What the data for this category looks like
Data sources for white goods industry research reports include monthly industry reports released by the China Household Electrical Appliances Association, special home appliance industry research reports from securities firms, public investor relations documents from leading home appliance enterprises, and retail end data from third-party industrial monitoring institutions. Monthly retail data updates weekly. Industry quarterly reports release at the end of each quarter. Corporate financial reports update alongside quarterly and annual milestones. Research reports related to sudden energy efficiency policies update when events trigger. Most documents use structured tables paired with paragraph analysis. Fields include product category (such as drum washing machine, built-in refrigerator), shipment volume, retail sales, year-on-year growth rate, with units of ten thousand units and ten thousand yuan respectively. Some documents include additional details such as energy efficiency ratings for sub-models and core component cost proportions.
What constraints do these characteristics impose on the knowledge base retrieval and recall link?
Dispersed data sources and inconsistent update cycles require the knowledge base to support multi-source scheduled synchronization and incremental updates. This avoids excessive node load caused by full retransmissions. Most documents contain structured tables. The recall process must retain table structures instead of extracting only plain text. Losing dimensional information for sub-categories and sub-models leads to matching deviations. There are subtle differences in field units. For example, retail sales distinguishes between ten thousand yuan and hundred million yuan. Unit calibration during retrieval avoids matching errors. The number of sub-categories and sub-models is large. The recall process must cover a sufficient candidate set while avoiding irrelevant general home appliance data.
How to set the configuration
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
RECALL_TOP_K | Top 10-15 results | White goods industry research reports include numerous sub-categories. A sufficient candidate set is required to cover relevant data for different models and cycles |
SIMILARITY_THRESHOLD | 0.72-0.80 | Research report text contains a large number of professional terms. A threshold that is too low introduces irrelevant general home appliance data, while a threshold that is too high omits matching results for sub-models |
PARSE_TABLE_ENABLED | Enabled | White goods industry research reports contain a large number of structured tables for shipment volume and retail sales. Enabling this option retains table structures for precise recall |
SYNC_INTERVAL_MINUTES | 15-60 | Monthly retail data updates frequently, and quarterly reports require timely synchronization. Short intervals adapt to high-frequency data, while long intervals adapt to low-frequency research reports |
UPLOAD_FILE_MAX_SIZE | 200 MB | The size of a single large corporate financial report or industry collection research report usually does not exceed 200 MB. This avoids parsing timeouts |
RERANK_TOP_N | Top 5-8 results | Relevant results for sub-categories require precise screening to avoid excessive redundant information interfering with retrieval results |
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 case-by-case analysis. It is recommended to test on your own samples before finalizing settings.
Three common mistakes
- The symptom is an error related to
providerreturned after clicking to add a new folder in the knowledge base. The cause is that the storage provider parameters of the knowledge base are not correctly configured, leading to identity verification failure during directory creation. - The symptom is a
401 Unauthorizedstatus code returned when calling the knowledge base synchronization API. The cause is that a valid API key is not carried in the request header, or the key permissions do not cover the knowledge base collection synchronization operation. - The symptom is that sub-model related data is missing from knowledge base recall results. The cause is that the
PARSE_TABLE_ENABLEDconfiguration is not enabled, leading to failure to correctly parse structured sub-model tables in research reports, making it impossible to match precise user retrieval keywords.
How to confirm the configuration is correct
- Upload a white goods quarterly research report, check the parsed document structure, confirm that table content is fully retained, to verify that the
PARSE_TABLE_ENABLEDconfiguration takes effect. - Initiate a retrieval request that includes a sub-model (such as "built-in refrigerator"), check that the number of recall results matches the
RECALL_TOP_Kconfiguration. - Test the scheduled synchronization task, check whether new research reports in the knowledge base are automatically updated according to the cycle set by the
SYNC_INTERVAL_MINUTESconfiguration. - Call the synchronization API, verify that a
200 OKstatus code is returned after carrying a valid key, to confirm that the identity verification configuration is correct.
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.