Data Characteristics
Medical Information (MI) response data primarily originates from internal MI system records, clinical study reports, adverse event databases, and regulatory documents. This data typically exists in a mixed format of structured (e.g., database fields) and unstructured (e.g., PDF documents, Word files) content. Data update frequencies vary; regulatory documents and product inserts might update quarterly or annually, while adverse event reports could be entered in real time. Document structures are complex, containing extensive specialized terminology, dosage units, drug batch information, and individualized patient data. Fields may include Drug Name, Indication, Adverse Reaction, Dosage, Route of Administration, Batch Number, Report Date, etc. Units include mg, ml, μg/kg, times/day, etc.
Constraints on Tool Calling and Plugins from These Characteristics
The complexity of MI response data imposes specific requirements on tool calling and plugin configuration. Heterogeneous data sources necessitate robust document parsing capabilities from plugins to accurately extract key information from formats like PDF and Word, and to standardize specialized terminology. High data update frequencies mean tool calling must support scheduled synchronization and incremental updates to ensure knowledge base timeliness. Complex data structures and diverse fields require plugins to differentiate between Drug Name and Indication during information extraction, and to correctly identify and process numerical values with units like mg and ml, avoiding confusion that could lead to incorrect responses. The need for tracing historical response records requires tool calling to structure and store information from each interaction, including input, output, and citation sources.
Configuration Guidelines
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
Chunk size (Segment Length) | 300–500 characters (characters) | Balances semantic completeness and recall efficiency, avoiding irrelevant information from overly long passages. |
Recall count (Recall Count) | 8–12 entries (items) | Covers multi-source information, ensuring support points can be retrieved from different documents. |
Similarity threshold (Similarity Threshold) | 0.75–0.85 | Ensures high relevance of recall results to medical queries, reducing noise. |
Rerank result count (Rerank Return Count) | 3–5 entries (items) | Focuses on the most critical medical information, enhancing response accuracy. |
PARSE_FILE_TIMEOUT_SECONDS | 300 seconds (seconds) | Accommodates parsing time for large PDF or complex Word documents, preventing timeout errors. |
History Record Storage Fields | {"query": "", "answer": "", "source_docs": [], "timestamp": ""} | Ensures completeness and traceability of response records, facilitating subsequent auditing and analysis. |
Three Common Mistakes
- Plugin call failure, returning
Error Code: 500. This may occur if the plugin's configured API key is expired or lacks sufficient permissions to access external MI system data. - Dosage unit confusion in responses, such as mistaking
mgforml. This typically happens when document parsing fails to correctly identify and differentiate unit identifiers after numerical values. - Missing critical citation source document links in historical response records. This may be due to the tool call not correctly populating the
source_docsfield when recording results, or incorrect document storage path configuration leading to invalid links.
How to Verify Correct Configuration
- Perform simulated queries to verify if responses accurately cite key information from different data sources (e.g., clinical reports, regulatory documents), and check if the
source_docsfield contains correct document references. - Use queries containing specific dosages or units to cross-check the correctness of numerical values and unit matching in responses, for example, querying the
recommended dosageof a specific drug. - Inspect historical response records to confirm that
query,answer, andtimestampfields for each interaction are fully recorded, and that documents pointed to by thesource_docsfield are accessible.
The values provided are common starting points and should be measured against the reader's 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.