What the Data for This Category Looks Like
Ordnance equipment-related data used for financial sector marketing and customer acquisition is sourced from official development entity manuals, public test reports, marketing promotional materials, and bidding technical documents. Update cycles are irregular, aligned with new equipment finalization and marketing campaign milestones. Most documents take the form of PDF-format technical descriptions, long-text scenario cases, and XLSX-format parameter summary tables. Fields include equipment model, performance parameters such as range and rate of fire, compliance standards, and application scenarios. Most parameters include clear physical units.
Constraints Imposed on Document Parsing and Chunking
Ordnance equipment-related documents used for financial sector marketing and customer acquisition require that long technical description paragraphs in official manuals not be split between specialized term combinations, to ensure complete presentation of parameter descriptions. XLSX-format parameter summary tables have multi-row and multi-column structures, so the parsing tool must accurately identify row and column associations to prevent parameter misalignment and confusion. Irregularly updated documents have large layout variations, so parsing logic must adapt to variable formats. For marketing scenarios, performance parameters and application scenarios must be prioritized as independent chunk units, to facilitate subsequent precise matching of financial customer inquiry needs.
Configuration Settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
PARSE_TABLE_MODE | merged cell recognition mode | Ordnance equipment marketing document parameter tables often use merged cells to link models and performance parameters, which ensures complete table parsing |
chunk_size | 800–1200 characters | Ensures complete specialized term paragraphs, while adapting to the information density of marketing content, avoiding overly fragmented or overly long chunks |
UPLOAD_FILE_MAX_SIZE | 500 MB | Adapts to the characteristics of ordnance equipment documents that often include high-definition images and long text, preventing large file uploads from being blocked |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Reserves sufficient time to complete format recognition, content extraction, and chunking operations for long documents |
enable_document_sourcing | enabled | Financial sector marketing content requires clear parameter sources to enable users to verify information authenticity and meet compliance requirements |
table_chunk_strategy | split by row + bind header | Each row of an ordnance equipment parameter table corresponds to an independent performance item. Binding headers preserves the association between parameters and models |
The parameter values provided on this page are common recommended starting points for configuration. Actual values are affected by material format, data volume, and business rules. Specific issues require individual analysis. It is recommended to test on your own samples before finalizing settings.
Three Common Mistakes
- Issue: When processing ordnance equipment PDF marketing documents, the interface displays parsing failure and returns
{"detail":"Parsing timed out"}. Cause: The document parsing tool’s environment variables were not configured correctly, or insufficient computing resources were reserved during deployment to complete long document parsing. - Issue: After importing an XLSX-format ordnance equipment parameter table, some performance parameter fields are missing. Cause: The merged cell recognition configuration was not enabled, causing merged headers that link models and parameters in the table to fail correct identification.
- Issue: Knowledge base recall results do not include source document traceability information. Cause: The document traceability switch was not enabled, and no association mapping was established between chunked content and the original document.
How to Verify Correct Configuration
- Upload a typical ordnance equipment PDF marketing document, and check if the parsed chunked content retains complete specialized term paragraphs, with no forced splits between term combinations.
- Import an XLSX parameter table that includes merged cells, and verify that the parsed table data matches the row and column associations of the original document.
- After enabling the document traceability function, initiate an inquiry related to parameters, and verify that the recall results include identification information for the corresponding source document.
- Adjust the chunk length parameter, upload a long-text document, and confirm that the character count of chunks falls within the preset value range.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-09-14.