Data Characteristics for This Category
Imaging equipment registration and declaration materials originate from diverse sources. These include product technical requirements, registration inspection reports, clinical evaluation reports, instruction manuals, labels, and manufacturing information. Document updates typically align with product lifecycles and regulatory changes; for example, technical requirements may be revised during product iterations or regulatory updates. Document structures are complex, often containing numerous charts, images, and scanned documents. Text content involves detailed technical parameters, performance indicators, safety standards, and operating procedures. Fields and units are highly specialized, such as "spatial resolution" (lp/mm), "signal-to-noise ratio" (dB), and "dose area product" (Gy·cm²), demanding extreme precision and consistency.
Constraints Imposed by These Characteristics on "Document Parsing and Chunking"
The complexity of imaging equipment declaration materials directly impacts document parsing accuracy. Extensive charts and image content require advanced visual recognition capabilities; traditional text parsing methods are insufficient for extracting complete information. The presence of scanned documents increases OCR error rates, especially for tables and specialized terminology. Although the update frequency is not high, each update may involve revisions to core technical parameters. This requires the knowledge base to accurately identify and update relevant information, preventing interference from outdated data. The sensitivity of specialized fields and units means that chunking must maintain the integrity of this critical information. This avoids loss of meaning or misinterpretation due to splitting, for example, splitting "spatial resolution 5 lp/mm" into "spatial resolution" and "5 lp/mm" loses its complete context.
Configuration Settings
| Configuration Item | Suggested Value | Rationale for This Value |
|---|---|---|
Chunk size (Chunk Length) | 500–800 characters (characters) | Balances contextual completeness with recall efficiency, ensuring specialized terms and associated parameters are not truncated. |
Overlap Length | 50–100 characters (characters) | Ensures contextual continuity between adjacent chunks, handling specialized descriptions that span paragraphs. |
Enabled OCR (Enable OCR) | Yes | Declaration materials contain numerous scanned documents and text within images; OCR must be enabled for extraction. |
Parsing Timeout | 600 seconds (seconds) | Accounts for the processing time of images and tables within documents, especially large PDF files, requiring a longer parsing duration. |
Image Parsing Model | vlm-standard | Ensures accurate recognition of key information in professional images such as imaging equipment structural diagrams and waveform diagrams. |
Max File Size | 200 MB | Declaration materials often include multiple attachments and high-resolution images, leading to large individual file sizes. |
Three Common Mistakes
- Uploading large PDF files results in a long period of unresponsiveness or a
504 Gateway Timeouterror: This occurs because the default parsing timeout is insufficient to process documents containing numerous images or complex layouts. - The knowledge base is missing certain critical technical parameters or chart descriptions: This happens when OCR is not enabled or an appropriate image parsing model is not configured, preventing effective extraction of text content from images.
- Recall results for a specific device model contain incomplete or vague parameter information: This can occur if the
Chunk size(Chunk Length) is too short, splitting complete technical parameter descriptions into incomplete fragments.
How to Confirm Correct Configuration
- Randomly select 5–10 representative imaging equipment declaration documents, upload them to the knowledge base, and verify that the parsing status for each document displays "successful" (Success).
- For successfully parsed documents, randomly select 3–5 chunks. Verify that the chunk content completely includes key technical parameters, specialized terminology, and their units. Check for any obvious chunking errors.
- Use the knowledge base's search function to query for specific image information, such as "X-ray tube voltage range." Verify that the system accurately recalls chunks containing relevant image descriptions.
- Compare tabular data in the original documents with the text content of corresponding chunks in the knowledge base. Ensure that values and units in tables are correctly identified and stored.
The values provided are common starting points. Measure them against your 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 2026-09-21.