Data Characteristics
Data for autoimmune disease products and reagents comes from various sources. These include in vitro diagnostic (IVD) reagent instructions, product technical manuals, clinical research reports, patent literature, regulatory documents, and academic papers. Data update frequency varies by type. IVD reagent instructions and product manuals typically update with product versions or batch changes. Clinical research and academic papers are continuously published. Documents are often standardized PDFs or Word files. They contain extensive technical terms, abbreviations, charts, and data. Fields and units are highly specific. Examples include antibody titers (IU/mL, U/mL), sensitivity (%), specificity (%), limit of detection (LOD), and limit of quantitation (LOQ). These parameters can differ across products and detection methods.
Constraints on Knowledge Base Retrieval and Recall
The highly specialized nature and standardized structure of autoimmune data challenge knowledge base recall accuracy. Extensive technical terms and abbreviations require models with strong semantic understanding. Models must identify synonyms, near-synonyms, and hierarchical concepts. This avoids recall failures due to insufficient literal matching. Charts and tables in product manuals, if not effectively parsed and vectorized, lead to significant information loss. The cyclical nature of data updates, especially new product manual releases, demands efficient incremental update mechanisms for the knowledge base. This ensures timely recall of information. Furthermore, the specificity of fields and units, such as numerical ranges and specific unit combinations, requires precise matching in retrieval results. This prevents incorrect information due to unit confusion or misinterpretation of values.
Configuration Settings
| Configuration Item | Suggested Value | Rationale |
|---|---|---|
Chunk size (Segment Length) | 800–1200 characters | Ensures each segment contains a complete concept or argument, preventing semantic fragmentation from overly fine splitting. |
Chunk overlap (Segment Overlap) | 100–200 characters | Maintains contextual continuity, improving the completeness of information recall across paragraphs. |
Recall count (Recall Count) | top 8–12 items | Balances coverage with the processing efficiency of the subsequent re-ranking module. |
Similarity threshold (Similarity Threshold) | Calibrate based on actual measurements | Determine by testing recall and precision against the actual corpus and query types. |
Rerank result count (Re-rank Return Count) | top 3–5 items | Filters for the most relevant results, reducing user reading burden and improving information acquisition efficiency. |
UPLOAD_FILE_MAX_SIZE | 500 MB | Accommodates the upload of PDF documents containing numerous charts or high-resolution images. |
Common Pitfalls
- "Unable to read file content" preview after uploading a PDF file: This usually indicates abnormal internal encoding or format in the PDF, preventing the parsing library from correctly identifying the text layer.
- Inability to sync uploaded PPT or PDF files to the knowledge base: This occurs if system configuration does not enable parsing support for these file types, or if the parsing service times out.
- Missing image understanding model option when creating a new knowledge base: This means the relevant configuration item is not displayed in the interface. This typically happens if the deployed version does not support this feature or if related dependencies are not correctly installed.
How to Verify Configuration
- Upload several typical autoimmune product instruction PDFs. Check if file segmentation is reasonable and semantic integrity is maintained.
- Query for specific antibody names, detection indicators, and numerical ranges included in the instructions. Verify that recall results include correct information sources.
- Simulate user consultation scenarios. Use colloquial or non-standard terms in queries. Check the relevance and accuracy of recall results. Adjust the
Similarity threshold(Similarity Threshold) based on the evaluation. - Check if the latest version of IVD reagent instructions in the knowledge base has been successfully synchronized. Ensure the timeliness of new product information.
The values provided are common starting points. Measure them against your own samples to determine optimal settings.
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.