Document Parsing and Chunking for Cardiovascular

Data Characteristics

Cardiovascular intervention regulations and SOP documents originate from national health commissions, medical device regulatory bodies, internal hospital operating procedures, and manufacturer product manuals. These documents are primarily in PDF format. They are highly structured and contain specialized terminology, diagrams, flowcharts, and data tables.

National regulations update annually or every few years. Hospital SOPs update irregularly, typically every six months to a year, based on new guidelines, technologies, or device introductions. Document fields include device models, operating steps, indications, contraindications, complications, dosage units (e.g., mg, ml), time units (e.g., seconds, minutes), and pressure units (e.g., mmHg). Precision is critical.

Constraints on Document Parsing and Chunking

The specialized and structured nature of cardiovascular intervention documents imposes strict requirements on document parsing. First, traditional text extraction tools often fail to accurately recognize embedded diagrams and flowcharts in PDFs, leading to potential information loss. Second, extensive specialized terminology and abbreviations, such as PCI and CABG, require dedicated glossaries to prevent tokenization errors and semantic misunderstandings. Third, irregular document updates necessitate knowledge base support for incremental updates and version management to ensure the use of the latest procedures. The precision required for fields and units dictates that chunking strategies must maintain contextual integrity. For example, an operating step description should not be arbitrarily truncated to avoid omitting critical dosage or time parameters, which would affect subsequent question-answering accuracy.

Configuration Settings

Configuration Item	Recommended Value	Rationale
`chunkSize`	`800–1200 characters`	Balances contextual completeness and retrieval efficiency, preventing excessively long or short chunks that could lead to semantic fragmentation or insufficient information.
`overlapSize`	`100–200 characters`	Ensures sufficient overlap between adjacent chunks, improving the coherence of cross-chunk information retrieval.
`PARSE_FILE_TIMEOUT_SECONDS`	`600 seconds`	Accommodates parsing large PDF documents and complex diagrams, preventing parsing failures due to timeouts.
`UPLOAD_FILE_MAX_SIZE`	`500 MB`	Supports uploading regulation documents containing numerous high-resolution images and diagrams without hindrance.
`Custom Parsing Service`	`Enabled`	Addresses accurate extraction of complex layouts, diagrams, and tables within PDFs, enhancing parsing accuracy.
`Chunking Strategy`	`By Title and Paragraph`	Prioritizes preserving the document's logical structure, ensuring the completeness of regulatory items and operating steps.

Common Pitfalls

Files remain in an "parsing" state for an extended period after upload, eventually showing "parsing failed" or "timeout." This often occurs because PARSE_FILE_TIMEOUT_SECONDS is set too low, not allowing enough time for large or complex PDF files to parse.
Uploaded PDF documents have missing or garbled content, especially in diagram and table areas. This indicates that the default text extraction method is insufficient for the complex layouts in cardiovascular intervention documents, and the Custom Parsing Service is either not enabled or improperly configured.
During question-answering, the model provides incomplete details for a specific operating step, such as missing dosage or device model. This may result from chunkSize being set too small, causing critical information to be fragmented during chunking, preventing complete context from being available in a single chunk.

How to Verify Configuration

Upload a cardiovascular intervention SOP document containing diagrams and complex tables. Check if the parsed text content is complete and free of garbling, paying special attention to table data and flowchart descriptions.
Select a paragraph from the document that includes key parameters (e.g., drug dosage, surgical time). Use the knowledge base to ask questions and verify if the model can accurately provide these parameters.
Upload a PDF document larger than 100MB. Observe if the parsing process is smooth and check if the parsing time is within the PARSE_FILE_TIMEOUT_SECONDS setting.
Search using specialized terminology from the document. Check if the returned chunks are closely related to the term and if the contextual semantics are complete without illogical truncation.

The values provided are common starting points and should be measured 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.