Data Characteristics in This Category
Medical affairs regulations and Standard Operating Procedures (SOPs) typically exist as PDFs, Word documents, or scanned images. Their content covers guidelines for drug clinical trials, post-market pharmacovigilance, medical information communication, and compliance review processes. Document update frequency depends on regulatory changes and internal company policy adjustments, usually quarterly or annually, with some urgent guidelines released immediately. Document structures are complex, containing extensive specialized terminology, regulatory clauses, flowcharts, and tables. Fields include document number, publication date, revision version, effective date, responsible person, and scope. Units are often dates, version numbers, or specific business metrics.
Constraints Imposed by These Characteristics on Tool Calling and Plugins
The complexity of medical affairs regulation documents requires tool calling to possess strong semantic understanding. This ensures accurate identification of differences between versions and the meaning of specific clauses. Diverse document formats necessitate flexible file parsing capabilities, especially Optical Character Recognition (OCR) for scanned documents. The lack of standardization in fields requires data preprocessing before tool calling or embedding additional parsing logic within plugins. The uncertain update frequency means tool calling results must be traceable to specific document versions and effective dates, requiring plugin integration with version management systems. The intensive use of specialized terminology demands higher accuracy from models in understanding and generating responses, potentially requiring customized glossaries or domain-specific models.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
maxContext | 4000 characters | Medical affairs documents have high information density per sentence; ensure the model captures context. |
Chunk size (Segment Length) | 500 characters | Ensure each segment contains a complete concept, avoiding information truncation. |
Recall count (Recall Count) | 8 entries | Increase recall quantity to improve the probability of retrieving relevant information from complex documents. |
Similarity threshold (Similarity Threshold) | 0.78 | Set a higher threshold to filter out semantically irrelevant results, improving recall quality. |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Large PDF files take longer to parse; allocate sufficient time to avoid timeouts. |
ENABLE_OCR | true | Ensure effective content extraction from scanned and image-based regulation documents. |
Three Common Mistakes
- A 400 status code returned when the model calls a tool usually indicates that the request body format of the plugin interface does not meet expectations. Examples include incorrect field types or missing required parameters.
- Poor function call performance, where the model fails to accurately identify when or with which parameters to call a tool, may stem from the model's limited understanding of function call instructions or an unclear function description.
- Authentication failures when connecting to external tools, manifested as HTTP 401 or 403 errors, occur because the plugin does not correctly configure authentication information in the request header. Examples include a missing
Authorizationfield or an expired token.
How to Confirm Correct Configuration
- Call the plugin and observe log output to confirm if request parameters and return results match the expected data structure.
- Ask questions based on specific regulatory clauses to check if the model can accurately retrieve relevant document segments through tool calls and cite the correct version number and effective date.
- Simulate various user query scenarios, especially those involving cross-referencing multiple documents, to verify if tool calls can correctly handle complex logic and provide coherent answers.
- Ask questions comparing differences between different versions of regulations to confirm if the model can identify and report changes between versions. This requires the plugin to access version control information.
Note: The values provided are common starting points. Measure them against specific 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.