What the data for this category looks like
This category’s research report data primarily comes from official brand product manuals, public industry survey summaries, and e-commerce monitoring data. Update frequency fluctuates with new product launch cycles and industry research cycles: it increases during new product release phases, and follows a standard monthly update schedule. Most documents are multi-page PDFs, containing text analysis sections, nested data tables, embedded product ingredient diagrams, and compliance test report screenshots. Some derivative documents are in HTML format. Fields within the documents include product specifications, ingredient lists, efficacy descriptions, compliance markings, and market performance data, with units related to volume, mass, and concentration.
What constraints do these characteristics impose on the document parsing and chunking process
Multi-page PDF documents with embedded images require the parsing step to extract both text and image content, to avoid missing image-related information. The presence of nested data tables requires the chunking logic to retain the full structure of tables, preventing field association breaks caused by improper splitting. Derivative documents in HTML format need to adapt to tag hierarchy parsing, rather than only extracting plain text. Structured fields such as ingredient lists and compliance markings have strong contextual associations, so chunk length must match semantic integrity requirements, to avoid splitting professional information. Additionally, some images in documents have accompanying descriptive text; the descriptive text must be bound to its corresponding image before chunking is performed.
How to set the configurations
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
PARSE_ENABLE_IMAGE | Enabled | Documents include product ingredient diagrams and test report screenshots, requiring extraction of image-related information |
PARSE_HTML_ENABLE | Enabled | Some derivative research reports are in HTML format, requiring tag hierarchy adaptation for content parsing |
SEGMENT_MAX_LENGTH | 800–1200 characters | Documents contain long text analysis paragraphs and nested tables; this length preserves semantic integrity while avoiding redundancy between chunks |
TABLE_PARSE_MODE | Retain full table structure | Product specifications and ingredient data in nested tables require complete association, preventing field loss from improper splitting |
PARSE_FILE_TIMEOUT_SECONDS | 120 seconds | Parsing multi-page PDFs with images takes longer, requiring avoidance of timeout interruptions |
CHUNK_OVERLAP_RATE | 10%–15% | Structured fields have strong contextual associations; overlap ensures semantic coherence |
The parameter values provided on this page are general recommendations to use as a starting point for configuration. Actual values are affected by material format, data volume, and business rules. Specific issues require targeted analysis, and it is recommended to test on your own samples before finalizing settings.
Three common mistakes
- Symptom: After uploading a PDF containing product diagrams, the knowledge base recall results only return plain text with no image-related content. Cause: The
PARSE_ENABLE_IMAGEconfiguration item was not enabled, causing the parsing step to skip image extraction. - Symptom: After uploading an HTML-format research report, no parsed content is returned by the knowledge base. Cause: The
PARSE_HTML_ENABLEconfiguration item was not enabled, or the parsing process did not adapt to HTML tag hierarchies. - Symptom: Split fragments of ingredient tables appear in recall results, and cannot be matched to complete product specification information. Cause: The chunk length was set too small, or the full structure retention mode of
TABLE_PARSE_MODEwas not enabled.
How to confirm configurations are correctly set
- A single-page test PDF containing product images should be uploaded. The parsed knowledge base content should be checked for image descriptive text and image-related information, to confirm the
PARSE_ENABLE_IMAGEconfiguration is active. - A single HTML-format test research report should be uploaded. The parsing progress and results should be reviewed, to confirm the
PARSE_HTML_ENABLEconfiguration is active and content is fully extracted. - A test document containing nested tables should be uploaded. The chunked content should be reviewed to confirm it retains the full table structure, verifying the
TABLE_PARSE_MODEconfiguration is correct. - A test query asking for ingredient lists or product specifications from the document should be initiated. The recall results should be checked to confirm they include complete associated information, verifying the semantic integrity of the chunking logic.
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.