What the data for this category looks like
Baijiu due diligence data comes from four main sources: internal production ledgers of distilleries, third-party testing institution reports, dealer cooperation documents, and public industry association materials. Update frequency falls into three categories based on document type. Routine inventory and sales ledgers update monthly. Batch testing releases alongside production runs. Annual production capacity and compliance documents update once per year. Supporting documents for new product launches generate temporarily when products launch. Common document formats include multi-page PDFs, Word table documents, and Excel detailed ledgers. These files contain nested physicochemical indicator tables, batch traceability information, raw material composition descriptions, and other fields. Field units include milliliters, kilograms, tons, and other standard measurement units.
What constraints do these characteristics impose on document parsing and chunking?
The multi-nested tables, varied document formats, and tight field-unit links in baijiu due diligence reports create three constraints for parsing and chunking. First, nested physicochemical indicator tables must keep hierarchical associations. Do not split cross-page tables into unrelated fragments, as this breaks the link between batches and their associated indicators. Second, document formats are inconsistent. Some files are native Office structured documents, others are scanned PDFs. The workflow must support both native parsing and OCR extraction. Third, fields bind tightly to their units. After parsing, preserve the link between each indicator and its corresponding unit to avoid data misalignment during later due diligence analysis. Overall, separate structured table data from unstructured compliance text. Aggregate and chunk content by type to meet retrieval requirements.
How to set the configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
PARSE_TABLE_NESTING_LEVEL | 3 levels | The nested table hierarchy of baijiu due diligence reports typically does not exceed 3 levels. Retaining this hierarchy fully restores the link between batches and indicators |
PARSE_OCR_ENABLE | Enabled | Some third-party testing reports are scanned PDFs. OCR extraction retrieves tables and text content from these files |
CHUNK_SIZE | 800–1200 characters | Matches the length of table fragments and compliance text in baijiu due diligence reports, preventing split critical indicator combinations |
PARSE_FILE_TIMEOUT_SECONDS | 120 seconds | Large annual production ledger documents take longer to parse. This duration covers most common scenarios |
RECALL_CHUNK_COUNT | Top 6 | Balances retrieval needs for multi-indicator single batches and cross-batch comparisons, covering core due diligence information |
UPLOAD_FILE_MAX_SIZE | 500 MB | Accommodates the standard size of group-level baijiu production documents, preventing upload failures |
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 individual analysis. It is recommended to test on your own samples before finalizing settings.
Three common mistakes
- Symptom: After uploading a multi-column physicochemical indicator table, parsing results show field misalignment and missing units. Cause:
PARSE_TABLE_NESTING_LEVELwas not set to an appropriate value, orPARSE_OCR_ENABLEwas not enabled, leading to failed column alignment for scanned tables. - Symptom: After uploading a PDF document, embedded testing report images cannot be viewed. Cause: The image parsing switch was not enabled, or images in the document use non-standard formats leading to parsing failure.
- Symptom: Knowledge base retrieval results only contain scattered text, and do not cover core batch indicators. Cause:
CHUNK_SIZEwas set too small, splitting complete batch indicator tables into multiple unrelated fragments, orRECALL_CHUNK_COUNTwas set too low, failing to cover sufficient associated information.
How to confirm configurations are correct
- Upload a typical baijiu testing report PDF, and check if parsed tables retain nested hierarchies and unit binding relationships.
- Upload a scanned baijiu production ledger document, and confirm that text and tables extracted via OCR can be properly identified.
- Run a knowledge base retrieval test, and verify that retrieval results include all physicochemical indicators for the target batch.
- Check that the size of uploaded files falls within the configured maximum upload threshold, to avoid upload failures due to exceeding limits.
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.