Data Characteristics for This Category
Site Management Organization (SMO) quality documents primarily include Standard Operating Procedures (SOPs), work guidelines, training materials, quality control records, and regulatory documents from clinical trial projects. Update frequency for these documents typically aligns with project cycles and regulatory changes. For example, new project launches, protocol amendments, or Good Clinical Practice (GCP) guideline updates might lead to partial updates monthly or quarterly.
Document structures are mostly hierarchical. SOPs often contain fixed sections such as purpose, scope, responsibilities, procedures, and attachments. They are frequently stored in PDF or Word formats. SOPs contain specialized terms and specific numerical values, such as "subject screening criteria," "visit windows (±N days)," and "dosage units (mg/kg)," requiring high precision.
Constraints on Knowledge Base Retrieval and Recall
The hierarchical structure and specialized terminology of SMO quality documents require specific knowledge base chunking strategies. These strategies must ensure semantic completeness of documents and prevent inappropriate splitting of critical procedures.
Although the update frequency is not high, each update can involve multiple related documents. This demands efficient batch update and version management capabilities from the knowledge base. The precise numerical values and specialized fields in the documents mean that fuzzy matching recall is ineffective. Retrieval needs to focus more on keyword matching combined with semantic similarity.
Compliance requirements dictate that retrieval results must trace back to original document sources. This ensures information authority and accuracy, requiring rich metadata in recall results.
Configuration Settings
| Configuration Item | Suggested Value | Rationale |
|---|---|---|
Chunk size (Chunk Length) | 800–1200 characters | Balances SOP section completeness with vectorization model processing capacity |
Chunk Overlap Length (Overlap Length) | 100–200 characters | Ensures semantic continuity across chunks and prevents loss of context |
Recall count (Recall Count) | Top 8–12 items | Increases relevant information coverage for multi-faceted queries |
Similarity threshold (Similarity Threshold) | Calibrate based on actual measurements | Ensures precision of recall results and avoids irrelevant information interference |
Rerank result count (Reranked Return Count) | Top 5 items | Refines final presented results, focusing on the most relevant content |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Handles parsing time for large PDF or Word documents, preventing timeout interruptions |
Common Mistakes
- Retrieval results contain many irrelevant SOPs. This might be due to a
Similarity threshold(Similarity Threshold) set too low, leading to excessive generalized recall. - Uploaded Chinese SOP document content appears as garbled text. This usually indicates incompatible file encoding formats, for example, uploading a GBK encoded CSV file when the system defaults to UTF-8.
- When querying specific procedures, recalled SOP segments are incomplete. This happens when the
Chunk size(Chunk Length) is too short, truncating the procedure description during chunking.
How to Verify Correct Configuration
- Select multiple typical queries. Check if recall results include all expected key information from SOPs. Verify the original source using
docId. - Review system logs for document parsing status. Confirm all uploaded SOP documents are successfully chunked and vectorized, with no
PARSE_FILE_TIMEOUTerrors. - For core procedure queries, evaluate the contextual completeness of recall results. Ensure each segment independently provides effective information.
Note: The values provided are common starting points and should be measured against specific 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.