What Data for This Category Looks Like
This category of data originates from manufacturing enterprises’ PLM, ERP, MES, supplier materials, validation tests, and customer-specific requirements. A change management team composed of R&D, process, quality, production, and procurement personnel maintains this data. Daily documents include ECN/ECR, change assessments, drawings and BOM versions, process validation reports, switching plans, inventory disposal documents, and customer approval documents. Each change triggers an update, following an irregular schedule. Documents include specific fields such as change number, version number, impact scope, and approval status. Their structures cover structured forms, complex tables, and technical drawings. FastGPT v4.17.0 supports custom adjustments for all the above configuration items.
Constraints on Document Parsing and Chunking
Multi-source formats and specific field requirements of documents in this category create multiple constraints for parsing and chunking. Structured change documents must retain the association between change numbers and approval opinions. Complex BOM tables must avoid splitting material codes and their corresponding usage quantities. Technical drawings must accurately extract version annotations. Documents from multiple systems have large format differences; the platform must adapt to multiple carriers such as PDF, Excel, and Word. Irregular change updates allow parsing rules to be adjusted flexibly, without requiring reconfiguration for each change. At the same time, chunked content must cover associated information at new version switching points, to provide complete context for subsequent quality traceability.
How to Configure Settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
chunkSize | 800–1200 characters | Adapts to the paragraph length of ECN/ECR documents, retaining complete associated information such as change reasons and impact scope |
chunkSplitter | Split by paragraph + heading | Adapts to the hierarchical structure of change documents, avoiding splitting change numbers and their corresponding approval opinions |
customPdfParse | Enabled | Accurately parses structured content such as drawing annotations and BOM tables, preventing loss of version number fields |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Compatible with the parsing duration of large process validation reports, preventing timeout interruptions |
UPLOAD_FILE_MAX_SIZE | 1000 MB | Supports uploading complete drawing sets and BOM version files |
chunkSettingMode | Manual configuration | Adjusts chunking rules for different document types (such as PDF drawings, Excel BOMs) to adapt to specific fields of change management |
Three Common Misconfigurations
- Phenomenon: Files uploaded via the create file collection API show inconsistent chunking results compared to files uploaded directly via the platform. Cause: The API upload did not specify the
chunkSettingModeparameter, using the platform's default general chunking rules which do not match the category-specific manually configured rules. - Phenomenon: No data is returned when configuring custom URL parsing. Cause:
customPdfParsewas not enabled to adapt to non-standard web-format change documents, or the file corresponding to the URL does not contain the structured fields required for change management. - Phenomenon: The model cannot read the uploaded parsed files. Cause:
chunkSizewas set too small, splitting change numbers and approval opinions into different chunks, leading to broken context association and preventing the model from matching complete change logic.
How to Confirm Successful Configuration
- Upload a typical ECN document, check that the parsed chunks retain complete change numbers and impact scope paragraphs, with no forced splitting of key associated information.
- Compare the chunking results of the same document uploaded via API and directly via the platform, confirming that both use consistent chunking rules.
- Submit a large process validation report, check that the parsing process does not experience timeout interruptions and that all validation data in the report is fully extracted.
- Test the custom URL parsing function, confirming that change-related content in the target document can be extracted normally.
The values provided are common starting points and should be measured against the reader's own samples.