What the data for this category looks like
Data for white goods intelligent due diligence reports comes primarily from manufacturer factory inspection reports, energy efficiency label filing documents, after-sales maintenance ledgers, and industry spot check notices. Factory reports are updated alongside product batches, filing documents are updated annually, and after-sales ledgers add new entries in real time based on service frequency.
Two document structure types are present:
- Structured tables containing fields such as cooling capacity, noise level, and net weight, with corresponding units of W, dB(A), and kg respectively.
- PDF-format inspection reports with header identifiers including batch number and production date. Some documents include parameter annotations embedded as images.
What constraints do these characteristics impose on the document parsing and chunking workflow?
Field order in structured tables varies across product batches. Parsing must match fixed field names instead of relying on layout position to avoid parameter misalignment.
Embedded image parameter annotations require OCR parsing to extract core information such as cooling capacity and energy efficiency rating.
Header batch numbers in multi-page inspection reports are redundant metadata and must be filtered before chunking.
Some documents display complete product parameters across multiple pages. Chunking must retain contextual association of cross-page fields to avoid splitting parameters apart.
Additionally, document layouts vary significantly across manufacturers, so parsing logic for non-standard tables must be supported.
How to set the configurations
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
PARSE_OCR_ENABLE | Enabled | White goods documents often have parameter annotations embedded as images, so OCR is needed to extract text content |
MAX_SEGMENT_LENGTH | 800–1200 characters | The core parameter blocks of white goods due diligence reports mostly fall within the 600–1000 character range, this interval preserves the complete association between parameters and their descriptions |
UPLOAD_FILE_MAX_SIZE | 500 MB | The total size of a single multi-page inspection report plus supporting images typically does not exceed 400 MB, with reasonable buffer reserved |
PARSE_FILE_TIMEOUT_SECONDS | 300 seconds | Large multi-page PDF parsing requires longer processing time to avoid timeout interruptions |
CHUNK_OVERLAP_RATE | 15% | Context for cross-page parameter associations requires a small number of overlapping segments to ensure complete parameter groups can be retrieved |
ENABLE_TABLE_PARSE | Enabled | Structured tables are the core data carrier for white goods documents, retaining table structure improves subsequent vectorization and retrieval accuracy |
The parameter values provided on this page are common recommended starting points for configuration. Actual values are affected by material form, data volume, and business rules. Specific issues require targeted analysis, and it is recommended to test against your own samples before finalizing settings.
Three common configuration mistakes
- Symptom: Parsing API calls return
400 Bad Requestwith the promptinvalid image url. Cause: ThePARSE_OCR_REMOTE_URL_SUPPORTconfiguration is not enabled, or the passed image address does not have cross-domain access permissions enabled. - Symptom: Core fields such as cooling capacity and net weight are missing from parsed table data in chunking results. Cause: The
ENABLE_TABLE_PARSEconfiguration is not enabled, so structured tables are recognized as plain text and field association relationships are lost. - Symptom: Parsing tasks time out and fail after batch uploading multiple large inspection reports. Cause: The
PARSE_FILE_TIMEOUT_SECONDSsetting is lower than 300 seconds, which cannot complete the full parsing process for multi-page PDFs.
How to confirm configurations are correctly set
- Upload a white goods inspection report with embedded image parameters, check if the parsed results include text content from the images to confirm the OCR configuration is active.
- Submit a structured table document, verify that the parsed results retain the table's row and column structure to confirm the table parsing configuration is active.
- Call the knowledge base chunking API, pass a test document, and check if the returned chunk list retains contextual association of cross-page parameters to confirm the chunk overlap rate configuration is reasonable.
- Upload a test document with a size exceeding the conventional threshold, confirm that the parsing task does not trigger a
413 Payload Too Largeerror to verify the file upload size configuration is compliant.
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.