Data Characteristics
Data for respiratory system regulations and Standard Operating Procedures (SOPs) originates from internal medical institution rules, clinical pathways, diagnostic guidelines, and drug instructions. These documents are typically stored as PDFs, Word files, or plain text. Content includes disease diagnostic criteria, treatment plans, drug usage specifications, nursing procedures, and equipment operation guides. Data updates are relatively stable, usually following annual review and revision cycles by national health commissions or hospitals. Document structures commonly include chapter titles, body text, figures, and appendices. Some content involves specific medical terminology, dosage units (e.g., milligrams, micrograms, milliliters), time units (e.g., hours, days, weeks), and medical examination indicators (e.g., blood oxygen saturation percentage, lung function liters/second).
Constraints Imposed by Data Characteristics on HTTP Interfaces and External Systems
The characteristics of respiratory system regulation documents impose specific requirements on HTTP interfaces and external system integration. Document diversity (PDF, Word) necessitates flexible file parsing capabilities to accurately extract text, tabular data, and figure descriptions from various formats. The specialized nature of medical terminology and the precision of dosage units mean that data transfer and processing must avoid semantic loss and unit confusion, potentially requiring standardization during the data preprocessing stage. The periodic update cycle of regulations means external systems calling the interface must consider data version management and caching strategies to ensure the timeliness of question-answering results. HTTP interface response times also require optimization to handle complex queries that may contain extensive medical details, especially when processing cross-references across multiple documents.
Configuration Settings
| Configuration Item | Recommended Value | Rationale for Recommendation |
|---|---|---|
maxContext | 3000-4000 characters | Respiratory system regulation documents often contain long paragraphs and detailed descriptions, requiring a larger context window to capture complete semantics. |
Chunk size (Segment Length) | 500 characters | Ensures each text segment contains sufficient contextual information while preventing individual segments from being too long and impacting recall efficiency. |
Recall count (Recall Count) | 8-12 items | Complex medical questions may involve multiple regulatory sections; increasing the recall count helps cover more comprehensive information. |
Similarity threshold (Similarity Threshold) | 0.7-0.75 | Question-answering in the medical field demands high accuracy; appropriately raising the threshold filters out irrelevant, low-quality recalls. |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Respiratory system SOP documents may contain numerous charts and complex layouts, potentially leading to longer parsing times. |
HTTP_REQUEST_TIMEOUT | 120 seconds | When external systems call the interface, extend the timeout appropriately, considering that the backend may need to perform multi-document retrieval and complex reasoning. |
Common Pitfalls
- Symptom: API calls return
{"code":514,"statusText":"Internal Server Error"}or an empty result. Reason: File parsing failed, possibly due to uploading an unsupported document format or overly complex document content causing the parser to time out. - Symptom: Drug dosages or examination indicator units appear incorrect in question-answering results, or values are misinterpreted. Reason: Text extraction failed to correctly identify and process specialized medical units, leading to a disconnect between values and units.
- Symptom: A user asks about the latest version of a regulation, but the system returns outdated information. Reason: The external system did not timely synchronize or refresh the knowledge base, causing the data version called by the HTTP interface to be outdated.
Verification of Configuration
- Upload respiratory system regulation documents in various formats (PDF, Word) and verify successful parsing and ingestion.
- Ask typical questions involving dosages and indicators from the documents, then check the accuracy of numerical values and units in the answers.
- Simulate a regulation update scenario: upload a new version of a document, then query relevant content via the API to confirm the latest information is returned.
- Use queries containing complex medical terminology and long sentences to test if the API response time is within acceptable limits.
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.