Data Characteristics
II-III clinical trial quality documents include Investigator's Brochures (IB), Clinical Trial Protocols, Informed Consent Forms (ICF), Case Report Forms (CRF), and various Standard Operating Procedures (SOPs). Sponsors, Contract Research Organizations (CROs), and clinical trial sites are the primary sources for these documents. Document updates are infrequent, typically occurring at key milestones during trial progression, such as protocol amendments. Documents are structured into chapters and clauses, containing extensive specialized terminology, abbreviations, and specific formatting requirements. Common fields include Drug Name, Dosage, Route of Administration, Subject Inclusion/Exclusion Criteria, Primary/Secondary Endpoints. Units involve medical and pharmaceutical measurements like mg, ml, μg/kg, days, and weeks, with high demands for numerical precision and unit consistency.
Constraints on Tool Calling and Plugins
The specialized and rigorous nature of II-III clinical quality documents imposes strict requirements on the accuracy and reliability of tool calling and plugins. First, the complex document structure and specialized terminology demand strong semantic understanding from the model to correctly identify and invoke the appropriate tools for data extraction or validation. Second, infrequent but impactful document updates require tool calling to handle version control, ensuring operations always use the latest approved document version. Third, strict requirements for units and numerical precision mean that when calling external data validation or calculation tools, parameter passing must be accurate, and result units must be consistent to avoid severe deviations from unit conversion errors. Finally, sensitive data within documents (e.g., subject information) requires the tool calling pipeline to have robust data anonymization and access control mechanisms to comply with regulations.
Configuration Settings
| Configuration Item | Suggested Value | Rationale |
|---|---|---|
maxContext | 8000 | Clinical documents are lengthy; a larger context window maintains semantic coherence and prevents loss of critical information. |
Chunk size (Segment Length) | 800–1200 characters | Clinical documents have strong logical structures; longer segments preserve complete semantic units and reduce ambiguity from splitting. |
Recall count (Recall Count) | Top 10 | Ensures coverage of relevant clauses and definitions that may be scattered across different document sections, improving recall rate. |
Similarity threshold (Similarity Threshold) | 0.78 | Clinical documents demand high precision; increasing the threshold filters out irrelevant recall results, improving accuracy. |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Parsing large clinical documents takes time; increasing the timeout prevents parsing interruptions and ensures complete processing. |
ENABLE_ADVANCED_RAG | true | Enables advanced RAG strategies, such as multi-hop reasoning, to handle complex logical relationships and cross-chapter references in clinical documents. |
Common Mistakes
- Plugin call returns
AxiosError 404: This usually indicates an incorrectAPI_URLorendpointin the plugin configuration, or that the plugin service is not properly deployed or started. - Inconsistent or missing units in data returned after tool invocation: This often happens when the plugin does not standardize units during raw document data processing or when unit information is lost during parameter transfer to external calculation tools.
- Deep thinking tool does not trigger as expected: This might be because the
trigger wordsare too broad or too narrow, failing to precisely match keywords in the user's query that require deep analysis.
Verification Steps
- Ask questions about key specialized terms or abbreviations. Observe if the tool accurately identifies and invokes relevant plugins for explanation or data retrieval.
- Simulate practical operations, such as querying the dosage range for a specific drug. Check if the returned numerical values and units are entirely consistent with the document content and unambiguous.
- Submit complex queries containing multiple related questions. Verify if the tool chain logically calls multiple plugins and provides coherent answers.
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.