What the data for this category looks like
White goods intelligent due diligence report data is primarily sourced from official brand public product parameter pages, compliance certification reports from third-party testing institutions, e-commerce platform product detail pages, and after-sales feedback databases. Update rhythm adjusts based on brand new product release cycles and quarterly after-sales data updates, with no fixed cycle but covering regular new product launches and compliance revision scenarios. Document structure combines structured tables and paragraph descriptions, including fields such as product model, rated power, energy efficiency rating, cooling/heating capacity, warranty terms, compliance certification numbers, and more. Most field units use metric standards such as watts, liters, decibels, and others.
What constraints do these characteristics impose on deployment and upgrade
The multi-field structured nature of white goods intelligent due diligence reports requires parsing rules configured during deployment to support multi-dimensional data extraction, avoiding missing core fields such as product model and energy efficiency rating, or format parsing errors. The non-fixed update cycle of data requires adjusting the trigger logic of scheduled synchronization scripts during upgrades, adapting to sudden data updates caused by new product launches and compliance revisions. The large per-report volume requires expanding resource quotas for file upload and vector storage during deployment, avoiding timeouts during parsing or cross-node synchronization. The standardized unit requirement for fields requires configuring unified unit conversion rules during upgrades, ensuring report data from different brand sources can be compared uniformly.
How to set the configurations
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
PARSE_FILE_TIMEOUT_SECONDS | 300-600 seconds | White goods due diligence reports often contain long text parameter tables and compliance descriptions, resulting in long parsing times |
UPLOAD_FILE_MAX_SIZE | 2000 MB | Single official brand due diligence reports may contain multiple pages of test data, default configurations cannot cover large file uploads |
maxContext | 8000-12000 characters | Long paragraph content such as compliance certifications and parameter comparisons in due diligence reports must be fully retained to avoid truncation of critical information |
SYNC_DATA_INTERVAL | 86400 seconds | Adapts to daily after-sales data updates and synchronization of new product data in line with brand release rhythms |
RECALL_TOP_K | Top 8-12 entries | Due diligence reports require coverage of multi-dimensional parameters. Too many recalls increase context pressure, while too few will miss critical information |
SIMILARITY_THRESHOLD | 0.75 | Precise matching of appliance models and parameters is required to avoid recall of low-relevance non-target products |
The parameter values provided on this page are general recommendations used as a starting point for configuration. Actual values are affected by material form, data volume and business rules. Specific issues require on-site analysis, and it is recommended to test on your own samples before finalizing settings.
Three common mistakes
- Phenomenon: A
413 Request Entity Too Largeerror occurs when loading the white goods due diligence knowledge base after private deployment with docker compose. Cause: TheUPLOAD_FILE_MAX_SIZEparameter is not adjusted, and the default upload limit cannot accommodate single large due diligence reports. - Phenomenon: A
401 Unauthorizederror occurs when using a generic account KEY as theBASE_URIconfiguration item when connecting to an external model. Cause: Generic account KEYs only apply to online platform calls. Private deployments require exclusive API keys and compliant BASE_URI for the corresponding model. - Phenomenon: Uncaught exceptions appear in deployed due diligence applications after upgrading to version v4.8.20. Cause: Database migration scripts after version upgrade are not executed, and old configurations are incompatible with new data structures.
How to confirm correct configuration
- Upload the single largest volume white goods due diligence report, check upload progress and parsing logs to confirm no timeouts or format errors.
- Configure a scheduled synchronization task, check whether the latest data from the data source is synchronized to the knowledge base after triggering, to confirm normal synchronization logic.
- Initiate a query for a specific appliance model, check whether the similarity and number of recall results match the preset configuration.
- Execute database migration commands after upgrading the version, check that the application startup logs have no structural incompatibility errors.
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.