What Data Looks Like for This Category
White goods data sources cover multiple types of official public documents and business data. These include public test reports from the National Energy Efficiency Labeling Center, compliance technical documents from brand owners, structured tables of after-sales repair return data from e-commerce platforms, and category monitoring summary documents from industry associations. Update rhythms vary significantly: energy efficiency test reports update with new product launches, after-sales data syncs daily, and industry summary documents release quarterly. There are two types of document structures: Structured table documents contain fields such as SKU, fault type, and repair time. PDF report documents have fixed fields including model, energy efficiency rating, rated power (unit: watt), and testing institution seal.
Constraints on Citation Sources and Traceability
Multi-source heterogeneous data formats require the system to adapt to multiple parsing rules for PDFs, structured tables, and web public notices. Different data sources have inconsistent field naming. For example, "SKU" in after-sales data and "model" in energy efficiency reports refer to the same identifier. Precise field mapping rules must be configured. Differences in update frequencies can cause some data sources to expire. Per-source recall update cycles must be set to avoid citing outdated energy efficiency parameters or after-sales data for discontinued models. Some test reports include official seals. The traceability link must support seal verification to ensure cited sources have not been tampered with. Additionally, white goods model hierarchies are complex. Precise SKU matching is required to avoid citing incorrect data across models.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
REFERENCE_TEMPLATE | {{content}} (Source: {{source_name}}, {{publish_date}}, {{document_type}}) | Adapts to traceability labeling for multiple white goods data sources, clearly displays required source information for compliance, and meets due diligence report archiving requirements |
SIMILARITY_THRESHOLD | 0.75-0.85 | White goods have many SKU models and high parameter similarity. A threshold that is too low will recall irrelevant model data, while a threshold that is too high will miss valid parameter sources |
RECALL_LIMIT | Top 8 entries | White goods parameter documents typically have long individual content. Too many recalled entries will cause context redundancy, while too few will fail to cover all parameter dimensions required for complete due diligence |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Some large brand quality inspection PDF documents include multi-page charts and seal verification, resulting in long parsing times. A timeout setting that is too short will cause parsing failures |
SOURCE_VERIFICATION_ENABLE | Enabled | White goods due diligence requires compliant traceability. When enabled, it can verify official seals and issuing institutions of test reports to avoid citing forged data |
RERANK_TOP_N | Top 12 entries | The re-ranking step filters low-relevance data from initial recall results. Recalling more entries first then re-ranking adapts to the complex matching needs of multiple white goods data sources |
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 individual assessment. It is recommended to conduct testing on suitable samples before finalizing configuration values.
Three Common Configuration Errors
- Symptom: After upgrading to version 4.9.7, knowledge base answer paragraphs do not display citation annotations at the end. Cause: The
REFERENCE_TEMPLATEparameter is not configured correctly, or theSOURCE_VERIFICATION_ENABLEswitch is not enabled, causing the system to fail to generate citation identifiers. - Symptom: White goods parameters cited in due diligence reports have cross-model matching errors, such as citing energy efficiency data of model A in due diligence content for model B. Cause: The
SIMILARITY_THRESHOLDis set too low, or SKU precise matching field mapping rules are not configured, resulting in recall of data sources with high similarity but incorrect model matching. - Symptom: A
504 Gateway Timeouterror occurs when parsing large brand quality inspection PDF documents. Cause: ThePARSE_FILE_TIMEOUT_SECONDSsetting value is less than the actual parsing time of the document, causing the system to forcibly terminate the parsing task.
How to Verify Successful Configuration
- Upload one white goods energy efficiency test report and one after-sales data document, initiate a due diligence query, and check if citation annotations matching the
REFERENCE_TEMPLATEformat are generated at the end of answer paragraphs. - Enter a query containing a specific SKU, and verify that recalled data sources only include parameter documents for the corresponding model, with no cross-model invalid citations.
- Upload a brand compliance document larger than 500MB, and check that the parsing task completes within the time set by
PARSE_FILE_TIMEOUT_SECONDS, with no timeout errors. - Disable the
SOURCE_VERIFICATION_ENABLEswitch and initiate a query, check that citation annotations do not include testing institution seal verification information, then enable the switch and recheck to confirm verification information has been added.
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.