Data Characteristics
IVD diagnostic reagent regulations and SOP documents primarily source data from regulatory files, industry standards, internal quality management system documents, product instructions, and registration approval materials. Policy regulations, technological advancements, and product lifecycle management influence document update frequency. Updates typically occur quarterly or annually, with critical standards potentially revised at any time. Documents are mostly PDF or Word format, containing numerous charts, flowcharts, and specialized terminology. Sectioning is clear, with well-defined hierarchical relationships. Fields and units include batch numbers, expiration dates, storage conditions (e.g., 2-8℃), testing methods, judgment criteria (e.g., OD value, Ct value), quality control product concentrations (e.g., 10ng/mL), and reaction times (e.g., 30min). Units are precise and industry-specific.
Constraints Imposed by Data Characteristics on Workflow Orchestration
The characteristics of IVD diagnostic reagent regulation data impose specific requirements on workflow orchestration. Document updates, though infrequent, may involve critical clause revisions. This necessitates version management and incremental update capabilities in the workflow to ensure knowledge base timeliness. Complex document structures and numerous charts mean traditional text chunking methods are insufficient. Enhanced parsing capabilities for rich text content are required to extract key information correctly. Specialized terminology and precise field units challenge model comprehension and answer accuracy. The workflow needs to incorporate glossaries or domain-specific dictionaries for enhancement. For example, a query for OD value requires the workflow to recognize it as optical density and link it to corresponding judgment criteria. Furthermore, the rigor of regulations and standards demands high traceability and accuracy for question-answering results. The workflow must support citing original sources and handle cross-references across multiple documents.
Configuration Guidelines
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
Chunk Length | 800–1200 characters | Balances semantic completeness and retrieval efficiency. Avoids dilution of key information in long texts or loss of context in short texts. |
Recall Count | Top 5 | Considering the precision requirements of regulatory Q&A, too many items can introduce noise. A small number of highly relevant items are sufficient to cover primary information. |
Similarity Threshold | Calibrate by measurement | Ensures semantic relevance of recalled content. Too low may recall irrelevant information; too high may miss valid information. |
Rerank Recall Count | Top 3 | Further optimizes recall results, submitting the most relevant information to the large model to improve answer quality and efficiency. |
maxContext | 4096 tokens | Accommodates the context requirements of lengthy regulations and SOP documents, ensuring the model can understand complex contexts. |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Provides sufficient time to process IVD PDF documents containing numerous charts and complex layouts, preventing parsing timeouts. |
Common Pitfalls
- Symptom: When a user asks about
batch numberregulations, the model's answer is vague or inaccurate. Reason: During document parsing, the workflow fails to effectively identify and extract batch number fields in various formats and their related regulations from the documents. - Symptom: After updating to version
4.8.14, the "code execution" node in the workflow fails validation if it includes "history" as an input. Reason: The version update introduced a new validation mechanism, imposing stricter limits on the reference method or type of thehistoryvariable. - Symptom: For questions regarding the
2-8℃storage condition, the model cannot correctly interpret the temperature range and provides non-compliant answers. Reason: The workflow lacks semantic understanding enhancement for special units and numerical ranges, relying only on literal matching. This prevents the model from distinguishing the association between numbers and units.
Verification Steps
- Upload and parse a series of IVD diagnostic reagent regulation documents that include specialized terminology, charts, and multi-chapter cross-references. Check if knowledge base segmentation is reasonable and if key information is correctly extracted.
- Conduct multiple rounds of Q&A testing for specific IVD domain questions, such as "expiration date regulations for a certain reagent" or "quality control product concentration standards." Evaluate the accuracy and completeness of the model's answers and verify the correctness of cited original sources.
- Simulate document update scenarios by uploading revised regulatory documents. Verify if the workflow can identify updated content and perform incremental updates to the knowledge base correctly, ensuring accurate Q&A for both new and old versions of regulations.
The values provided are common starting points and should be measured 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.