equipment serial numbers and models must be fully retained in a single chunk. Splitting these fields would prevent accurate matching during subsequent Q&A. Third, the per-order update rhythm requires the parsing process to quickly adapt to the structure of individual documents. Single-batch arrival documents can be processed without global unified configuration.
How to Set Configurations
The following configurations are based on FastGPT v4.17.0.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
chunkSize | 800–1200 characters | Adapts to the length of individual business units for purchase orders and arrival acceptance slips, avoiding splitting paragraphs containing key fields such as equipment model and serial number |
chunkSplitter | Split by paragraph + title | Matches the paragraph structure of documents in this category, ensuring each business unit (such as acceptance information for a single device) is treated as a complete chunk |
customPdfParse | Enable table recognition mode | Adapts to the table formats of arrival acceptance slips and serial number lists, accurately extracting structured equipment-related fields |
UPLOAD_FILE_MAX_SIZE | 1000 MB | Supports the upload requirement for multiple equipment documents in a single batch, matching the business scenario of project bulk arrivals |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Adapts to parsing long documents exported from large equipment manufacturer backends, preventing timeout failures caused by overly long documents |
chunkSettingMode | Manual configuration | Adjust chunking parameters for different document types such as purchase orders and arrival acceptance slips, adapting to the diverse document formats in this category |
Three Common Configuration Mistakes
- When deploying Qwen3-14B, response fields cannot be extracted from PDF parsing results. Qwen2.5-14B can extract fields normally. Differences exist in the context matching thresholds for structured fields across large models. Failure to adjust the context length after chunking for dedicated fields such as equipment serial numbers and models leads to failure to accurately identify some fields.
- Local environments can parse uploaded files normally. A 404 error is reported during parsing after server deployment. In server environments, the file upload path configuration is not synchronized with the local environment. The parsing node cannot read the actual stored file address, leading to parsing failure.
- The knowledge base cannot complete parsing and chunking after a file is actively pushed by an external system. Configuration related to triggering parsing via external interfaces is not enabled. Only front-end manual uploads support triggering the parsing process. Active push requests from external systems cannot be responded to.
How to Verify Correct Configuration
- A single purchase order PDF is uploaded. The chunking results parsed by FastGPT v4.17.0 are reviewed to confirm that key fields such as equipment model and serial number are not split across different chunks.
- A single long document exported from a large equipment manufacturer backend is uploaded. Parsing is completed, and confirmation is made that no timeout error is triggered.
- After configuring the external push interface, a test file is uploaded via a simulated interface. Confirmation is made that the parsing node can normally read the file and complete chunking.
- Switch between different large models to test field extraction effects. Confirmation is made that target equipment-related fields can be stably extracted after adjusting
chunkSize.
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 2026-10-19.