Data Characteristics
R&D document data in smart triage scenarios originates from clinical research reports, drug inserts, medical guidelines, and patent literature. Update frequencies vary by source. Clinical research reports may have monthly or quarterly updates. Drug inserts change with approval and market dynamics. Documents typically have complex structures, including extensive unstructured text, tables, charts, and nested sections. Fields include drug names, indications, dosages, adverse reactions, mechanisms of action, and clinical trial data. These often contain specialized medical terminology and units, such as milligrams (mg), milliliters (ml), days (day), and times (time), requiring high precision.
Constraints Imposed by Data Characteristics on Database and Operations
Complex and diverse document structures demand high robustness and accuracy from document parsers. Parsers must effectively identify and extract nested information. Specialized medical terminology and units require databases to support precise text matching and numerical range queries, ensuring correct unit conversion. Inconsistent update frequencies necessitate flexible data synchronization mechanisms to maintain knowledge base timeliness while avoiding resource waste from frequent full updates. Storing and retrieving large volumes of unstructured text challenges database full-text search capabilities and vector embedding storage efficiency. High data accuracy requirements mandate strict quality validation before data ingestion and robust error handling processes.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
UPLOAD_FILE_MAX_SIZE | 500 MB | Accommodates large clinical trial reports or comprehensive medical guidelines. |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Provides sufficient time for complex document parsing to prevent timeouts. |
Chunk size | 800–1200 characters | Balances context completeness and vector model processing efficiency. |
Similarity threshold | Calibrate based on actual measurements | Adjust through test sets according to specific triage scenarios and recall precision requirements. |
rerank_max_tokens | 2048 | Handles longer specialized terms and descriptions in medical texts, ensuring the rerank model processes full semantics. |
MongoDB WiredTiger Cache Size | 50% of total memory or 8 GB (whichever is smaller) | Optimizes MongoDB read/write performance, reducing disk I/O, especially for large vector data and text indexes. |
Common Pitfalls
- Incomplete knowledge base segmentation leads to missing critical information in query results. This occurs when the document parser fails to correctly identify complex section structures or table boundaries, resulting in lost or incorrectly merged content.
slow operation xxxxmswarnings frequently appear in system logs when uploading large files. This typically indicates MongoDB I/O performance bottlenecks, failing to process large data writes after file parsing in a timely manner.- Rerank model experiences GPU or memory overflow after running for some time, causing service instability. This results from a lack of effective memory management mechanisms, where resources are not released after model loading and inference.
Verification Steps
- Upload representative R&D documents of various types (e.g., clinical reports with tables, multi-level guidelines). Check if knowledge base segmentation is complete and logically correct, without obvious missing or misplaced information.
- Monitor database read/write latency and CPU utilization via the FastGPT backend or MongoDB monitoring tools. Ensure stable and acceptable system response times under concurrent query and write operations.
- Conduct simulated triage query tests. Verify the accuracy and relevance of recall results. Adjust
Similarity thresholdbased on actual medical scenario feedback to ensure smart triage reliability.
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.