HTTP Interface and External Systems for Cardiovascular

Data Characteristics

Cardiovascular intervention regulations and SOP documents primarily source data from regulatory files published by the National Medical Products Administration and the National Health Commission, operational guidelines from industry associations, and internal institutional rules and procedures. These documents update at a stable pace, typically after regulatory revisions or technological innovations, with cycles ranging from months to years. Document formats are mainly PDF and Word, containing numerous charts, flowcharts, and specialized terminology. Examples include "Percutaneous Coronary Intervention (PCI)," "stent implantation," and "cardiac catheterization laboratory infection control standards." Field content covers device models, operational steps, indications, contraindications, and complication management. Units often include millimeters (mm), milliliters (ml), minutes (min), and atmospheres (atm), with high precision requirements for numerical values.

Constraints Imposed by these Characteristics on "HTTP Interface and External Systems"

The PDF and Word formats of cardiovascular intervention regulation documents, along with their embedded charts, pose challenges for data extraction and parsing by external systems. Generic crawlers may not effectively extract text information from embedded charts or may result in formatting errors. The relatively stable update frequency means full synchronization is not required often, but incremental update mechanisms must identify and process revised versions. The precision requirements for specialized terminology and units necessitate consistent encoding during HTTP interface transmission to prevent garbled text or numerical conversion errors. Furthermore, the hierarchical structure and cross-referencing within regulation documents require external systems to maintain these relationships when building knowledge bases, supporting complex question-answering scenarios. For specific fields like device models, interface design must accommodate diversity and future scalability using flexible data structures.

Configuration Guidelines

Configuration Item	Recommended Value	Rationale
`UPLOAD_FILE_MAX_SIZE`	`50 MB`	Individual regulation documents may contain extensive charts and detailed content, leading to larger file sizes.
`PARSE_FILE_TIMEOUT_SECONDS`	`600 seconds`	Processing complex PDF or Word documents, especially those with charts, can be time-consuming.
`maxContext`	`3000 Tokens`	Cardiovascular intervention guidelines are detailed and require a longer context window for understanding and answering.
`Chunk size`	`800 characters`	Maintain paragraph semantic integrity and avoid breaking critical process descriptions.
`Recall count`	`Top 5 entries`	Ensure coverage of multiple relevant regulations or operational steps.
`Similarity threshold`	Calibrate based on actual measurements	Optimize for specialized terminology, balancing recall and accuracy.

Common Pitfalls

When an external system makes API calls, the returned text format is garbled or critical information is missing. This happens because the document parsing service fails to correctly identify tables or flowchart text within PDFs.
Online chat question-answering results are accurate, but HTTP interface call results frequently show errors. This may be due to incorrect maxContext parameter transmission or configuration during API calls, preventing the model from acquiring complete context.
The numerical units returned by the interface do not match expectations, or precision is lost. This typically occurs when the external system does not perform strict type validation and conversion for specific measurement unit fields during data transmission or reception.

Verification Steps

Upload and parse a typical cardiovascular intervention SOP document containing charts and tables via the HTTP interface. Check if the returned text content is complete and correctly formatted, then compare it with the original document.
Use query statements containing specialized terminology and units to call the question-answering service via the HTTP interface. Verify that the terms and numerical values in the returned answers match the original knowledge base text, and check unit correctness.
Simulate concurrent requests to observe the API interface's response time and success rate. Ensure stable service operation under expected load, without timeouts or connection interruptions.

Note: The values provided are common starting points. Measure against your own samples for optimal configuration.

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.