What the data for this category looks like
This scenario addresses research report retrieval needs for the finance, insurance, and wealth management sectors. Data sources for kitchen and bathroom appliance research reports include public reports from the Kitchen and Bathroom Professional Committee of China Household Electrical Appliances Association, official technical white papers from leading kitchen and bathroom brands, and monthly data from offline retail monitoring institutions. Update frequency is once every two weeks during new product launch cycles, and monthly updates for routine monitoring. Document structures include product parameter tables, technical principle explanations, market performance analyses, and compliance requirement chapters. Fields include rated smoke exhaust volume (unit: m³/h), heat load index, installation reserved space (unit: mm), gas source adaptation type, and noise value (unit: dB(A)). There is no unified fixed format template.
What constraints do these characteristics impose on the knowledge base retrieval and recall link?
Differences in data formats across sources require the retrieval link to distinguish between structured parameters and unstructured analysis content, and set differentiated matching weights. Differences in update frequencies require configuring incremental update trigger conditions to match new product launches and routine monitoring update cycles. The diversity of document structures requires retrieval to cover both precise keyword matching and semantic association matching to avoid missing key parameters or analysis content. Specific unit requirements for fields mandate retaining the original data format to prevent matching failures caused by unit conversion, and require verifying field integrity to ensure the accuracy of recalled content.
How to configure the settings
| Configuration Item | Recommended Value Range | Rationale |
|---|---|---|
chunkSize | 800–1200 characters | Adapts to the length of parameter entries and analysis paragraphs in kitchen and bathroom appliance research reports, avoiding semantic segmentation breaks or insufficient recall accuracy |
recallTopK | Top 8–12 results | Balances precise parameter recall and coverage of trend analysis content, avoiding excessive irrelevant information interfering with retrieval results |
similarityThreshold | 0.72–0.85 | Adapts to the high matching requirements of parameter content and semantic flexibility of analysis content, covering different retrieval scenarios |
incrementalUpdateTrigger | New product tag trigger + monthly scheduled task | Matches the new product launch cycle and routine monitoring data update rhythm of kitchen and bathroom appliances |
parseTimeout | 300 seconds | Adapts to the parsing time requirement for single research reports containing multiple product parameter tables |
rerankTopK | Top 4–6 results | Retains core content after reranking recall results, improving the relevance of final responses |
The parameter values provided on this page are conventional recommendations used as a starting point for configuration. Actual values are affected by material form, data volume, and business rules. Specific issues require case-by-case analysis, and it is recommended to test on your own samples before finalizing settings.
Three common mistakes
- Phenomenon: A web search node is configured in the workflow, but execution directly calls the large model to generate content without triggering an HTTP request. Cause: No trigger condition for web search is configured in the retrieval and recall link, or the parameter settings of the trigger condition are incorrect.
- Phenomenon: Markdown first- and second-level heading levels are lost in imported research report documents. Cause: The option to retain original document format is not enabled in parsing configuration, or the segment length setting is inappropriate, causing headings to be split.
- Phenomenon: After retrieval results are returned, the response content contains the phrase "Citation: [1]". Cause: No instruction to remove citation markers is configured in the large model prompt, or the prompt format does not match the model's output rules.
How to confirm correct configuration
- Upload a single kitchen and bathroom appliance research report, check the parsed segmented content, and confirm that the segmentation of parameter entries and analysis paragraphs meets expectations.
- Enter a search term containing specific kitchen and bathroom appliance parameters, verify that the recalled results include matching parameter data, and adjust the similarity threshold and number of recalled entries.
- Trigger an incremental update task, check the synchronization log, and confirm that new product tags and scheduled tasks are triggered as expected.
- After configuring the large model prompt, generate a test response, verify that citation markers are removed, and confirm that the prompt format 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.