Data Characteristics for this Category
Cardiovascular intervention product data primarily originates from product manuals, technical white papers, clinical trial reports, regulatory filings, and training manuals. Document update frequency depends on product iterations, regulatory changes, and clinical feedback, typically several times a year or as needed. Document structure for product manuals usually includes sections like product overview, indications, contraindications, usage instructions, precautions, performance parameters, material composition, and storage conditions. Technical white papers focus more on technical principles, design details, and test data. Fields and units involve physical quantities such as millimeters (mm), kilograms (kg), Newtons (N), millivolts (mV), and flow rates (ml/min), as well as specialized terms like pressure resistance, biocompatibility, catheter diameter, and length. Documents often contain complex charts and semi-structured data.
Constraints from these Characteristics on Document Parsing and Chunking
The characteristics of cardiovascular intervention product documents impose specific requirements on document parsing and chunking. High update frequency necessitates efficient incremental parsing capabilities to quickly synchronize the latest information. Documents containing complex charts and semi-structured data, such as product parameter tables or clinical data statistics, require parsing tools to identify and extract this information. Standard text chunking may lose critical relationships between data points. Accurate identification of specialized terms and units of measurement is crucial; incorrect parsing can lead to misinterpretation of technical parameters. Furthermore, the hierarchical structure of chapter and sub-chapter titles in documents is key to understanding product functions and usage specifications. Chunking must preserve this structural information for precise context retrieval in subsequent searches and question-answering.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
Chunk Length | 800–1200 characters | Ensures each chunk contains sufficient context while avoiding information redundancy, suitable for technical document paragraph lengths. |
Overlap Length | 100–200 characters | Guarantees semantic continuity between adjacent chunks, preventing critical information from being truncated. |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Provides ample parsing time when processing large technical white papers and clinical reports. |
MAX_FILE_SIZE_MB | 200 MB | Accommodates PDF documents containing numerous images and charts. |
Enable Table Parsing | Checked | Cardiovascular intervention product documents often contain important parameter tables. |
Enable Title Hierarchy Recognition | Checked | Chunks documents based on their structural hierarchy, improving retrieval accuracy. |
Three Common Mistakes
- After uploading a large PDF document, the knowledge base training status remains stalled for an extended period or shows failure. This occurs because
PARSE_FILE_TIMEOUT_SECONDSis set too short, preventing the completion of complex document parsing. - During question answering, responses about a specific product parameter are incomplete or inaccurate. This happens when
Chunk Lengthis set too small, causing critical parameters and descriptions to be scattered across different chunks, losing context. - During search testing, clinical trial data results for a specific product model are empty. This is due to
Enable Table Parsingnot being checked, which prevents correct extraction of semi-structured tabular data from the document.
How to Verify Correct Configuration
- Upload typical cardiovascular intervention product manuals and technical white papers. Check log output to confirm no parsing timeouts or error messages.
- Use the knowledge base's search test function. Enter specific product parameters or specialized terms from the document. Verify that recall results include complete relevant descriptions and context.
- Compare the original document with the parsed chunks. Confirm that tabular data, title hierarchies, and units of measurement are accurately identified and preserved.
- For frequently updated documents, perform incremental upload tests. Confirm that the system effectively identifies and processes new version content.
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.