What This Category of Data Looks Like
The data for traditional Chinese medicine (TCM) marketing content primarily comes from official corporate promotional brochures, exported files from e-commerce platform product detail pages, industry compliance filing documents, and dealer promotional materials. Update frequency fluctuates with new product launches and adjustments to compliance policies, with no fixed cycle. Document structures typically include fields such as product name, nature and tropism of Chinese materia medica, functions and indications, dosage and administration, contraindications, and compliance approval numbers. Units often involve professional medical units such as grams, milliliters, and treatment courses. Some long documents are split into chapters by product series, while short documents are single-page efficacy descriptions.
What Constraints These Characteristics Impose on Document Parsing and Chunking
The specialized fields and compliance requirements of this category require that cross-field content integrity be preserved during document parsing. For example, national drug approval numbers must be bound to their corresponding products, and must not be split into different chunks. Document structure spans vary widely, so chunking boundaries must be flexibly adapted for both short documents and multi-chapter brochures. This prevents critical content such as contraindications and dosage and administration from being truncated. Professional medical units such as grams and treatment courses must be bound to their associated descriptions, to avoid separation between units and their content. For content that mixes marketing copy and compliance explanations, the independence of semantic units must be preserved during chunking. This ensures the accuracy of subsequent retrieval and application. Additionally, the non-fixed update frequency requires the parsing process to adapt to input files of varying lengths.
How to Set Configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
PARSE_FILE_TIMEOUT_SECONDS | 300–600 seconds | TCM marketing documents often include multi-page product brochures, and large files take longer to parse. This range adapts to the processing duration of common large files |
| Segment Length | 800–1200 characters | TCM content contains specialized terminology and long sentences. This range preserves semantic integrity and avoids splitting professional expressions |
UPLOAD_FILE_MAX_SIZE | 500–1000 MB | Some series product brochures have large single-file sizes. This range covers the upload requirements of most marketing documents |
chunk_overlap | 100–150 characters | Preserves semantic continuity between adjacent chunks, and prevents loss of context when professional content such as nature and tropism of Chinese materia medica is split across different chunks |
PARSE_MODE | Parse by document structure | TCM documents often have fixed chapter structures. Parsing by structure preserves field associations, and avoids mixed arrangement of content across chapters |
RECALL_CHUNK_COUNT | Top 6–8 results | Marketing content needs to match precise user query scenarios. This range covers core compliance and efficacy information |
The parameter values provided on this page are common starting points for configuration. Actual values are affected by material format, data volume, and business rules. Specific issues require case-by-case analysis. It is recommended to test on your own samples before finalizing settings.
Three Common Mistakes
- Uploading large PDF files to the knowledge base results in an "offset out of range" error at 90% progress. Cause: The match between
UPLOAD_FILE_MAX_SIZEand the file parsing chunk threshold was not adjusted, leading to offset misalignment during large file chunking. - Direct chunking fails to recognize specialized medical content, resulting in semantic breaks in extracted chunks. Cause: The specialized field structure of TCM documents was not adapted, and the
PARSE_MODEset to parse by document structure was not enabled, leading to disordered splitting of terminology and associated content. - Files uploaded via the API have inconsistent chunking results compared to files uploaded directly through the platform. Cause: The Segment Length and
chunk_overlapparameters were not unified, and default parsing configurations differ across upload channels.
How to Confirm Configurations Are Set Correctly
- Upload a single-page TCM efficacy description document, and check that chunking results retain complete fields such as product name, efficacy, dosage and administration, with no content truncation.
- Upload a series product brochure with 10 or more pages, and verify that parsing completes within the preset timeout period with no abnormal errors.
- Compare the same document uploaded via the API and directly through the platform, and confirm that the boundaries and quantity of chunking results are consistent.
- Retrieve chunked content, and check that professional medical units are bound to their corresponding descriptions, with no instances of separation.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-09-14.